Entamoeba histolytica, among them is EhSyf. Molecular predictions confirmed that EhSyf contains 15 type 1 TPR tandem α-antiparallel array motifs. Amoeba transformants carrying plasmids overexpressing HA-tagged or EhSyf silencing plasmids were established to monitor the impact of EhSyf on the splicing of several test Entamoeba transcripts. EhSyf Entamoeba transformants efficiently silenced or overexpressed the proteins in the nucleus. The overexpression or absence of EhSyf notably enhanced or blocked splicing of transcripts irrespective of the strength of their 3′ splice site. Finally, the absence of EhSyf negatively affected the transcription of an intron-less transcript. Altogether our data suggest that EhSyf is a bona fide Syf1 ortholog involved in transcription and splicing.Syf1 is a tetratricopeptide repeat (TPR) protein implicated in transcription elongation, spliceosome conformation, mRNA nuclear-cytoplasmic export and transcription-coupled DNA repair. Recently, we identified the spliceosomal components of the human parasite  ACT) when U4/U6 basepairing is unwound allowing U6 snRNA to form two mutually exclusive interactions with the 5′ss and U2 snRNA, destabilizing U1 and U4 snRNPs. The first transesterification reaction occurs when U6/U2 and U2/BS RNA/RNA interactions position the bulged BS adenosine to attack the 5′ss, producing 5′ exon and intron lariat-3′ exon intermediates. The active spliceosome undergoes various rearrangements to form complex C that carries out the second transesterification reactions, ligating the exons and removing the intron-lariat  splicing  complex shuttles mRNA from the nucleus to the cytoplasm. TREX is formed by the THO complex along with mRNA export proteins UAP56/Sub2 and Aly/Yra1. Strong evidence links TREX to transcription elongation in yeast. Strains carrying mutations in any of the four THO members fail to export mRNA and are defective in transcription elongation accumulating transcripts in or near their transcription start sites . Two major NER pathways exist: global genome repair (GGR) and transcription-coupled repair (TCR). In the former, damage recognition is carried out by a DDB heterodimer which binds to the XPC-RAD23B-CEN2 complex . Of note is the E. histolytica putative ortholog of U2AF65, which participates in spliceosome/pre-mRNA (at the 3′ss of the intron)/CTD of Pol II. Factors of the Entamoeba histolytica NTC, Prp19 (EHI_13870), Cwc2 (EHI_126150), Cef1 (EHI_000550) and Syf (EHI_073300) were also identified. Furthermore, microarray data showed that EhSyf transcripts were overexpressed in amoebas transformed with HA-U1A (not shown) and splicing factor 1 (SF1). Trying to understand EhSyf participation in fundamental biological processes and to provide evidence about a key molecule that links transcription and splicing in a deep branched eukaryote, we cloned and characterized the general impact of EhSyf on splicing irrespective of 3′ss strength of Entamoeba virulence-related and virulence-unrelated introns.The protozoan parasite E. histolytica trophozoites strain HM-1:IMSS Cl-6 were incubated at 37°C in 13 × 100 mm screw-capped Pyrex glass tubes or plastic culture flasks in BI-S-33 medium as described  of amoeba transformants were separated by 10% SDS-PAGE and analyzed by western blotting using mouse anti-αSyf , goat anti-Pol II (Santa Cruz Biotechnology), mouse anti-Actin, and secondary horseradish peroxidase-conjugated anti-IgG antibody (Sigma-Aldrich). The human anti-αSyf antibody target in EhSyf was validated by CLUSTALW alignment Figure . Enhancein vivo splicing assays EhSyf, Sam50, RabX13, MybS6, ClcB1, Cdc2, actin, and RNA polymerase II expression was monitored by RT-PCR. Total RNA of amoeba transformants was extracted with Trizol (Invitrogen) and the synthesis of cDNA was performed using the SuperScript III First Strand Synthesis System (Invitrogen) according to the manufacturer's instructions. Unspliced pre-mRNA/intron retained (IR) and mRNA molecules were detected with their respective primers  using the neighbor-joining method; the significance of nodes was assessed using a bootstrap test with 1,000 , Saccharomyces cerevisiae (NP_010704), Drosophila melanogaster ORF de CG6197 accession number NP_610891, Caenorhabditis elegans ORF C50F2.3, accession number NP_491250, Schizosaccharomyces pombe ORF SPBC211.02c, accession number NP_596612 were carried out. EhSyf modeling was carried out with I-Tasser. For RT-PCR and western blots, differences between means were determined by t-test with GraphPad Prism 5.0. p-values were calculated comparing all pairs of the expression percentages obtained from the normalized IntDen values of densitometries using ImageJ. To eliminate plasmid transfection-effect, differences of transcript-expression values were normalized with respect to 18S rRNA (EhSyf) or RNA polymerase II (monitor transcripts) and were expressed as percent of the total expression (unspliced plus spliced gene products) as previously reported  proteins were identified in the initial BLAST.We first performed phylogenetic inference of EhSyf. All EhSyf hits in the BLAST analysis were used to construct the rooted phylogeny tree Figure . As expein silico structural models, EhSyf contains 15 TPR class I , S. pombe , D. melanogaster , and C. elegans .TPR proteins participate in a wide variety of functions involving protein-protein interactions  are strong and conserved in Entamoeba (Hon et al., s Figure . Statists Figure . Unexpecs Figure , indicatEhSyf gene encodes a tetratricopeptide repeats protein involved in several nuclear functions. The Entamoeba Syf gene products appear to have low copy number that can be boosted during transfection of unrelated genes. This might reflect the direct/indirect participation of EhSyf in transcription, or it might reflect that the introduction of plasmid DNA evokes general transcription/DNA-repair mechanisms, increasing in turn EhSyf transcripts. The impact of plasmid transfection on endogenous genes has been documented since the pioneering works attempting heterologous expression of proteins in E. histolytica (Hamann et al., EhSyf expression directly impacts splicing in a general manner. This reflects its relationship with the large subunit of U2AF which binds to poly-pyrimidine tracts in front of the 3′ss, and tethers the pre-mRNA/spliceosome to the CTD. Interestingly, EhSyf silencing but not overexpression, negatively affected transcription even of intron-less genes indicating its role in transcription elongation.bona fide Entamoeba histolytica Syf1 ortholog that participates in splicing and transcription elongation. To our knowledge this is the first evidence of the molecular link between transcription and splicing in Entamoeba histolytica.Together, our data suggest the coordinated functions of EhSyf in transcription and splicing in this early branched protist. Although the impact of EhSyf in transcription termination and mRNA export still remains to be tested. We conclude that EhSyf is a JV, DT-C conception, experimental design, manuscript preparation; DT-C, JG-R, OS-C, and JV data acquisition and interpretation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


AFF4 and POL2RA, which encodes a subunit of RNAPII. Loss of PTEN also increased cells’ sensitivity to transcription inhibition via small molecules, which could provide a strategy to target PTEN-deficient cancers. Overall, our work describes a previously unappreciated role of nuclear PTEN, which by interacting with the transcription machinery in the context of chromatin exerts an additional layer of regulatory control on RNAPII-mediated transcription.Regulation of RNA polymerase II (RNAPII)-mediated transcription controls cellular phenotypes such as cancer. Phosphatase and tensin homologue deleted on chromosome ten (PTEN), one of the most commonly altered tumor suppressors in cancer, affects transcription via its role in antagonizing the PI3K/AKT signaling pathway. Using co-immunoprecipitations and proximal ligation assays we provide evidence that PTEN interacts with AFF4, RNAPII, CDK9, cyclin T1, XPB and CDK7. Using ChIP-seq, we show that PTEN co-localizes with RNAPII and binds to chromatin in promoter and putative enhancer regions identified by histone modifications. Furthermore, we show that loss of PTEN affects RNAPII occupancy in gene bodies and further correlates with gene expression changes. Interestingly, PTEN binds to promoters and negatively regulates the expression of genes involved in transcription including  Phosphatase and tensin homologue deleted on chromosome ten (PTEN) is a dual specificity phosphatase that is inactivated or lost in a large proportion of human cancers, making it one of the most commonly mutated tumor suppressors ,2. PTEN It has been described that loss of PTEN alters gene expression programs associated with poor prognosis . PTEN ha1S2P3T4S5P6S7) of the RNAPII subunit RPB1 C-terminal domain (CTD)  . During in (CTD) , which tin (CTD) . Upon enin (CTD) ,21, as win (CTD) . P-TEFb in (CTD) . The scain (CTD) . The P-Tin (CTD) . The actin (CTD)  and the in (CTD)  and negain (CTD) .As transcription is an essential process in normal as well as malignant cells and tissues, it has long been regarded a challenging target in cancer therapy. RNAPII-mediated transcription can be inhibited at different stages during the transcription cycle, for example during initiation or elongation. CDK7 kinase activity can be effectively inhibited by the covalent CDK7 inhibitor THZ1 . TranscrHere, we report that nuclear PTEN binds to components of the transcription machinery and that its genome-wide distribution in chromatin correlates with RNAPII, H3K4me3, and H3K27ac at promoters, and H3K27ac and H3K4me1 in distal regions. Loss of PTEN increases levels of RNAPII Ser2P and Ser5P that in turn leads to a genome-wide increase in RNAPII Ser2P and Ser5P occupancy in gene bodies and altered gene expression. Changes in chromatin occupancy and gene expression due to PTEN mutation correlated most strongly at PTEN-bound genes, which included components of the transcription machinery and transcriptional regulators. PTEN loss also upregulates a subset of genes, whose expression renders cells more susceptible to transcription inhibition by small molecule inhibitors. In summary, our findings indicate that PTEN functions in the nucleus, where by interacting with the transcription machinery it provides an additional layer of regulatory control on RNAPII-mediated transcription and gene expression.PTEN vector and the pIRES-FLAG-C2TAIL vector were previously described (PTEN as a template. The AFF4 bait-fragment was cloned into the pcDNATM3.1/V5-His vector using the TOPO® TA Expression Kit (Invitrogen) via topoisomerase ligation of Taq-Polymerase generated PCR purified fragments using full length AFF4 as a template.Bacterial expression plasmids encoding GST-PTEN domains have been reported previously . The MSCescribed . The PTEAll antibodies are listed in the l-glutamine  (Cellgro). HEK293 and HeLa cells were cultured in Dulbecco's minimal essential medium (Cellgro) supplemented with 10% (vol/vol) fetal bovine serum (FBS), 100 IU penicillin, 100 μg/ml streptomycin (Cellgro). DBTRG-05MG and HCT116 cells were cultured in RPMI-1640 supplemented with 10% (vol/vol) FBS, 100 IU penicillin and 100 μg/ml streptomycin.MycOE Pik3ca Mut cells, MycOE Pten Null cells and mouse embryonic fibroblasts were cultured in Dulbecco's minimal essential medium (Cellgro) supplemented with 10% (vol/vol) fetal bovine serum (FBS), 100 IU penicillin, 100 μg/ml streptomycin (Cellgro) and 2 mM Ptenflox/flox mice  (Cellgro). For deletion of Pten, MEFs were infected with adenovirus Adeno-CMV-Cre-recombinase (Vector Biolabs) or Adeno-CMV-Null (Vector Biolabs) as a control.lox mice  in a C57PTEN targeting guide RNA (ACAGATTGTATATCTTGTAA NGG) was generated previously .1500 cells were plated per well in a 96-well plate in triplicate for each experiment. Proliferation was monitored by analyzing the occupied area (% confluence) of cell images over time as recorded by the IncuCyte ZOOMCell fractionation was performed as described before . The det2) and proteins were eluted using 0.5 mg/ml V5 peptide (Sigma-Aldrich).HEK293 cells were co-transfected with FLAG-tagged PTEN-C2TAIL and V5-tagged AFF4 or empty vector (EV), respectively. Cells were lysed in BC200 buffer , sonicated, centrifuged and pre-cleared with protein A/G agarose beads. Supernatants were incubated with anti-V5 agarose beads, beads were washed with TBS . The extended protocol is provided in the GST fusion proteins were purified as previously described . In vitrHEK293 cells were lysed in BC200 . Lysates were sonicated, centrifuged, and then pre-cleared using Pierce™ protein A/G magnetic beads (ThermoFisher Scientific). Supernatants were incubated with PTEN (6H2.1) or mouse IgG crosslinked to Pierce™ protein A/G magnetic beads using dimethyl adipimidate (ThermoFisher Scientific). Beads were washed four times with BC200 and proteins were eluted with 0.1 M glycine pH 2.0.