Ureagenesis predominantly occurs in the liver and functions to remove ammonia, and the dysregulation of ureagenesis leads to the development of hyperammonemia. Recent studies have shown that ureagenesis is under the control of nutrient signals, but the mechanism remains elusive. Therefore, intensive investigation of the molecular mechanism underlying ureagenesis will shed some light on the pathology of metabolic diseases related to ammonia imbalance.Mice were fasted for 24 h or fed a high-fat diet (HFD) for 16 weeks. For human evaluation, we obtained a public data set including 41 obese patients with and without hepatic steatosis. We analyzed the expression levels of hepatic BAF60a under different nutrient status. The impact of BAF60a on ureagenesis and hyperammonemia was assessed by using gain- and loss-of-function strategies. The molecular chaperons mediating the effects of BAF60a on ureagenesis were validated by molecular biological strategies.Cps1, a rate-limiting enzyme, through interaction with Y-box protein 1 (YB-1) and by switching the chromatin structure of Cps1 promoter into an inhibitory state. More importantly, in response to different nutrient status, PGC-1α  and YB-1 competitively bound to BAF60a, thus selectively regulating hepatic fatty acid β-oxidation and ureagenesis.BAF60a was induced in the liver of both fasted and HFD-fed mice and was positively correlated with body mass index in obese patients. Liver-specific overexpression of BAF60a inhibited hepatic ureagenesis, leading to the increase of serum ammonia levels. Mechanistically, BAF60a repressed the transcription of The BAF60a-YB-1 axis represses hepatic ureagenesis, thereby contributing to hyperammonemia under overnutrient status. Therefore, hepatic BAF60a may be a novel therapeutic target for the treatment of overnutrient-induced urea cycle disorders and their associated diseases.  •HFD-feeding increases hepatic BAF60a expression, while inhibits ureagenesis genes.•Cps1 transcription and ureagenesis, causing ammonia accumulation.BAF60a represses •YB-1 binds to BAF60a and mediates the inhibitory effects of BAF60a on ureagenesis.•BAF60a mediates crosstalk between hepatic ureagenesis and fatty acid oxidation. During cis-regulatory elements are present on the promoter of Cps1. For example, a C/EBPα binding motif is located on the proximal promoter of Cps1, which serves as the platform for the competitive binding of Y-box protein 1 (YB-1) and C/EBPα [Cps1 expression also undergoes epigenetic regulation. For example, Francesco et al. identified that two CpG islands exist on the Cps1 promoter, and they are hypermethylated in patients with nonalcoholic steatohepatitis, causing a reduction in Cps1 transcription [Ureagenesis is controlled by five enzymatic reactions that occur sequentially in the mitochondrial matrix and cytoplasm of hepatocytes. These enzymes are carbamoyl phosphate synthetase 1 (CPS1), ornithine transcarbamylase (OTC), argininosuccinate synthetase (ASS), argininosuccinate lyase (ASL), and arginase (ARG) ,8. Clinid C/EBPα . In addicription . In contcription ,14. AlthG6Pase and Bmal1) and turns the local chromatin structures into active states [It has not escaped our notice that various nuclear factors functionally coordinate molecular regulations of metabolic processes in response to nutrient signals. One of the best examples comes from the studies focusing on BAF60a, a subunit of the SWItch/Sucrose NonFermentable (SWI/SNF) complexes . In conte states . These fCps1 (the gene encoding a rate-limiting enzyme in the ureagenesis) promoter into an inhibitory state and represses its transcription. In addition, the peroxisome proliferator-activated receptor-γ coactivator-1α  and YB-1 competitively bind to BAF60a, thus selectively regulating hepatic FAO and ureagenesis in response to different nutrient states. Our findings strongly suggest that therapeutic intervention targeting BAF60a in the liver may be a promising strategy to treat hyperammonemia and HSC activation-induced fibrosis in patients with nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.In the present study, we aimed to explore whether BAF60a regulates hepatic ureagenesis and ammonia-induced HSC activation. To answer this question, we used gain- and loss-of-function strategies to manipulate the hepatic BAF60a expression both in vivo and in vitro. Our results demonstrated that BAF60a, as a sensor for malnutritional signals, switches the chromatin structure of 22.1NM_031842) or green fluorescent protein (GFP) into mice at a dose of 1 × 1012vg through tail-vein injection under the hepatocyte-specific thyroid binding globulin (TBG) promoter. The dose of AAV was chosen based on a previous study showing that this dose functionally manipulates the gene expression in mouse hepatocytes [All animal procedures in this investigation conform to