® In Situ Red Starter kit mouse/rabbit or goat/rabbit, Sigma-Aldrich). In brief, 20 000 HeLa cells were plated on gelatin-coated, 16-well chamber slides, fixed with 2% Paraformaldehyde, permeablized in perm/block solution  and incubated with primary antibodies diluted 1:100 overnight at 4°C. PLA detection was performed and images were taken with a confocal microscope (Zeiss LSM 880 with Airyscan) at a magnification of 63x and analyzed with the ImageJ software.PLA assays were performed according to the manufacturer's protocol (DuoLinkPTEN HeLa cells was processed using the TruSeq RNA Sample Preparation kit V2 (Illumina). Libraries were sequenced using the NextSeq® 500/550 High output Kit v2 (75 cycles) on a NextSeq® 500 sequencing system (Illumina). mRNA-seq analysis was performed as previously described  on a NextSeq® 500 sequencing system (Illumina). Extended protocols and the data analysis procedure are provided in the One-step and two-step crosslinking ChIP experiments were performed as described before ,41. One-Pten (Nuclear PTEN has been extensively studied in mouse embryonic fibroblasts (MEFs), where it was shown to be associated with chromatin . To furtPten . By immuPten . HoweverPten . NuclearPten , suggestTo further characterize the Pten nuclear pool, we performed cellular fractionation experiments. As expected the majority of Pten resided in the cytosolic fraction Figure . Howeverin vitro transcribed/translated full-length AFF4  screen using the PTEN C2TAIL-domain, which is thought to facilitate most of PTEN’s known interactions with other proteins , as the 4 Figure . GST-PTE4 Figure  and HEK24 Figure , indicat4 Figure  23). PT. PTin vi4 Figure  17), in, inin vi4 Figure . Further4 Figure .PTEN was deleted employing the CRISPR/Cas9 system using a guide RNA targeting exon 3 and a small part of the downstream intron of the endogenous PTEN locus (CRISPR-PTEN)  Figure  35). We. WePTEN 7 Figure –I. Using7 Figure –I. ColleMoreover, we analyzed nuclear extracts from PTEN WT HeLa cells by size exclusion chromatography, which is a useful tool to isolate large multi-subunit complexes (i.e. transcription complexes) and to identify potential interactors . These sPTEN HeLa cells using two different antibodies against PTEN  > 5), in the PTEN WT cells  in PTEN WT and CRISPR-N Figure  41). By. ByPTEN s Figure ,45, H3K4s Figure ,47  analysis. This identified gene sets involved in important cellular processes including cellular metabolism, cell cycle, as well as gene expression ,51 Figu, suggestPTEN HeLa cell lines. Notably, PTEN-bound genes are expressed at higher than median levels  data from PTEN WT and CRISPR-s Figure  and losss Figure . Genes ws Figure , left. Ms Figure ; right, PTEN HeLa cells, as well as in Pten−/− MEFs and a Pten−/− mouse breast tumor cell line (MycOE Pten Null) (Transcription regulation is highly complex and can be accomplished through a multitude of mechanisms including the phosphorylation of the RNAPII CTD . Inspecten Null)   –C when cPTEN HeLa cells . RN. RN−/− v changes . OverallWe next wanted to examine the changes in chromatin occupancy of RNAPII, RNAPII Ser2P and Ser5P, and SPT5 at PTEN-bound genes. The correlation between chromatin occupancy and gene expression was slightly stronger at PTEN-bound genes than at genes genome-wide , indicatAs changes in chromatin occupancy are not always reflected in gene expression changes, we analyzed these relationships at differentially expressed and differentially expressed PTEN-bound genes. As expected, the correlations of changes in chromatin occupancy and gene expression were stronger at differentially expressed genes than at genes genome-wide Figure ; top. MoPTEN HeLa cells and performed RT-qPCR to probe for changes in gene expression before and after PTEN re-expression. As expected loss of PTEN did increase the expression levels of several of the PTEN-bound genes examined (PTEN HeLa cells decreased the expression of three out of four genes tested (We next over-expressed wild type PTEN (PTEN WT) in our PTEN-depleted CRISPR-examined . Re-exprs tested , indicatOverexpression of genes involved in cell signaling and transcription has been to shown to render cells more susceptible to transcription inhibition with small molecule inhibitors such as the CDK7 inhibitor THZ1 ,53. NotaPTEN HeLa cells, but did not detect a difference in the sensitivity of the PTEN deleted cells  during the cell cycle , raisingbociclib  57), su, su−/− MNext, we over-expressed wild type PTEN (PTEN WT) or phosphatase-dead PTEN C124S in MycOE Pten Null cells. While expression of PTEN WT decreased sensitivity to transcription inhibition by THZ1 or Flavopiridol Figure  and H, eIn this study we identified a nuclear pool of PTEN that interacts directly with AFF4 and directly or indirectly with RNAPII, CDK9, cyclin T1, XPB and CDK7, which are components of different transcription complexes. In our model, PTEN can interact with RNAPII and XPB and CDK7 during initiation and with AFF4, RNAPII, CDK9 and cyclin T1 during elongation ; top. Fuin vitro transcribed/translated AFF4, we can only speculate whether the interactions are direct or indirect. As RNAPII is a commonality between these complexes and associates with, for example, TFIIH during initiation and P-TEFb during elongation  and are genetically aberrant with a deletion of the STK11 gene, encoding the tumor suppressor LKB1  under accession number GSE120478.ChIP-seq peaks, RNA-seq and microarray data can also be found in gkz272_Supplemental_FilesClick here for additional data file.


Progesterone and its receptor, PR, are essential for uterine leiomyoma  tumorigenesis, but the underlying cellular and molecular mechanisms remain unclear. The receptor activator of NF-κB (RANKL) was recently identified as a novel progesterone/PR-responsive gene that plays an important role in promoting LM growth. Here, we used RANKL as a representative gene to investigate how steroid hormone, genetic, and epigenetic signals are integrated to regulate LM stem cell (LSC) function. We demonstrated that RANKL specifically upregulates LSC proliferation through activation of Cyclin D1. RANKL gene transcription was robustly induced by the progesterone agonist R5020, leading to a dramatically higher RANKL expression in LM compared to adjacent myometrial (MM) tissue. MethylCap-Seq revealed a differentially methylated region (DMR) adjacent to the distal PR-binding site (PRBS) 87 kb upstream of the RANKL transcription start site. Hypermethylation of the DMR inhibited recruitment of PR to the adjacent PRBS. Luciferase assays indicated that the DMR and distal PRBS constitute a novel RANKL distal regulatory element that actively regulates RANKL expression. Furthermore, MED12 physically interacts with PR in LM tissue. The interaction between MED12 and PR, binding of PR and MED12 to PRBS, and RANKL gene expression are significantly higher in LM containing a distinct MED12 mutation (G44D) than in LM with wild-type MED12. In summary, our findings suggest that DNA methylation and MED12 mutation together constitute a complex regulatory network that affects progesterone/PR-mediated RANKL gene expression, with an important role in activating stem cell proliferation and fibroid tumor development. Uterine leiomyomas  represent the most common gynecological tumors in women. By age 50, about 80% of women will develop at least one LM, and 15–30% will develop severe symptoms, including excessive uterine bleeding, recurrent pregnancy loss, and pelvic pain; these symptoms may mimic or mask malignant tumors . ConsideProgesterone P4) and its receptor, PR, play essential roles in LM development; however, the cellular and molecular mechanisms responsible remain unclear . Anti-pr and its Receptor activator of nuclear factor κB ligand (RANKL), a P4/PR target gene, recently became a key actor in oncology . The molEpigenetic alterations, such as DNA methylation, play crucial roles in regulating gene expression and disease progression . DNA metMutation of mediator complex subunit 12 (MED12) is the most prevalent mutation (mut-MED12) in LM, occurring in over 70% of all LMs . LM-assoHere, we used RANKL as a representative P4/PR target gene to study the genetic and epigenetic mechanisms underlying dysregulated RANKL expression in LM, which will also shed mechanistic light on our understanding of RANKL gene regulation and PR action in breast cancer and other steroid-responsive tumors .n = 43 patients). RANKL mRNA was significantly higher in LM compared with matched MM tissues , CD34+/CD49b− , and CD34−/CD49b−  [There are three distinct cell populations in LM based on CD34 and CD49b expression: CD34d cells) . Based oTo evaluate the mechanism underlying the percentage change of LM cell populations after RANKL treatment, we conducted proliferation (CCK8 assay) and apoptosis (Annexin V staining) assays. RANKL specifically increased LSC proliferation Fig.  without Our finding that RANKL plays a critical role in regulating LSC function and LM tumorigenesis prompted us to further explore the mechanism underlying dysregulated RANKL gene expression in LM . RANKL iR2 = 0.8252), suggesting that the distal PRBS is an enhancer region that regulates RANKL transcription  data in LM cells and found multiple PR-binding sites (PRBS) around RANKL gene locus . A regioion Fig. .R2 = 0.7407) with PR binding at the distal PRBS . This region has strong gene transcription regulatory activity and is enriched with DNA-binding motifs of AP-1 and PRE half sites, which are important for PR recruitment to DNA –26. To eRBS Fig. . Next, wRBS Fig. . This suRBS Fig. .To examine whether the enhanced PR binding around the RANKL gene in LM was due to differential PR expression levels between the two tissues, we measured PR mRNA and protein levels in the tissues used in the ChIP-qPCR. The PR mRNA level in LM was only marginally higher (1.3-fold) than in MM tissue  between untreated MM and LM cells. Intriguingly, 44.23% of DMRs were found to be located in intergenic regions Fig. . NetworkMotif enrichment analysis of all DMRs between LM and MM showed that PREs (PR and androgen receptor (AR) bind to essentially identical motifs), together with several other critical TF binding elements such as HIF-1b and Smad2, were highly enriched at DMRs Fig. . Since POur findings suggested that DNA methylation may contribute to the global difference in progesterone responsiveness of LM and MM through interference of PR-binding activity. We specifically examined DMRs adjacent to the RANKL gene locus and discovered a hypermethylated region located 500 bp upstream of the distal PRBS in MM versus LM cells, which was de-methylated after 5ʹ-aza treatment, but no methylation difference was detected adjacent to the RANKL promoter Fig. . Using MTo test whether DNA methylation affects PR-binding activity at the distal PRBS of the RANKL gene, we treated primary MM and LM cells with 5ʹ-aza (5 µM) or vehicle (DMSO) for 4 days and examined PR recruitment to this region. In vehicle-treated cells, PR-binding activity was significantly higher in LM than in MM cells Fig. . ConsistFurthermore, we evaluated the effects of 5ʹ-aza and R5020 treatment on chromatin interaction activity between the distal PRBS and the RANKL promoter using 3C-qPCR. In MM, the looping activity between these two regions in vehicle-treated cells was weak, increased slightly with either 5ʹ-aza or R5020 treatment, and peaked when the two treatments were combined Fig. . ConsistWe recently reported that RANKL is preferentially expressed and specifically upregulated by R5020 in LIC , we wentTogether, our findings indicate that the novel DMR upstream of the distal PRBS may mediate RANKL expression. We designated the DNA fragment spanning the novel DMR and the distal PRBS as the RANKL distal regulatory element (RDRE). To determine whether the RDRE has a regulatory function in RANKL gene transcription, we cloned the 1496 bp RDRE  into a CpG-free luciferase construct and performed luciferase reporter assays . As showMutations in MED12 alter its interaction with transcriptional co-activators and induce E2 + P4-dependent LM formation , 34; thi2 = 0.6282) and PR-binding affinity in this region  in LM with G44D mut-MED12. Supporting the pro-proliferation role of RANKL in LSC, we detected a marginally larger (P = 0.0551) LSC population in LM harboring G44D mutation versus wild type (WT) LM  MED12 Fig.  (MM tissWe uncovered a novel cis-regulatory element (RDRE) downstream of P4/PR signaling that regulates RANKL transcription. We demonstrated that RANKL expression is regulated by converging signals from steroid hormone (P4/PR), genetic factors (MED12 mutation), and epigenetic modifications (DNA methylation and histone modification) and contributes to LSC proliferation and tumor formation. We summarize our proposed model of P4/PR-mediated RANKL gene regulation in Fig. The RANKL/RANK pathway is known for its crucial role in paracrine signaling between stem and differentiated cells in breast cancer, where RANKL, released from PR-positive cells upon P4 stimulation, binds to its receptor on PR-negative progenitor cells and stimulates tumorigenesis through expanding the progenitor cell population . RANKL iPrevious studies have demonstrated that RANKL transcription is directly regulated by DNA methylation at its promoter in bone and mammary gland tissues , 36. HowFurthermore, gene transcription is also controlled by extensive crosstalk and interactions between DNA methylation and histone modifications. For example, in embryonic stem cells, H3K4 methylation  can prevent the binding of DNA methylation machinery DNMT3L, resulting in lower methylation levels at nearby CpG sites . ConsistThe human mediator complex was first identified through an intracellular ligand-dependent association with thyroid hormone receptor . Since tIn support of our findings, previous researches have demonstrated that LM-associated MED12 mutations could alter its interaction with proteins involved in transcriptional co-activator pathways, such as the loss of mediator-associated CDK activity , 18. MEDIn summary, our findings suggest that DNA methylation, histone modification, and MED12 mutation status together constitute a complex regulatory network that influences P4/PR-mediated RANKL transcription. Using RANKL as a representative PR target gene, our study provides novel and important insights into the regulation of PR action and provides rationale for further elucidation of P4/PR-mediated transcriptional regulation in LM. Dissecting the relationship among TF binding, histone modification, and DNA methylation will improve our understanding of the mechanisms underlying LM development. Considering the heterogeneous genetic background of LM pathogenesis, our studies also represent a key step towards a better understanding of mechanisms underlying the pathogenesis of specific LM subtypes and the necessity for personalized therapeutic strategies.Northwestern University’s Institutional Review Board approved the use of human tissue. LM and matched MM tissues were obtained from premenopausal women undergoing either myomectomy or hysterectomy . Patients receiving hormone treatment 6 months prior to surgery were excluded. Tissues were dissociated and cells isolated as previously described .−6 M) for 48 h. To elucidate the role of RANKL in LSC function, the explants were subjected to vehicle or RANKL  treatment for 24 h and analyzed using flow cytometry.Primary cells and ex vivo explant culture of MM and LM tissue were performed as previously described , 11. ForEach freshly FACS-sorted population of LM cells was cultured in mesenchymal stem cell growth medium  in low-attachment 96-well plates  to maintain stem cell characteristics. After 5 days, cells were starved for 24 h using basal mesenchymal stem cell growth medium followed by treatment with RANKL or vehicle for 24 h. Apoptosis assay was performed using Annexin V-FITC Apoptosis Detection Kit  on FACS-sorted cells treated with vehicle or RANKL for 24 h and analyzed using flow cytometry. Proliferation assay was performed using Cell Counting Kit-8 .LM passage zero cells were transfected with two different PR siRNAs  or control siRNA (D-001810-10-05) for 96 h, and stimulated with vehicle or R5020 for 24 h before harvesting.All antibodies and primers used in this study are listed in Supplementary Table +/CD49b+, CD34+/CD49b−, and CD34−/CD49b− LM cells were FACS-sorted as previously described [CD34escribed .About 0.2–1 µg of total RNA was reverse transcribed and quantified using real-time PCR as previously described .Paraffin-embedded LM and MM tissues were sectioned and immunohistochemistry was performed by the Northwestern University Pathology Core Facility to detect RANKL expression as previously described . The scoAbout 0.2–0.5 g of frozen LM and matched MM tissues were used for ChIP using the SimpleChIP Kit . Chromatin was isolated and incubated with antibodies against PR, MED12, H3K4me3, H3K27Ac, or H3K27me3. Normal rabbit IgG was used as a negative control.Genomic DNA was extracted from LM and MM tissues or cells using DNeasy Blood and Tissue Kit  and fragmented to 300–500 bp using Covaris M220 . Methylated DNA fragments were captured using the MethylCap Kit .PciI   followed by ligation with T4 ligase  in diluted condition. Ligated DNA was then de-cross-linked (overnight at 65 °C) and purified by classical phenol extraction procedures. All primers were designed within 150 bp of PciI sites and detailed information is provided in Supplementary Table 3C assay was performed and analyzed following previously published protocol . BrieflyI 400 U, ,000 U/mlNext-generation sequencing libraries for MethylCap-Seq and PR ChIP-Seq were prepared using the KAPA Hyper Prep Kit  and KAPA Single-Indexed Adapter Kit . The libraries were sequenced at the Northwestern University NUSeq Core Facility using the NextSeq 500 system  with 20–30 million reads per sample (75 bp single-end for PR ChIP-Seq and 75 bp paired-end for MethylCap-Seq). Sequences were aligned to the hg19 reference genome using Bowtie2. We performed following analysis using Homer: peak calling (-style factor for PR ChIP-Seq and -style histone for MethylCap-Seq), differential binding analysis  and motif analysis (findMotifsGenome.pl) . PathwayAbout 0.2–0.5 g of frozen LM and MM tissues were lysed in non-denaturing buffer  containing protease inhibitor  for 2 h at 4 °C. One hundred and fifty microgram protein lysate was used for IP following previously published protocol . Five peWhole-cell extracts were prepared and western blot analysis was performed as previously described . ImageJ The RANKL gene distal cis-regulatory element spanning the novel DMR and distal PRBS (RDRE) was amplified by PCR using primers listed in Supplementary Table P < 0.05. Similarity of variance across compared groups was tested by: F-test in two groups, Sum of Square in multiple groups. Normal distribution of data was assessed by Shapiro–Wilk test. Error bar represented SEM for biological replicates of three technical replicates within one patient. All experiments are repeated with at least three patients, with patient number stated in the figure legend.All of the statistical analysis in this study were performed using GraphPad Prism 7  with detailed statistic test description in each figure legend. Sample size was determined based on previous publications , 19. No Supplementary Figure LegendSupplemantary Figure S1Supplementary Figure S2Supplementary Figure S3Supplementary Figure S4Supplementary Table 1_PR_ChIP-Seq_LM_peaks_bedfileSupplementary Table 2_PR_ChIP-Seq_LM_higher_peaks_bedfileSupplemantary Table 3_Antibody_Primer_Info


Using an inducible system with fine temporal resolution, we show that the nucleosome remodeling and deacetylation (NuRD) complex controls chromatin architecture and the protein binding repertoire at regulatory regions during cell state transitions. This is primarily exerted through its nucleosome remodeling activity while deacetylation at H3K27 follows changes in gene expression. Additionally, NuRD activity influences association of RNA polymerase II at transcription start sites and subsequent nascent transcript production, thereby guiding the establishment of lineage-appropriate transcriptional programs. These findings provide a detailed molecular picture of genome-wide modulation of lineage-specific transcription by an essential chromatin remodeling complex as well as insight into the orchestration of molecular events involved in transcriptional transitions in vivo.Chromatin remodeling complexes play essential roles in metazoan development through widespread control of gene expression, but the precise molecular mechanisms by which they do this   •NuRD increases nucleosome density, expelling TFs or inhibiting recruitment•NuRD displaces RNA Pol II from TSSs, reducing nascent transcription•Local gains in TF and Mediator occupancy can be indirect effects of NuRD activity•Resetting protein binding at regulatory elements can promote or suppress transcription Bornelöv et al. define how NuRD, an abundant chromatin remodeling complex, fine-tunes gene expression. NuRD controls nucleosome positioning across regulatory elements genome-wide, controlling access of DNA-binding proteins to enhancers and promoters. This resetting of the transcription factor repertoire at regulatory elements restricts expression from some loci and induces transcription at others. The nucleosome remodeling and deacetylation (NuRD) complex is an abundant, highly conserved multiprotein chromatin remodeler initially defined as a transcriptional repressor . NuRD acNuRD is an abundant chromatin-associated protein complex, and its components have been reported to physically interact with a wide repertoire of transcription factors. Indeed, a few of these have been shown to recruit NuRD to specific DNA sequences to influence transcription of individual target genes e.g., . Genome-The Mbd3 protein was originally identified by sequence similarity to the methyl-CpG binding protein Mecp2, but the putative methyl-CpG binding domain of Mbd3 contains mutations that prevent binding to methylated DNA . Mbd3 isMbd2 and Mbd3 are mutually exclusive components of NuRD, and Mbd2/NuRD and Mbd3/NuRD have been found to exhibit distinct but overlapping functions . In mousHow the two distinct enzymatic activities of NuRD individually influence the transcriptional machinery is not clear. NuRD activity results in loss of H3K27 acetylation, providing a substrate for PRC2-mediated trimethylation at some sites . The nucIn this study, we set out to determine how NuRD fine-tunes gene expression. Using an inducible ESC system with fine temporal resolution, we show that transcriptional control by the NuRD complex is primarily exerted through its chromatin remodeling activity. NuRD acts at regulatory sequences to increase nucleosome density, which in turn influences the ability of transcription factors, coactivators, and RNA polymerase II to associate with those sequences. We further demonstrate that NuRD-dependent nucleosome rearrangements are used by cells to control protein access to enhancers during lineage commitment. This shows how the dual enzymatic activities of one chromatin-modifying complex impact the transcription machinery to precisely control transcription levels during cell state transitions.Two NuRD component proteins, the ATP-dependent helicase Chd4 and the scaffold protein Mbd3, associate with