the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health  and the approved regulations set by the Laboratory Animal Care Committee at China Pharmaceutical University (permit number SYXK-2016-0011). Male C57BL/6 J mice were maintained in a 12-h light–dark cycle and in a temperature- and humidity-controlled environment. For fasting experiments, mice were either fed ad libitum or subjected to 24-h fasting. For HFD-feeding experiments, 10-week-old male C57BL/6 J mice were fed on an HFD  for 16 weeks. For liver-specific overexpression of BAF60a, we transduced a single-stranded adenoviral-associated virus 8 (AAV8) system carrying either BAF60a CDS  were constructed by Bioworld Company . For YB-1 knockdown, three sets of stealth siRNA were designed, validated, and synthesized by GenePharma . To improve gene silencing efficiency, a siRNA cocktail comprising these three sets of siRNA oligonucleotides  was used. The sequences of these siRNA oligonucleotides are listed in Adenoviruses, including Ad-GFP and Ad-BAF60a, Ad-PGC-1α, Ad-Scra shRNA, and Ad-BAF60a shRNA, and plasmids encoding the Baf60a CDS domain were kindly provided by Prof. Jiandie Lin  . The pla2.42 at 37 °C [Primary hepatocytes (PHs) were isolated from mice using the collagenase IV  perfusion method as described previously and cultured in a humidified atmosphere containing 5% COat 37 °C . The mou2.5Total RNA was isolated using Trizol reagent , reverse transcribed, and analyzed by qPCR using SYBR Green  and the LightCycler® 480 System . The primers for mouse 36B4 were included for normalization. A complete list of PCR primers is shown in 2.6To assess the hepatic capacity for urea production in vivo, we conducted an alanine tolerance test as performed previously. Mice were fasted for 16 h and then injected intraperitoneally with 1 mg/kg alanine solution  . Blood s2.7Blood samples were collected in nonheparinized tubes and centrifuged at 4000 rpm for 10 min at 4 °C. Serum levels of urea and ammonia were determined spectrophotometrically by using commercial kits purchased from BioVision .2.8Livers were isolated, fixed in 4% paraformaldehyde solution for 24 h in situ, processed for paraffin embedding, and cut into 4-μm transverse sections for Sirius red staining. The sections were photographed with a Nikon fluorescence microscope . For the collagen I content, a 1% liver homogenate was used for determination of liver collagen I content using an enzyme-linked immunosorbent assay (ELISA) kit from Cloud-clone Corp .2.9To mimic the hepatic microenvironment in vitro, we performed the co-culture experiments. Cells were cultured using cell culture inserts (50 μm pore size) to separate both cell populations. JS-1 cells were seeded on the bottom of the plate, while the PHs were plated on the insert. A ratio of PHs/JS-1 of 5:1 was chosen according to a previous study . After 42.10JS-1 cells were fixed in ice-cold 4% paraformaldehyde for 30 min, followed by blocking in 5% goat serum for 1 h, and incubation with rabbit polyclonal anti–α-SMA antibody overnight at 4 °C. After repeated washing, the cells were probed with secondary antibodies conjugated to Alexa Fluor 488 anti-rabbit immunoglobulin G  for 1 h at room temperature. Nuclei were identified with DAPI. The sections were photographed with a Nikon fluorescence microscope .2.11Cps1 promoter was mutated and synthesized by Bioworld . All transient transfections were conducted using Lipofectamine 3000  according to the manufacturer's instructions. For the luciferase reporter assays, 200 ng of reporter plasmids was mixed with 50 ng of expression constructs for YB-1 in the presence or absence of 500 ng BAF60a expression construct. Equal amounts of DNA were used for all transfection combinations by adding the appropriate vector DNA. Relative luciferase activities were determined 48 h following transfection using the Luciferase System . The data were representative of at least six independent experiments.The YB-1 binding site on the 2.12Liver tissues were homogenized, and the cells were lysed in the IP lysis buffer. After centrifugation, 40 μg of protein lysate was incubated with 20 μL of protein-A/G agarose beads  and 1 μg of anti-BAF60a or anti–YB-1 antibody. After overnight incubation, the immune complexes were centrifuged and washed four times with ice-cold IP wash buffer. The immunoprecipitated protein was further analyzed using Western blotting assay.2.13Cps1 promoter, as detailed in Acaa1b promoter was synthesized according to our previous studies.ChIP assays were performed in mouse PHs essentially as described previously. Briefly, chromatin lysates were prepared, precleared with protein-A/G agarose beads, and immunoprecipitated with antibodies against BAF60a, YB-1, PGC-1α, and K4-trimethylated histone H3 , K9-dimethylated histone H3 , or normal mouse IgG  in the presence of bovine serum albumin (BSA) and salmon