chromatin extensively in ESCs A and S1BMbd3-null ESCs  on known NuRD target sequences between 15 and 30 min after tamoxifen addition, where enrichment continued to increase over 48 hr C. BindinMbd3−/− ESCs , a mark generally associated with active transcription, is anticorrelated with NuRD activity . We therPpp2r2c and Htra1; Genes for which a change in mRNA levels was detectable within 8 hr of tamoxifen addition showed no significant differences in H3K27Ac within this time frame  digestion followed by high-throughput sequencing (MNase-seq). MNase cuts DNA efficiently at relatively open chromatin but digests less efficiently at sites associated with DNA binding proteins or nucleosomes and can therefore be used to map regions of open chromatin and to define sequences frequently associated with nucleosomes. Mbd3 induction resulted in a rapid (<30 min) and pronounced increase in protection from MNase digestion at Chd4- and Mbd3-bound sites genome-wide A. This mPpp2r2c and Bmp4  was quickly lost, and MNase resistance was gained at flanking sites . For Med12, we performed a similar analysis using Mbd3-null cells and inducible cells after 24 hr of induction. These are sites that we predict would gain or lose TF/Med12 binding, respectively, during Mbd3 induction. We then compared protein occupancy and MNase accessibility at these two different classes of sites for each protein across the time course. Sites with highest Nanog, Klf4, or Med12 binding in Mbd3-null cells all showed a significant loss of protein enrichment within 30 min of Mbd3 induction  or in Sites at which Nanog, Klf4, or Med12 binding was lower in Mbd3 KO cells than in WT cells  showed no consistent pattern of behavior. At Nanog sites, Mbd3 induction was associated with a rapid loss of MNase protection, consistent with NuRD acting to make these sites more accessible, although increases in Nanog protein binding were not detected until 4–24 hr B. At MedPpp2r2c enhancer showed an acute and sustained loss of all chromatin-associated proteins tested upon Mbd3 induction, coincident with rapid stabilization of the +8.3 Kb nucleosome , although at other genes, the result of re-establishment is an overall increase in stable transcript levels (up genes). Therefore, by resetting the local nucleosome landscape and clearing the TSS of RNA polymerase II so that a new transcriptional state is established, one chromatin remodeling complex can act to repress some genes and activate others. The activity exerted by NuRD is the same at all target sites, namely altering nucleosome density. Yet the impact this has differs at specific genes, presumably due to variation in the architecture of the regulatory element in question.Klf4 and Zpf42 (Rex1), but not the primed pluripotency marker Otx2. Upon withdrawal of self-renewal factors, cells exit naive pluripotency, downregulating Klf4 and Zfp42 and upregulating Otx2. These initial effects are observed in both WT and Mbd3-null cells, but in the absence of Mbd3, gene expression changes proceed more slowly , supporting targeting mechanisms more tightly linked to the transcription process itself. The downstream effect of nucleosome remodeling activity differs in a locus-specific manner. What governs whether a gene is up- or downregulated in response to NuRD remains to be defined but is likely to be determined by the underlying DNA sequence and affinity of transcription factors for sites therein.Mbd3 WT and Mbd3 KO ESCs could therefore be argued to be “directly regulated by NuRD”. This does not distinguish between gene expression changes occurring as a primary consequence of Mbd3 loss and those that occurred as a consequence of the cells having been selected to survive and proliferate in the absence of Mbd3/NuRD. Differentiating between these two scenarios is important for understanding how NuRD, or indeed any chromatin remodeler, regulates transcription. Furthermore, combining ChIP-seq data with observations from steady state knockout lines led us to propose that NuRD can act as both activator and repressor of transcription .Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Brian Hendrich  cells were cultured in 2i/LIF (2iL) media on gelatin-coated plates unless otherwise specified. escribed  and werehttps://doi.org/10.17632/2whjxyxyc9.1Immunoprecipitation and western blotting were carried out using standard methods. Antibodies and concentrations used are listed in Chromatin immunoprecipitation (ChIP) was performed using standard protocols. Fixation was carried out using 1% formaldehyde 10 minutes at room temperature and quenched with 150 mM glycine. DNA was fragmented in the presence of 0.4% SDS using a Bioruptor sonication instrument (Diagenode) producing a size range of 200 to 300 bp. Antibodies used are listed in ChIP-seq libraries were filtered for adaptor sequences and aligned to the mouse reference genome (mm10/GRCm38) using Bowtie (v1.0.1/1.1.1)  with parMbd3−/− cells were identified using diffBind . Peaks were filtered for regions blacklisted by ENCODE.Values for read densities were adjusted by subtracting those found in the corresponding input experiment normalized for sequencing depth with deeptools (v1.6.0). We calculate ChIP-seq enrichment in 10bp bins as Reads per Genomic Content (RPGC).Regions enriched for H3K4me1 were categorized into inactive enhancers (without H3K4me3 enrichment) or active enhancers (with overlapping H3K27ac and p300 enrichment). If more than one published dataset was available for a given histone modification or p300, only peaks called in all datasets were considered in enhancer identification.Traveling ratio was calculated for all genes in Ensembl 75, defined as the ratio of RNA Polymerase II Serine 5 phosphorylation density (RPKM) in promoters to that in the gene body and promoter C. The prMetabolic labeling of cells for purification of nascent transcript was carried out as described . Cells wLibraries for sequencing were prepared using the NEXTflex Rapid Directional RNA-seq kit (Illumina) or SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara Bio) and sequenced as above. Individual expression assays were carried out using gene-specific TaqMan probes (Life Technologies).p-values less than 0.05. For time series analyses differential expression was assessed for all pairwise comparisons against the 0 h time point.RNA-seq libraries were mapped against the mouse reference genome mm10 using GSNAP (gmap-2014- 12-17)  with par2, 0.5% IGEPAL, 150mM spermine and 500mM spermidine) at a concentration of 106 cells/ml. 1ml aliquots were centrifuged at 300 × g for 10 min at 4°C and pellets washed in 1ml digestion buffer . MNase digestion was carried out in 100ul digestion buffer containing 1mM CaCl and 2000U/ml micrococcal nuclease (New England Biolabs) at 24°C for 15min with shaking. The reaction was terminated using an equal volume of stop buffer  before RNase and Proteinase K treatment. Monosomal DNA was isolated by phenol chloroform extraction followed by gel purification and either used for library preparation in the case of MNase-seq or for quantitative PCR. Locus-specific primers and their positions relative to annotated transcription start sites are listed in For nucleosome positioning analyses, cells were grown in 2iL conditions (supplemented with tamoxifen as noted). Cells were harvested, washed in ice cold PBS and resuspended in ice cold lysis buffer , E-MTAB-6805 (nascent RNA-seq), E-MTAB-6806  and E-MTAB-6807 (MNase-seq).


Super-enhancers (SEs) are clusters of enhancers that play a key role in regulating genes that determine cell identity. Enhancer RNAs (eRNAs) are non-coding RNAs transcribed from enhancers that function to promote the enhancer's functions via multiple mechanisms, such as recruiting transcription factors to specific enhancers, promoting enhancer-promoter looping, directing chromatin accessibility, interacting with RNA polymerase II and facilitating histone acetylation. Understanding how super-enhancer RNAs (seRNAs) contribute to specific gene regulation has thus become an area of active interest. Immune checkpoint deregulation is one of the key characteristics of tumors and autoimmune diseases, and is also closely related to cell identity. Recent studies revealed a potential pathway for seRNA's involvement in regulating the expression of immune checkpoints. The present study reviews the current knowledge of eRNA function, immune checkpoint blockage mechanism, and its effect. In addition, for the first time, we explore the direct and indirect roles of seRNAs in regulating immune checkpoint expression in cancer and autoimmune diseases. The identification of substantial amounts of non-protein coding transcripts and their versatile functions is one of the most striking findings of contemporary genomic research. Only ~2% of the transcribed human genome is accounted for by protein coding exons, thus non-coding RNAs constitute the majority of transcripts . Long noNPC1L1, APOC3, and LCT in enterocytes, FOXP3, CTLA1, and IL2RA in T regulatory cells  (Enhancers are DNA elements of a few hundred base pairs in length that are characterized by acetylation. Enhancers interact with transcription factors (TFs) and promoters. A mammalian cell contains thousands of active enhancers and ~1 million active enhancers have been found in all human cells . Super-ery cells . OCT4, Nll (ESC) . These gll (ESC) . Howeverll (ESC) –12. ReseThe immune system comprises innate and adaptive immunity. Immune checkpoints, consisting of co-stimulatory checkpoints and co-inhibitory checkpoints, are vital for the maintenance of self-response and prevention of autoimmunity. They are paired molecules that act as a double check before the stimulation or inhibition of an immune response. Immune checkpoints are expressed in a tissue or cell subset-specific manner. The application of immunotherapy in a wide variety of cancers has led to significant tumor shrinkage and improved clinical outcomes in patients by revitalizing the anti-tumor immune response , 14. TheRecent studies have shown that SEs play key roles in determining cell identity in both healthy and pathological states. Over 25,000 enhancers were identified as deferentially activated in renal, breast, and prostate tumor cells, as compared with normal cells . This sucis-acting function along with interactions with the promoter and multiple TFs, including Yin-Yang 1 (YY1) and myogenic differentiation 1 (MYOD)  binding, mediator complex subunit 12 binding, and a high sensitivity to nucleases –22. A ty1 (MYOD) , 23. Enh1 (MYOD) . RNAP II1 (MYOD) . By inve1 (MYOD) . The lev1 (MYOD) . Moreove1 (MYOD)   .RNAs transcribed from enhancers can be classified as short, bi-directional, and non-polyadenylated eRNAs, and long, unidirectional, and polyadenylated eRNAs. The majority of seRNAs are capped and polyadenylated RNAs . This feThe exact function of eRNAs is incompletely understood; nevertheless, evidence suggests that at least some eRNAs play an active part in the regulation of enhancer activity and gene expression. Nicholas et al. found that the synthesis of eRNAs precedes the transcription of target gene transcription in lipopolysaccharide-activated macrophages . This inThe actions of eRNAs have been widely studied in recent decades and several functional mechanisms have been proposed. The biological functions of eRNA are associated with TF recruitment, enhancer-promoter looping, chromatin conformation, and histone acetylation  7–12, 33, 34. InIFNG) eRNAs that bind nuclear factor kappa B (NF-κB) to enhance its function. Treatment of chromatin with ribonuclease led to decreased NF-κB binding to the IFNG genomic sites. Using cell transfection techniques, the authors illustrated that knockout of IFNG-R-49, an IFNG eRNA, resulted in the reduction of NF-κB binding to the IFNG-D-49 genomic site, which demonstrated that IFNG eRNAs contribute to maintaining the binding between NF-κB and the IFNG locus  loci, respectively. Normally, the MYOG locus remains inaccessible to nucleases, and chromatin remodeling is needed for the transcription activation of this locus. Using deoxyribonulcease I (DNase I) accessibility as an indicator for remodeling, the authors detected a reduction of DNase I accessibility at specific loci in eRNA-depleted cells. Additionally, they hypothesized that eRNAs are involved in regulating the assembly of transcriptional systems by observing that eRNAs affects RNAP II residency at target genes  on the promoter. NELF induces RNAP II pausing by binding to RNAP II, the promoter, and the newly generated RNA. Katie et al. suggested that eRNAs bind to NELF via competing with the nascent RNA, leading to the detachment of NELF from RNAP II, thereby enabling RNAP II elongation and mRNA synthesis  domain of CBP. This domain determines the HAT enzymatic activity and this process promotes CBP acetyltransferase activity. The authors demonstrated that eRNA binding exposes the activation loop in CBP/P300. Thus, there is an increase of H3K27ac and H3K18ac at the enhancer and promoter, which increases transcription of the target genes . Taken tcis-regulation and trans-regulation. The cis regulation by eRNAs has been widely accepted, in which the enhancer-promoter looping structure brings the eRNA close to the target gene. Using chromosome conformation capture (3C) technology, this looping model has been supported by a wide range of studies. As previously discussed, the cis-acting function of eRNAs is accomplished via their dynamic interactions with TFs, modifiers, and cohesin subunits within or near the enhancer-promoter loop. Depletion of seRNAs from distal super enhancers at the NANOG locus led to significantly decreased expression of DPPA3 . DPPA3 is the nearest gene to the NANOG super enhancer apart from NANOG itself. Using 3C, the authors demonstrated that the looping of the distal super-enhancer at the DPPA3 promoter decreased by ~50%, suggesting that the distal seRNA stabilizes the looping and chromatin interactions in cis, thereby regulating the expression of DPPA3 (CARMEN (Cardiac mesoderm enhancer-associated non-coding RNA), was found to cause activation the expression of direct downstream genes (in cis.The functions of seRNAs can be classified as of DPPA3 . Similaram genes . Taken ttrans activity) to direct target gene expression (MUNC), an eRNA originating from the distal regulatory region enhancer of MYOD, was observed to induce the transcription of specific myogenic genes  in trans. Overexpression of MUNC in MYOD−/− cells caused MYOG and MYH3 transcription and expression. Notably, these two genes are located on different chromosomes, validating MUNC's trans activity ] techniques, the authors found that Bloodlinc interacted with multiple protein complexes that function as RNA helicases , RNA transporters , RNA splicers , chromatin organization regulators , and Lamin A/C), and transcription coactivators or co-repressors . Moreover, immunoprecipitates of endogenous heterogeneous nuclear ribonucleoprotein U (HNRNPU), a nuclear matrix protein that stabilizes RNA-chromatin associations, were specifically enriched for Bloodlinc, which confirmed the interaction between Bloodlinc and HNRNPU  or transcriptional repressors . This process is stabilized by chromatin organization regulators that also interact with Bloodlinc.Intriguingly, some recent studies suggested seRNAs might also function interchromosomally  and mediator occupancy in an SE led to inhibition of tumor oncogenes, including MYC (TP53 (p53 tumor suppressor). Melo et al. found some of the TP53 binding regions encompass enhancer activity and produce eRNAs in a p53-dependent manner. Knockdown of these eRNAs significantly inhibited downstream target gene transcription upon TP53 activation, suggesting the eRNAs produced from TP53 bound enhancer regions that are required for efficient TP53 transcription enhancement and p53-dependent cell-cycle arrest (HPSE (heparanase) promoter , avoiding immune destruction  and sustaining proliferative signaling  . Consistding MYC . Recentle arrest . Moreovepromoter . The resImmune checkpoints, including stimulatory and inhibitory pathways, are regulatory signals that play vital roles in the maintenance of the delicate balance between activation of adaptive immunity and retaining self-tolerance from autoimmunopathy. Stimulatory checkpoint molecules encompass CD28 and the inducible T cell costimulator (both from the B7-CD28 superfamily) as well as CD27, CD40, OX40 (TNF receptor superfamily member 4), and CD137 (TNF receptor superfamily member 9), which are all from the tumor necrosis factor (TNF) receptor superfamily. Inhibitory checkpoint molecules include members of the B7-family , Lymphocyte Activation gene-3, and nicotinamide adenine dinucleotide phosphate. Through unique and non-redundant pathways, these molecules work as secondary signals to determine the activation or inhibition of immune cells upon antigen recognition, which modulates the duration and amplitude of physiological immune responses.+ effector cells (Teff) and promotion of Treg cell activity  in humans correlate with a variety of autoimmune diseases, including type 1 diabetes (T1D), rheumatoid arthritis (RA), multiple sclerosis, and systemic lupus erythematosus (SLE)  . Mice deus (SLE) . CTLA-4 olvement , while holvement . Jury etolvement . In addiolvement –56. The olvement . This leolvement –60.reg cells. When engaged to its receptor PD-L1, which is widely expressed on antigen-presenting cells, CD4+ T cells, and non-lymphoid tissues, PD-1 delivery an inhibitory signal via direct and indirect pathways. In the direct pathway, PD-L1-engaged PD1 potently counteracts CD28-co-stimulation and T cell receptor (TCR) signal transduction via terminating zeta chain of T cell receptor associated protein kinase 70 and phosphoinositide-3-kinase (PI3K) phosphorylation, leading to recruitment of protein tyrosine phosphatase non-receptor type 11 (PTPN11), which in turn inhibits IL2 production and reduces the transcription of pro-survival factor BCL-2-like protein 1  and its ligand PD-L1  inhibit adaptive immune resistance and reinvigorate the immune response against cancer cells. PD-1 mediates immune suppression via a variety of mechanisms in cancer. In T cells, PD-L1-bound PD-1 inhibits TCR signaling by recruiting PTPN11 to the immunoreceptor tyrosine-based switch motif domain, which results in dephosphorylation of downstream signaling molecules, decreased IL-2 production, reduction in cell cycle progression, and reduced expression of TFs involved in effector function (T-bet and eomesodermin) . An elevironment . In addiironment . The resphocytes . The prophocytes . PD-1 anphocytes .PD-L1 expression is especially high in tumor cells and tumor-associated APCs  . As a reMYC, IRF4 (interferon regulatory factor 4), XBP1 (X-box binding protein 1), CCND2 (Cyclin D2)] that are deregulated in multiple myeloma cells , CCND1 (Cyclin D1), and F2RL1 are associated with activating invasion and metastasis, evading growth suppressors, and avoiding immune destruction, respectively  gene expression in non-small cell lung cancer cell  in the human 8q24 region. This SE forms an enhancer-promoter loop with the MYC promoter, thus bringing CCAT1-L in to close proximity with the promoter. Such chromatin interactions are present specifically in colorectal, breast, and prostate cancer , and the MYC promoter showed the highest interaction frequency with this site, while the interaction between MYC-515 and MYC-355 ranked as second. Earlier Pomerantz et al. found an enhancer located at MYC-355, which forms a loop between the MYC promoters to promote its transcription  are enriched at the loops of the MYC promoter, and the MYC-335 and MYC-515 segments. Moreover, knockdown of CTCF is associated with decreased transcription of MYC and CCAT1-L, suggesting that the enhancer-promoter looping at MYC is CTCF-mediated. In addition, RNA immunoprecipitation showed a specific interaction between CTCF and CCAT1-L. Reduced CTCF occupation of the loop region at MYC was detected after depletion of CCAT1-L, indicating that CCAT1-L assists the binding of CTCF to chromatin and contributes to the looping formation at the MYC locus  and PI3K/AKT signaling pathways  signaling  and SRY-box 2 (SOX2) to regulate the expression of the epidermal growth factor receptor (EGFR) in esophageal squamous cell carcinoma (ESCC) . With idpathways . Consistpathways , 86. Furpathways . Many stmutation –89. Highmutation , 89. Forignaling . Notablypathways .MYCN overexpression and MYCN-driven transcription amplification in neuroblastoma  inhibitor, THZ1, selectively downregulates SE-regulated blastoma . Similarblastoma , 93.MYC , is a direct target of BRD4. In addition, the application of JQ1 increased CD8+ cytotoxic T cell activity; thus promoting anti-tumor immunity, limiting ovarian cancer progression, and improving mouse survival , forming a chromatin loop. The accumulation of BRD4 at the PDCD1L1 TSS decreased substantially upon JQ1 treatment, indicating that disruption of the TSS and SE loop might contribute to JQ1-mediated PD-L1 expression inhibition . As a transcription co-activator, BRD4 is often required for the expression of oncogenes, including MYC –96. The MYC , 98. StuMYC . RecentlMYC , 99. WheMYC . eRNAs hs in MYC . JQ1 disleukemia , 96. Zhuleukemia . In a mosurvival . The mecgnancies , 103. Thhibition . Therefo PDCD1L1 .+ memory/effector cells in the synovial fluid of patients with juvenile idiopathic arthritis -signal transducer and activator of transcription (STAT)-IRF1 axis that regulates PD-L1 expression (In vivo and in vitro experiments showed that T cell infiltration-dependent islet beta cell PD-L1 upregulation is mediated by IFNγ (The application of immune checkpoints in oncology sometimes triggers auto-inflammatory adverse effects, which has prompted further investigations of the contribution of immune checkpoints to autoimmunity. The expression and functions of inhibitory immune checkpoints are often dysregulated in autoimmune diseases. Promoting the inhibitory function of immune checkpoints should be beneficial to restore the immune balance in rheumatic disease. However, Farh et al. found that distinct enhancers and eRNAs are involved in autoimmune disease . Genome-rthritis . These Srthritis . A previrthritis . In T certhritis . ADAM ligulation . One of gulation . That st T cells . BACH2 r and T1D –116. Vaheceptors . In addieceptors . Therefoeceptors . Recent pression . Thus, tpression . Such fipression . T cell- by IFNγ . In addi by IFNγ . These fCurrent knowledge of immune checkpoints and SEs has increased our understanding of immune checkpoint expression in oncology and autoimmunity. Evading immune destruction is a major hallmark of cancer, suggesting that the expression of inhibitory immune checkpoints could be a critical identity character of tumor cells . Super eAs a potential therapeutic target, many researchers had focus on exploring the application of SE blockers in cancers and autoimmune diseases . He et aAlthough remarkable process has been made in revealing the regulation of immune checkpoint expression and eRNA function, many questions and challenges remain. For instance, the exact function and mechanism of seRNAs have not been clearly demonstrated. Additional and direct evidence of seRNA function in immune checkpoint expression is required to further support the indirect gene regulation effect by seRNAs. Recent findings also revealed that the exact boundaries between eRNAs and lncRNAs are not absolute, suggesting that some eRNAs might have been mistakenly identified as lncRNAs . DespiteAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