sperm DNA. The beads were extensively washed before reverse cross-linking. The DNA was purified using a PCR purification kit  and subsequently analyzed by PCR using primers flanking the proximal binding sites for YB-1 on the mouse 2.14oxygen consumption rate was analyzed using a Seahorse XF24 Extracellular Flux Analyzer . In brief, 2 × 105 PHs were seeded into each well of a Seahorse XF24 cell culture microplate. On the next day, the cells were transfected with either vector or YB-1 plasmid for 48 h; 1 μM dexamethasone and 10 μM forsklin were added when necessary. Prior to the assay, the medium was changed to DMEM containing 25 mM glucose, 1 mM pyruvate, and 4 mM glutamine, and the cells were equilibrated for 1 h at 37 °C. During measurement, oligomycin , carbonyl cyanide-p-trifluoromethoxy phenylhydrazone , rotenone, and antimycin  were sequentially injected into each well at the indicated time points. Data were derived from Seahorse XF24 Wave software and displayed in pmol/min.The 2.15post hoc test were performed to analyze the data. A P value < 0.05 was considered statistically significant.Statistical analysis was performed using the Origin 8 software . Groups of data were presented as the mean ± SD (standard deviation). One-way analysis of variance followed by Fisher's least significant difference 33.1Baf60b and Baf60c, two more BAF60 family members, remained unchanged in all the examined settings  in the liver of obese patients  and found that the expression of patients D,E.Taking these data together, we conclude that BAF60a may serve as a specific component of the BAF60 family linking the nutrient signals to hepatic ureagenesis.3.2α-Sma, Tgf-β, and collagen synthesis-associated gene Col1a1, which are three markers for HSC activation  existed on its proximal promoter (−95 to −91 bp). Reporter gene assays demonstrated that BAF60a augmented the inhibitory effects of YB-1 on Cps1 transcription. However, this synergistic inhibition was partially abolished when the Y-box was mutated  under fasting status, whereas its function is abolished in the liver of HFD-fed mice [Cps1 promoter. As a result, urea production was increased while the ammonia secretion was decreased in the cell supernatant  and overnutrient (HFD-feeding) conditions, ureagenesis is oppositely regulated in these settings. Thus, we ask how BAF60a regulates this pathway in different ways in response to specific nutrient signals. It has been reported that PGC-1α, a well-known transcriptional coactivator, recruits BAF60a to PPARα-binding sites and activates the transcription of peroxisomal and mitochondrial FAO genes  and CPS1 protein (deacetylation) [Cps1 expression at the transcriptional level, thus forming a rapid responsive regulation  and the decreased contents of H3K4-me3 (activation) around its YB-1 binding site  ,13,14. Igulation . Such a ing site . Notablyle cells ,29. All Cps1 transcription. We found that YB-1 was a bona fide chaperon for BAF60a to synergistically inhibit CPS1 expression and ureagenesis. YB-1 is a transcriptional factor recognizing the cis-regulatory element, defined as Y-box (a reverse CCAAT box or ATTGG) [Cps1 promoter in both the fetal and CCl4-injured adult mouse liver and inhibits the C/EBPα-induced transcription of Cps1 promoter via the Y-box [Cps1 transcription and altered the chromatin structure of the Cps1 promoter. Our findings extend the current understanding of the pathophysiological function of YB-1 in the liver system. In addition, we noticed that YB-1 was quite stable in normal adult liver under physiological conditions  but was activated in the steatotic liver under pathological conditions . These results indicated that compared with YB-1, BAF60a serves as a major effector responsive for physiological nutrient changes, and the BAF60a/YB-1 complex synergistically functions to produce the inhibitory effects on the metabolic processes, such as ureagenesis. Nevertheless, YB-1 participates in a wide variety of DNA/RNA-dependent events, including DNA reparation, pre-mRNA transcription and splicing, mRNA packaging, and regulation of mRNA stability and translation [The BAF60 family members are recruited to specific chromatin loci through physical interactions with various transcriptional factors . Therefor ATTGG) . As Y-bor ATTGG) ,36. In cr ATTGG) . More imhe Y-box . Similarnslation . TherefoAcaa1b) under fasting status. Only when its expression and function are abolished in the liver of HFD-fed mice can YB-1 play a dominant role and recruit BAF60a to the Y-box region of Cps1 promoter. Our findings established an important crosstalk between the FAO and urea cycle, and BAF60a functions as an integration node for these pathways. Our data demonstrated that the relative abundance of PGC-1α and YB-1 under different nutrient states determines the functions of BAF60a in activating FAO or inhibiting