S. cerevisiae, Chd1 is not essential for viability. We show that deletion of the gene leads to a defect in sister chromatid cohesion and in chromosome morphology. Chl1 is a non-essential DNA helicase that has been shown to regulate cohesin loading. Surprisingly, co-deletion of CHD1 and CHL1 results in an additive cohesion defect but partial suppression of the chromosome structure phenotype. We found that the cohesin regulator Pds5 is overexpressed when Chd1 and Chl1 are deleted. However, Pds5 expression is reduced to wild type levels when both genes are deleted. Finally, we show a correlation in the expression of CHD1 and cohesin genes in prostate cancer patients. Furthermore, we show that overexpression of cohesin subunits is correlated with the aggressiveness of the tumor. The biological roles of the interplay between Chd1, Chl1 and SMCs are discussed.Chd1 is a chromatin remodeler that is involved in nucleosome positioning and transcription. Deletion of CHD1 is a frequent event in prostate cancer. The Structural Maintenance of Chromosome (SMC) complex cohesin mediates long-range chromatin interactions and is involved in maintaining genome stability. We provide new evidence that Chd1 is a regulator of cohesin. In the yeast  The protein is a component of the SAGA and SLIK multi-subunit histone acetyltransferase complexes, which preferentially acetylate histones H3 and H2B, and deubiquitinate histone H2B. Chd1 stimulates DNA unwrapping from the edge of the nucleosome, which is involved in DNA packaging into chromatin, and regulates transcription. Yeast cells lacking CHD1 harbor chromatin defects associated with irregular nucleosome positioning5. These cells were associated with disparate effects on growth and lifespan10. In humans, eight members of the CHD family are associated with a variety of cellular functions1. Human CHD1 has been identified as a prostate cancer (PCA) tumor suppressor. Loss of CHD1 promotes PCA aggressiveness and is associated with early recurrence of serum prostate specific antigen, a high Gleason grade, advanced tumor stage, and increased cell proliferation13. Another member of the CHD family, CHD8 has been associated with autism spectrum disorder17.The evolutionary conserved Chd1 gene encodes for an ATP-dependent chromatin-remodeling factor, which contains a chromodomain, a DNA binding domain and a DEAH helicase domain  protein complexes are central factors in the higher order organization of the chromatin24. Therefore, nucleosome eviction and translocation may be a prerequisite for cohesin loading. Indeed, the FANCJ-like DNA helicase Chl1/DDX11 has been found to be involved in efficient recruitment of the Scc2/Scc4 loader to the chromatin. It has been suggested that Chl1 affects cohesin loading by chromatin structure in the loading region29. After loading, cohesin is driven from its loading site by the transcription machinery32. However, the effects of barriers such as DNA secondary structures, histones and chromatin-bound proteins on cohesin translocation are not fully understood. Chromatin remodelers may be essential for removing such barriers and clear the way for cohesin translocation. Chd1 and Chl1 may be involved in these processes. Indeed, a genetic interaction between Chd1 and cohesin has been reported in several high-throughput screens36. A physical interaction between Chl1 and cohesin has been found during the S phase of the cell cycle37. However, the mechanism by which Chd1 affects cohesin has not been studied.Chromatin remodelers and helicases can affect cohesin function by several mechanisms. Cohesin loading requires the Scc2/Scc4 loader, whose function includes maintaining a nucleosome free region at the loading siteIn this study we identified Chd1 as a new regulator of cohesin in budding yeast and humans. Our findings shed new light on the complexity of cohesin-chromatin complexes and imply a novel mechanism by which a deletion of Chd1 in the prostate drives tumorigenesis through misregulation of cohesin.39. We therefore sought to explore the possibility that Chd1 disturbs the higher order chromatin structure through the activities of the SMC complex cohesin. For this purpose, we constructed a yeast strain in which the CHD1 gene is deleted.The interplay between nucleosomes and cohesin motivated us to look for remodelers that may affect SMC activities. Chd1 has been identified as an effector of chromosome stability and a genetic interactor of cohesin in large-scale surveys40.To examine the effect of CHD1 deletion on sister chromatid cohesion we used the GFP dot assay. In brief, an array of LacO was integrated into the LYS4 locus, about 40 kbp distal to the centromere of chromosome III. Wild-type (yIO-120) and chd1Δ (yAB-2010) cells expressing LacI-GFP were used to assess cohesion of cells arrested in G2/M by nocodazole. Normal cohesion is detected as a single GFP dot, while cohesion loss appears as two distinct fluorescent dots. Precocious sister chromatid separation was detected in ~20% of chd1Δ cells, indicating a mild cohesion defect in these cells Fig. . These l29. Therefore, we sought to compare the cohesion loss in chd1Δ cells to the effect of CHL1 deletion. For this purpose, we constructed strains yAB-2028 (chl1Δ) and yAB-2029 (chl1Δ chl1Δ), and used them to assess cohesion, as described above  in wild type, chd1Δ, chl1Δ and chd1Δchl1Δ cells. Strains yIO-230 (Scc3-HA), yAB-2045 (Scc3-HA chl1Δ), yAB-2046 (Scc3-HA chd1Δ) and yAB-2048 (Scc3-HA chd1Δchl1Δ) were grown to mid-log phase and arrested in G2/M by nocodazole; mitotic chromatin spreads were prepared, stained with anti-HA antibodies and the intensity of cohesin was measured and normalized Fig. . Cohesin43. In yeast, the rDNA is located in a single locus on chromosome 12. In mitotic cells, this region appears as a distinguished loop that emerges from the chromosome mass , yAB-2003 (chd1Δ), yAB-2018 (chl1Δ) and yAB-2019 (chd1Δ chl1Δ) were grown at 30 °C and arrested in G2/M by nocodazole. Cells were processed for chromosome spreads and stained with DAPI. We examined the morphology of the rDNA and classified them into three distinct groups: normal  loop, extended loop and abnormal loop Fig. . In wildCohesin mutants are sensitive to several DNA damaging reagents. Therefore, we explored the sensitivity of cells carrying a deletion of Chd1 or Chl1 to the genotoxic drugs hydroxyurea (HU), methyl methanesulfonate (MMS) and camptothecin (CPT). These drugs affect the DNA damage response by various mechanisms. HU leads to nucleotide depletion-dependent collapse of the replication fork. MMS induces DNA breaks that activate the S phase checkpoint, while CPT induces DNA breaks that activate the G2 phase checkpoint Fig. . All sin45. We used a sir2Δ strain as a positive control in which the intra-chromosomal recombination frequency is increased compared to the wild type , yAB-2014 (chd1Δ), yAB-2023 (chl1Δ) and yAB-2024 (chd1Δ chl1Δ), in cells at mid-log phase. The expression of Mcd1 was not significantly different between wild type and chd1Δ cells. However, Pds5 expression was increased in CHD1Δ and CHL1Δ cells. Interestingly, Pds5 levels were reduced back to the wild type level when both CHD1 and CHL1 were deleted . However, a significant effect on tumor aggressiveness, as indicated by a high Gleason score, was found in low cohesin expressing PCA samples . CHD1 deletion was most common in PCA. However, the frequencies were lower in 50% of the different cancer types. Similar to PCA, PDS5A deletion was detected in lower frequencies in 20% of cancer types. Similar to CHD1, PDS5B deletion was detected in 50% of the cancer types; the highest deletion frequencies were in PCA, sarcoma and diffuse large B-cell lymphoma. These results suggest that PDS5B is a newly identified driver of cancer with an important role in PCA.47 to predict alterations to the cellular networks. We considered the cohesin complex and the CHD1 deletion that is found in many cancers, and that is particularly frequent in PCA. According to this approach, pre-computed data from multiple PubMed references on tumor-suppressors and oncogenes are used to identify gene roles in cancer. Based on this analysis, we found that CHD1 and PDS5 are connected through TIMLESS (the human homolog of TOF1) and the DNA polymerase loader clamp PCNA. Furthermore, the analysis indicated that the CHD1 is an oncogene and that PDS5B is a tumor suppressor sor Fig. . AltogetWe identified the chromatin remodeler Chd1 as a new regulator of the SMC complex cohesin in yeast. We showed that deletion of CHD1 affects cohesin chromosome binding, similar to the effect of the known cohesin regulator Chl1. Furthermore, double deletion of CHD1 and either CHL1 or TOF1 affected precocious chromatid separation. These results suggest that in yeast, CHD1 affects cohesin through the CHL1-TOF1-CSM3-CTF4. The bioinformatics analysis indicates that this effect is conserved in humans. Deletion of CHD1 also affects the morphology of the rDNA locus. Surprisingly, co-deletion of CHL1 suppresses this phenotype. Chd1 and Chl1 activity affect nucleosome occupancy and positioning. Therefore, we suggest that local changes in nucleosomes can affect the higher order structure of chromatin by affecting cohesin function.2. Chd1 is involved in chromatin remodeling, nucleosome sliding, gene expression and transcriptional elongation. Deletion of the CHD1 encoding gene is associated with extended heterochromatin regions. A number of reports have claimed that Chd1 prevents exchange of histones in the coding region49. Chd1 can affect cohesin by several mechanisms. Chromatin remodeling may affect cohesin loading and translocation. Chl1 has been shown to interfere with Scc2/Scc4 loading, which requires nucleosome free DNA for efficiency29. We cannot rule out the possibility that Chd1 has a similar effect. Another mechanism may be associated with cohesin translocation from its loading sites32. Evidence suggests that DNA structures and chromatin bound proteins may block the free movement of cohesin. In such case, irregular nucleosome orientation may act as a barrier. The RSC chromatin remodeler complex has been identified as an important factor for cohesin translocation23. It is possible that the activity of Chd1, Chl1 and most likely other remodelers may similarly affect cohesin association with chromatin. In agreement with this hypothesis, components of the RSC complex interact genetically with Chd1, implying redundancy between remodelers.Chd1 is an essential component of the histone acetyltransferase complexes SAGA and SLIK, which preferentially acetylate histones H3 and H2B, and deubiquitinate histone H2B50. Overexpression of Pds5 may shift complex stoichiometry and enhance cohesin chromatin dissociation over association.In addition to the possible interplay between chromatin structure and cohesin activity, Chd1 is a transcription regulator. We noted that deletion of the gene leads to a 1.5 fold increase in levels of Pds5. A similar effect was observed in CHL1 deleted cells. It has been suggested that Pds5 competes with Scc2 on the same cohesin binding site51. We speculated that the extended rDNA structure may be associated with intra-recombination. We detected a mild increase in recombination frequency in chl1Δ cells. However, this change was not statistically significant and thus, this hypothesis was not confirmed. The opposing effect of CHD1 and CHL1 on rDNA morphology, as was found in the double mutant, suggests that these proteins may differently regulate cohesin in this region. Further, genetic studies are needed to determine the genetic factors that regulate the size of the rDNA loop and to understand the biological differences between compact and extended loop morphologies.A notable effect of CHD1 deletion is evident by the morphology of the rDNA. The size of the rDNA loop has been shown to be affected by temperature. We demonstrated that genetics can also contribute to the size of the loop. However, cohesin levels per se seem not to sufficiently explain rDNA morphology, as cohesin levels were similarly reduced in the strains in which CHD1, and both CHD1 and CHL1, were deleted. Nonetheless, a difference in the frequency of extended loop morphology was found between these strains. The biological significance of the loop size is yet to be determined. Loop size has been shown to be affected by temperature and may reflect the transcription level of the rDNA genes13. However, the molecular mechanism by which the deletion affects the tumor is not fully understood.One of the interesting findings of this study relates to the interplay between Chd1 and cohesin in PCA. Deletion of the CHD1 gene is a common event in PCA, which is one of the most frequent malignancies in men worldwide. PCA carrying a CHD1 deletion is associated with early recurrence of serum prostate specific antigen, a high Gleason grade, advanced tumor stage and increased cell proliferation52. The correlations of CHD1 expression with PDS5B and ESCO1, but not with ESCO2, support associations of clinical outcomes in CHD1Δ patients with non-mitotic functions of cohesin. The contribution of cohesin to PCA is in addition to its involvement in leukemia, bladder cancer and other malignancies56. Remarkably, we found that deletion of the cohesin regulator PDS5B is a common event in PCA, as well as in other types of cancer. This adds to the growing number of reports on the involvement of this gene in cancer60. The identification of cohesin as a factor in PCA progression is important for the development of biomarkers and personalized medicine approaches for treating this type of cancer.Our analysis on PCA samples supports the idea that at least some of these clinical properties are related to cohesin misregulation. We found positive correlations of CHD1 with several cohesin subunits and regulators. particularly, cohesin can affect tumor aggressiveness by inducing genome instability, and also through misregulation of oncogenes and tumor suppressorsThe yeast strains that were used in this study are listed in Supplementary Table 62. In brief, cells carrying LacI-GFP and LacO array, integrated at the LYS2 locus, about 40 kb from the centromere, were grown to mid-log phase and arrested at G2/M by 5 µM nocodazole. Cells were fixed by using 4% formaldehyde and washed once with KPO4/sorbitol solution (0.1 M KPO4 pH = 7.5 and 1.2 M sorbitol), resuspended in KPO4/sorbitol and stored at 4 °C. Samples were analyzed using AxioImager M2 microscope (Zeiss), magnification x100, N/A = 1.4.Sister chromatid cohesion was measured by using the GFP dot assay as previously reported43 and nuclei stained with DAPI. For immunostaining, slides were washed with PBS for 30 min and then blocked with 20% BSA for 10 min at room temperature. The slides were covered with mouse anti-HA antibody (Roche) and incubated in a humid chamber for 1 hr at 23 °C, washed with PBS for 10 min at room temperature, and re-incubated with a goat anti-mouse antibody conjugated to Alexa Fluor 680 (Life Technologies) for 1 hr at 23 °C. Slides were washed with a PBS for 10 min, dried and covered with 100 ng/ml prolong gold antifade reagent DAPI. Nuclei were observed by AxioImager M2 microscope (Zeiss), magnification x100, NA = 1.4.Yeast strains were grown in YPD to the mid-log phase and arrested in the G2/M phase of the cell cycle by nocodazole. Chromosome spreads were prepared as described in64. In brief, the ADE2 gene is inserted into the rDNA locus. Cells expressing ADE2 are white. Cells in which the ADE2 gene is lost as a result of intra-molecular recombination develop a red color. Cell cultures were grown to saturation and plated on YPD plates, incubated at 30 °C for 3–4 days, then transferred to 4 °C until the red color appeared. The frequency of intra-chromosomal recombination was measured as the ratio between white (ADE2) and red (ade2) cells.Intra-chromosomal recombination was described inProtein extracts from mid-log cells were prepared and analyzed by SDS-PAGE followed by Western blot. Polyclonal antibodies against Mcd1 and Pds5 were a generous gift from Vincent Guacci. Antibody against tubulin was purchased from Abcam. Densitometry was done with Image J software. Statistical significance was determined by t-test on the average of 3 independent experiments. Reprehensive full blots are shown in Supplementary Fig. 66. Fifty (10%) of the patients were retrieved with CHD1 deletion. Further, mRNA expression data for a total of 502 PCA patients of TCGA were downloaded from NCBI’s GEO DataSets (GSE62944). The gene expression of cohesin and condensin subunits for all 502 patients were compared to the that of patients with CHD1 deletion by using in-house R script; the Pearson correlation coefficient was calculated. Pearson’s correlation coefficient in the range of 0.1–0.3 was considered as weak, 0.3–0.5 as moderate and 0.5–1.0 as a strong correlation. Moreover, based on the gene expression values, Kaplan-Meier survival plots were generated for PCA patients using the UALCAN server67.Putative CHD1 copy-number alterations from GISTIC for prostate adenocarcinoma of the Cancer Genome Atlas  were calculated using cBioPortal for cancer genomics47. In brief, ChiPPI utilizes a pre-computed domain-domain co-occurrence table based on all human interactions from BioGrid68 and evaluates all the missing and gained interactors of the deleted genes in cellular PPI networks.To calculate protein-protein interactions (PPIs) and their alterations due to gene deletions in cancers, we used our previously developed method, ChiPPISupplementary Information


Trophectoderm (TE) lineage development is pivotal for proper implantation, placentation, and healthy pregnancy. However, only a few TE-specific transcription factors (TFs) have been systematically characterized, hindering our understanding of the process. To elucidate regulatory mechanisms underlying TE development, here we map super-enhancers (SEs) in trophoblast stem cells (TSCs) as a model. We find both prominent TE-specific master TFs , and >150 TFs that had not been previously implicated in TE lineage, that are SE-associated. Mapping targets of 27 SE-predicted TFs reveals a highly intertwined transcriptional regulatory circuitry. Intriguingly, SE-predicted TFs show 4 distinct expression patterns with dynamic alterations of their targets during TSC differentiation. Furthermore, depletion of a subset of TFs results in dysregulation of the markers for specialized cell types in placenta, suggesting a role during TE differentiation. Collectively, we characterize an expanded TE-specific regulatory network, providing a framework for understanding TE lineage development and placentation. Trophectoderm lineage development is essential for implantation, placentation, and healthy pregnancy. Here the authors map super-enhancers (SEs) in trophoblast stem cells and find both TE-specific master regulators and 150 previous uncharacterised transcription factors that are SE-associated, providing insight into trophectoderm-specific regulatory networks. The origin of the placenta is the trophectoderm (TE), an outer layer of the blastocyst stage of embryo. Placental tissues comprises multiple specialized cell types such as trophoblast giant cells (TGCs), spongiotrophoblasts (SpTs), and syncytiotrophoblasts (SynTs)1. Abnormal TE lineage differentiation is a major cause of pregnancy complications3.The placenta is a temporary yet crucial organ that facilitates nutrient uptake, waste elimination, and gas exchange through the mother’s blood supply to maintain a healthy pregnancy4 and intensively researched due to their pluripotency, trophoblast stem cells (TSCs) established from an outgrowth of either polar TE or extra-embryonic ectoderm5 have not been studied nearly as much, despite the importance of the placenta. This paucity of research has led to only a rudimentary understanding of the mechanisms underlying TE lineage specification, maintenance, and differentiation. During the past decade, rodent TSC models have been utilized to study placenta development6. Whether human TSCs recently established truly constitute a tractable model for placental development awaits further confirmation7.In contrast to embryonic stem cells (ESCs), derived from the inner cell masscis-regulatory elements, mainly enhancers, orchestrate lineage-specific gene expression programs to determine cellular identity and functions8. In TE lineage, only a few TFs have been identified as key regulators, such as Tead4, Cdx2, Gata3, Tfap2c, Eomes, Ets2, and Elf515. The precise transcriptional regulatory mechanisms of TE/TSC-specific TFs remain elusive. There has been no thorough investigation in how an expanded set of TFs, including previously uncharacterized factors, controls self-renewal of TSCs, modulates differentiation toward more specialized cell types, or interacts with their respective chromosomal targets via forming regulatory networks with their partner proteins, including epigenetic regulators.Cell-type-specific transcription factors (TFs) and their target 17. They can be predicted by strong occupancy signals of mediators, p300 (Ep300), or enhancer-specific histone modification marks, such as H3K27ac and H3K4me1. In ESCs, SEs are associated with master pluripotency TFs, such as Oct4 (Pou5f1), Sox2, and Nanog. In parallel, multiple master TFs co-occupy common SEs, further amplifying the levels of SE-associated target genes including master TFs themselves by forming highly intertwined regulatory circuitry. While previous studies attempted to identify global enhancer usage in TSCs or placenta21, there have been no systematic approaches to predict master regulators by defining enhancers or SEs.The concept of “super-enhancers” (SEs), consisting of a cluster of enhancers, has been recently proposedIn this study, we identify TSC-specific SEs and subsequently predict putative key TFs. SE-associated genes we defined in TSCs are implicated in placental development, and many of these encode for TFs, including almost all known TE/TSC-specific TFs as well as numerous TFs that have never been previously implicated in placental biology. By mapping global target loci of over two dozen known and newly identified SE-predicted TFs, we reveal that they not only co-occupy various target genes, most of which are highly active in TSCs and the placenta, but also form an intricate regulatory network. Accordingly, some TFs show dynamic switches in their enhancer-binding patterns upon differentiation. Interestingly, the SE-associated TFs show four distinct expression patterns during TSC differentiation and these different classes of TFs demonstrate discrete roles during TE lineage differentiation. Our findings will serve as a valuable resource for research in placental development and disorders.To identify enhancers utilized in TSCs, we first mapped the genomic occupancy of p300 using chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq). As a control, ChIP-seq in ESCs was performed in parallel. We identified total 39,957 and 36,190 enhancers in TSCs and ESCs, respectively  and plotted the average number of enhancers associated with each gene Fig. . We obse24, more recent studies showed that SEs are often associated with cell-type-specific master regulators25. We identified a total of 1,186 TSC-specific SEs with the criteria previously described16, then subsequently defined 1,046 SE-associated genes  involved in proliferation of TSCs or TSC-like progenitorsSCs Fig. , they shSCs Fig. , consistSCs Fig.  and theycis-regulatory elements  by ChIP-seq Fig.  and iden2, we reasoned that dysregulation of some SE-associated genes may be associated with human PE. In fact, we confirmed that previously known PE biomarkers, such as FLT, ENG, and BHLHE4043, are TSC-specific SEs-associated factors 33 -mediated knockdown (KD) of 17 TFs  followed by differentiation of TSCs for 3 days. Upon confirming at least 80% KD of most of the factors  generally enhances the levels of TGC/SpT marker genes during TSC differentiation, whereas KD of Maff, Mafk, or other Class 3 TFs dramatically suppresses the activation of multiple TGC/SpT markers during differentiation Fig. . This su49 while deletion of Hand1 prohibits TGC differentiation50. First, we intersected targets of differentially expressed genes (DEGs) with our ChIP-seq data and performed GO analysis to understand how and to what extent direct targets of a TSC-specific TF influence differentiation of TSCs. Consistent with our quantitative PCR (qPCR) results , as well as Maff, Mafk, Ets2, and Foxj2 (Class 3) upon differentiation. Hopx and Hand1 served as controls, as Hopx depletion leads to substantial propagation of TGC layers with reduction of SpT formation in placentalts Fig. , depletilts Fig. , b. Thes51. The result consistently supports that Maff, Mafk, Foxj2, or Ets2 KD shows impaired induction of the genes representing invasive SpTs and spiral artery TGCs. On the other hand, Meis1, Pou3f1, Id2, Pcgf5, Hopx, or Zfpm1 KD cells presented opposing patterns . Intriguingly and similar to the results shown in Fig. Finally, we performed immunohistochemistry (IHC) to see whether the functions of TSC-specific TFs proposed by in vitro experiments are correlated with in vivo expression patterns in placenta. We confirmed the area of TGC and SpT in placenta by IHC with proliferin and Tpbpa, respectively  of a few SE-associated TFs such as Ets2, Eomes, Esrrb, Dlx3, and Hand135, whereas Class 3 TFs including Gcm1, Prdm1, Fosl2, Cited2, and Dlx3 seem to orchestrate differentiation toward more specialized placental cell types58. Accordingly, the TFs in the Class 3 show dramatic changes in their target gene occupancy upon differentiation, shifting their preference toward marker genes for TGCs and SpTs. Our analysis demonstrates class-specific roles of multiple factors during differentiation, highlighting the complexity of the TE-specific gene expression regulation  were gifted from Dr. Janet Rossant laboratory. TSCs were maintained in TSC culture media (mixture of mouse embryonic fibroblast (MEF)-conditioned TS medium with TS basal medium at a ratio of 7:3) supplemented with 25 ng/ml Fgf4 and 1 μg/ml of heparin. The TS basal medium is composed of RPMI  1640 medium supplemented with 20% FBS, 100 μM β-mercaptoethanol, 2 mM L-glutamine, 1 mM sodium pyruvate, 50 U/ml penicillin/streptomycin. MEF-conditioned medium was composed of TS medium conditioned by MEF cells. Mitomycin-treated MEF cells were cultivated in TS basal medium for 3 days, and then the medium was collected. 