ureagenesis. Under a fasting condition, the BAF60a-PGC-1α complex elevates FAO to maintain the energy supply. In this case, AA degradation is also accelerated so that excessive ammonia is produced and needs to be cleared out promptly. To meet this demand, the formation of BAF60a-PGC-1α complex essentially retards the interaction of BAF60a-YB-1 complex, thus releasing the inhibitory function of BAF60a on CPS1 and activating ureagenesis. In contrast, under the energy-redundant condition , PGC-1α expression is reduced, while hepatic YB-1 and BAF60a expression levels are upregulated. Increased YB-1 competitively binds with BAF60a and decreases the interaction of the BAF60a-PGC-1α complex, thus triggering the inhibition of ureagenesis and FAO. Collectively, under different nutrient statuses, the net output of reciprocal competition between BAF60a-PGC-1α and BAF60a-YB-1 complexes finally determines the on-off switches of ureagenesis and FAO processes.Although hepatic BAF60a expression is induced in both nutrient-deficient (fasting) and overnutrient (HFD-feeding) conditions, ureagenesis is oppositely regulated in these settings. It is important to investigate how BAF60a differently regulates this pathway in response to specific nutrient signals. In our study, we found that PGC-1α competed with YB-1 to recruit BAF60a to PPARα-binding sites and activated the transcription of peroxisomal and mitochondrial FAO genes (e.g., In conclusion, we elucidated here a BAF60a-orchestrated upstream regulatory mechanism in the urea cycle and provided a convincing explanation for the mechanism through which steatotic hepatocytes produced ammonia via induction of the formation of the BAF60a-YB-1 complex. The attendant crosstalk between ureagenesis and FAO processes protects against excessive accumulation in hepatic ammonia, which otherwise leads to HSC activation in response to overnutrient signals. Therefore, therapeutic intervention targeting BAF60a in the liver may be a promising strategy to treat hyperammonemia and HSC activation-induced fibrosis in patients with nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.WXZ, CL, and SYC conceived and designed the research. WXZ and ZWD performed most of the experiments. MYX isolated the PHs from mice. SYZ assisted with all the adenoviral-associated virus constructs. WXZ, MYX, and SYZ performed data analysis and statistical analysis. WXZ, CL, and SYC wrote the paper. All authors reviewed and edited the manuscript and approved the final version of the manuscript.The authors declare that they have no conflict of interest.


Mitotic bookmarking constitutes a mechanism for transmitting transcriptional patterns through cell division. Bookmarking factors, comprising a subset of transcription factors (TFs), and multiple histone modifications retained in mitotic chromatin facilitate reactivation of transcription in the early G1 phase. However, the specific TFs that act as bookmarking factors remain largely unknown. Previously, we identified the “early G1 genes” and screened TFs that were predicted to bind to the upstream region of these genes, then identified GA-binding protein transcription factor alpha subunit (GABPA) and Sp1 transcription factor (SP1) as candidate bookmarking factors. Here we show that GABPA and multiple histone acetylation marks such as H3K9/14AC, H3K27AC, and H4K5AC are maintained at specific genomic sites in mitosis. During the M/G1 transition, the levels of these histone acetylations at the upstream regions of genes bound by GABPA in mitosis are decreased. Upon depletion of GABPA, levels of histone acetylation, especially H4K5AC, at several gene regions are increased, along with transcriptional induction at 1 h after release. Therefore, we proposed that GABPA cooperates with the states of histone acetylation to act as a novel bookmarking factor which, may negatively regulate transcription during the early G1 phase. Cell-type-, tissue-, and developmental stage-specific gene expression patterns are tightly controlled by transcriptional regulatory machinery consisting of specific transcription factors (TFs), epigenetic modifications, and higher-order chromatin structures. However, these cellular environments markedly change accompanying the breakdown of the nuclear envelope and chromatin condensation in mitosis, and are then restored upon chromatin decondensation and the reorganization of chromatin structures during the M/G1 transition [An early study showed that when cells enter mitosis, transcription is temporally silenced by the displacement of RNA polymerases and TFs from chromatin . When cePreviously we identified a variety of genes preferentially reactivated at the early G1 phase (early G1 genes) following establishment of a method for comprehensive gene expression analysis using nascent mRNAs specifically isolated from living mammalian cells and