293T cells were cultured in DMEM supplemented with 10% FBS and 50 U/ml of penicillin/streptomycin with 2 mM L-glutamine (Life Technologies). All cells were incubated at 37 °C and 5% CO2. To initiate the differentiation of TSCs, TSCs were washed three times with TS basal medium to remove residual Fgf4 and heparin and then grown in TS basal medium.Mouse J1 ES cells (ESCs) were cultivated in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 18% fetal bovine serum (FBS), 2 mM L-glutamine, 100 mM nonessential amino acid, nucleoside mix (Fisher Scientific), 100 μM β-mercaptoethanol (Sigma-Aldrich), 1000 U/ml recombinant mouse LIF (Gemini Bio-Products), and 50 U/ml penicillin/streptomycin (Fisher Scientific). Mouse TSCs derived from blastocyst (TS2O2 in PBS for 10 min at RT and incubated in blocking solution (10% horse serum in PBS) for 30 min at RT. Primary antibody solution prepared in 10% horse serum in PBS with dilution ratio of 1 to 500 was treated in the tissue section slides for 30 min at RT followed by rinsing with PBS for 5 min. The tissue section slides were incubated with biotinylated anti-rabbit or anti-goat IgG antibodies for 30 min at RT. After washing the slides with PBS for 5 min, they were incubated with a VECTASTAIN® Elite® ABC HRP Kit  for 30 min at RT. The tissue section slides were rinsed in PBS for 5 min and developed using the DAB Peroxidase (HRP) Substrate Kit  for 50 s–2 min until the antigen was visibly detected. All sections were counterstained with Harris modified hematoxylin for 3 s. After washing the sections in flowing tap water, they were dehydrated in a graded ethanol series, immersed in xylene, and mounted with VectaMount® Permanent Mounting Medium . The slides were examined and photographed using a Nikon Eclipse Ni Compound Light Microscope (Nikon) equipped with a Nikon DS-Ri2 color camera.For IHC, paraffin tissue sections  of commercial C57 mouse placenta taken at E15 were deparaffinized in xylene (2 times for 5 min). Deparaffinized tissue sections were rehydrated by soaking them in a series of ethanol solution with decreasing concentrations  and distilled water. Antigens were retrieved from the tissue section slides in pre-heated citrate-EDTA buffer solution . After heating the slides in water bath for 30 min at 99 °C, the slides were cooled down for 20 min at room temperature (RT) and washed in phosphate-buffered saline (PBS). Before primary antibody treatment, the slides were treated with 0.3% H6 293T cells. After 12 h, the medium was replaced with the TSC culture medium and then incubated at 37 °C for 36 h. Viral supernatant was collected, filtered with a syringe filter (0.45 µm), and used to infect TSCs. To knock down each factor, 1 × 105 TSCs in each well of a 12-well plate were infected with viral particles. Infected cells were cultured for 24 h, and the medium was replaced by fresh TSC culture medium with puromycin (1 μg/ml) for the selection of infected cells. For gene expression analysis, cells were harvested after 3 days of infection. For differentiation of TSCs upon KD of each factor, the culture medium was replaced with TS basal medium without Fgf4 and heparin after 3 days of infection.shRNA clones targeting each of TFs were purchased from Sigma-Aldrich (Supplementary Data http://bioinfo.ut.ee/primer3/). All primer sequences are listed in Supplementary Data −ΔΔCT method. Relative expression of tested genes was calculated from at least duplicate reactions.Total RNAs were extracted from cultivated cells using the RNeasy Plus Mini Kit . cDNAs were synthesized from 500 ng of total RNAs using qScript cDNA supermix . To measure gene expression, reverse transcriptase–qPCRs were performed with 1 µl of 20× diluted cDNA for each reaction using PerfeCTa SYBR Green FastMix  and 250 nM of each primer. PCR primer sets for investigating gene expression were designed to amplify the junction between two exons using a web-based primer design program, Primer3  showed either their own canonical motif or motifs highly similar in sequence to the canonical motif as enriched in the center area of the peaks .Global gene expression profiles using RNA-seq were performed in both ESCs and TSCs. Total RNAs were isolated using the RNeasy Plus Mini Kit. One μg of total RNA was used to generate RNA-seq library using the NEBNext Ultra RNA Library Prep Kit  according to the manufacturer’s instruction. Briefly, mRNAs were isolated from total RNAs with the Magnetic mRNA Isolation Kit, fragmented, and primed. First-strand cDNAs were synthesized following by second-strand synthesis. The ends of purified double-strand cDNAs were repaired, ligated with a barcoded adaptor, and amplified with PCR. Purified final PCR product was sequenced using Illumina NextSeq 500 machine. The reads were aligned to the mouse transcriptome (mm9) using salmon (v0.13.0)45. Cells were cross-linked with 1% formaldehyde for 7 min at RT, and then formaldehyde was quenched by adding glycine  for 5 min. After washing cells with PBS two times, fixed cell pellets were resuspended in ChIP dilution buffer and sonicated using a Bioruptor (Diagenode) with a setting of 30 s on and 1 min off for 10 min (3 times). Sheared chromatins containing DNA fragments with an average size of 300 bp were used for IP using 10 μg of a native antibody against each factor. Enriched ChIP samples were used for the generation of sequencing libraries using an NEB ChIP-seq library Preparation Kit  following the manufacturer’s instruction. ChIP-seq libraries were sequenced using Illumina NextSeq 500 machine.ChIP reactions were performed as previously62. Briefly, approximately 50,000 cells were incubated with transposition reaction mix for 30 min followed by 18 cycles of PCR. Approximately 250 bp of ATAC samples were isolated using the E-gel Size Select Kit. The final product was sequenced using Illumina NextSeq 500 machine.ATAC assays were conducted as previously described63 and filtered out non-uniquely mapped reads. We combined the mapped reads from the biological replicates for each unique factor and then performed peak calling using the model-based analysis for ChIP-seq (MACS2) peak caller (v2.1.1) with default parameters64. Further score filtering was applied to remove weak peaks by visual inspection. In addition, mouse genome mm9 repeat-mask file was downloaded from UCSC table browser (https://genome.ucsc.edu/cgi-bin/hgTables). Peaks found in simple redundant regions of the genome were further filtered out.For most of the generated data, at least two independent ChIP-seq and ATAC-seq were performed to identify the binding sites of TFs and open loci of chromatin, respectively. In all, 50 or 75 bp reads from ChIP-seq or ATAC-seq were mapped onto the mouse genome assembly (mm9) using bowtie2To investigate the effects of the number of enhancers on gene expression, enhancers (p300-binding sites) were mapped to the region surrounding 20 Kb upstream of the TSS as well as the gene body of all RefSeq genes from the RefFlat file and assigned to the gene. Moving average with a window size of 100 was used to average the number of enhancers that are associated with a gene.http://younglab.wi.mit.edu/super_enhancer_code.html). We first defined the binding sites of p300 using MACS peak caller, and then the defined peaks were transformed into gff files to meet the criteria of input files of the ROSE program. We run the ROSE with stitching distance option of 12.5 Kb and TSS exclusion zone size option of 2.5 Kb.SEs were defined using the ROSE program downloaded from the website of the Young laboratory (https://www.ncbi.nlm.nih.gov/geo/). Top 10% and bottom 10% of genes were determined by comparing gene expression between PE and normal samples. If human orthologs of mouse SE-associated genes are detected at least three times among these gene sets, the orthologs were finally selected and provided in Supplementary Data To investigate whether SE-associated genes are abnormally expressed in PE, we downloaded five different PE expression data sets from GEO  (http://meme-suite.org/index.html) was utilized to identify enriched motifs.To analyze the enriched motifs in the peaks from ChIP-seq data, we extracted sequences covering 200 bp centered on each peak. Web-based motif analysis program MEME-ChIP 66 for a set of genes.Enriched GO terms were investigated using GREAT (v3.0.0)A region of ±3 Kb from the center of peaks was binned (100 bp), and all reads from ChIP-seq were mapped into each bin. Each bin score was calculated by summing up the number of reads assigned into each bin and then normalized with the total sequencing depth. Average bin scores were plotted to generate averaged read density around peaks.To identify distribution of the binding sites of each TF across the genome, TF-binding sites were mapped to the region surrounding 20 Kb upstream and 2 Kb downstream of the TSS of all RefSeq genes from the RefFat file downloaded from UCSC genome browser. To assign one binding site to one genomic feature, we used the following hierarchy: promoter > upstream > intron >exon > intergenic regions. A promoter was defined as a region within ±2 Kb from the TSS, and an upstream element was defined as a region between 2 and 20 Kb upstream from the TSS. Binding sites without being mapped to promoter, upstream, intron, or exon were considered as intergenic target loci.67 and Java Treeview68, respectively.Overlapping binding sites among ChIP-seq data were identified using a moving window across the mouse genome. If the centers of peaks from different ChIP-seq data were discovered within a 500-bp window, we considered them as overlapping peaks. To generate correlation map of the binding sites among different TFs, peak calling followed by an overlap analysis identified the common binding sites of TFs. Score 0 and 1 were assigned to unique and overlapped binding sites of two TFs, respectively. A paired-wise Pearson correlation coefficient between the binding sites of two TFs was calculated for each pair of TFs. Clustering analysis and visualization of the data were done by Cluster 3.0http:// www.cytoscape.org).To assign a binding site to a gene, TF-binding sites were mapped to the region surrounding 20 Kb upstream and downstream of the TSS as well as the gene body of all RefSeq genes from the RefFlat file. If a binding site was not found within ±20 Kb including the gene body, the nearest gene was assigned as the target of the binding site. TF and target pairs were visualized using Cytoscape (All sequencing data generated or utilized in this study are listed in Supplementary Data Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Source Data