obtaining detailed expression profiles during the M/G1 transition. Furthermore, we discovered the motifs that were predicted to be bound by GA-binding protein transcription factor alpha subunit (GABPA) and Sp1 transcription factor (SP1) at upstream regions of all early G1 genes analyzed .GABPA plays an important role in regulating genes involved in various biological processes such as embryonic development, cell differentiation, cell cycle, and mitochondrial biogenesis ,26,27,28Gabpa knockdown affects histone acetylation at upstream regions of the studied genes and upregulates transcriptional reactivation during the M/G1 transition. Our results suggest that GABPA functions as a novel bookmarking factor that marks the various genes reactivated during the M/G1 transition along with multiple histone acetylations. Moreover, we propose that GABPA may regulate transcriptional reactivation of these genes by controlling histone acetylation states.Thus, we hypothesized that GABPA cooperates with SP1 in regulating early G1 gene transcription as a bookmarking factor. In this study, we investigated whether GABPA and SP1 are involved in mitotic bookmarking. Moreover, we also investigated whether these factors regulate the genes reactivated during the M/G1 transition by cooperating with multiple histone acetylation marks that have been reported to be involved in mitotic bookmarking. First, we showed that GABPA, but not SP1, binds to upstream regions of the several genes reactivated during the M/G1 transition in mitotic-arrested cells. Second, the levels of multiple histone acetylations such as H3K9/14AC, H3K27AC, and H4K5AC at the upstream regions of the genes bookmarked by GABPA are higher than those unbookmarked by GABPA in mitotic-arrested cells. Notably, we also found that the levels of multiple histone acetylations at the genes bookmarked by GABPA are decreased during the M/G1 transition, which is inconsistent with previous studies wherein histone acetylation levels were elevated during the M/G1 transition. Finally, we indicated that To assess whether GABPA and SP1 have the potential to act as bookmarking factors, we investigated their binding to mitotic chromatin. For this purpose, it was necessary for cells to be highly arrested in mitosis. Previously, we have demonstrated a method to synchronize the cell cycle in mitosis by a combination of temperature-sensitive CDC2 inactivation and nocodazole—an inhibitor of microtubule polymerization . We prepFth1 and Slc26a2 genes  assay coupled with quantitative PCR using asynchronous and mitotic-arrested tsFT210 cells. Several genes reactivated during the M/G1 transition were selected from our previous study of genome-wide gene expression analysis by DNA microarray using nascent mRNA , and bina2 genes . These rIt was previously shown that transcriptionally active gene regions are marked by histone acetylation during interphase, whereas in cells entering mitosis these histone acetylation sites are globally hypoacetylated . HoweverPrevious studies showed that a known bookmarking factor, bromodomain protein 4 (BRD4), binds to the transcriptional start sites of several “M/G1 genes” in mitosis, then BRD4 binding on these regions increases coinciding with the increase of histone H3/H4 acetylation during the M/G1 transition, thereby recruiting positive transcription elongation factor b (P-TEFb) and reactivating the transcription of “M/G1 genes” ,8. BasedGabpa knockdown on histone acetylation states. First, we confirmed the downregulation efficiency of siRNA against Gabpa. We downregulated GABPA in tsFT210 cells by siRNA and synchronized them in mitosis. Cells were harvested 1 h after release from mitotic arrest and then subjected to further assays. As shown in Gabpa. Second, to examine the effect of Gabpa knockdown on the acetylation levels of histone H3K9, H3K27, and H4K5 during the M/G1 transition, we performed a ChIP assay coupled with quantitative PCR using the same primer sets as in p < 0.05) of H4K5AC at Cox8a, Smndc1, and Rps21 (bookmarked genes) in the Gabpa knockdown cells at 1 h after release. Similar trends were observed for H3K27AC at Smndc1 and H4K5AC at Snrnp200, although they did not reach significance (p < 0.1). However, we could not observe an effect of Gabpa knockdown on the levels of these histone acetylation marks in mitosis, or those of H3K9/14AC at 1 h after release. In contrast, in asynchronous Gabpa knockdown cells, we detected an increase of these histone acetylation levels at Cox8a and an increase of H3K9/14AC or H3K27AC at several bookmarked, unbookmarked, or GABPA-unbound genes -PCR analysis. In this analysis, we used primers specific for pre-mRNAs to prevent detection of mature mRNAs that may have been carried over from a prior G2 phase. Prior to the analysis, we validated the expression profiles of the studied genes using primers specific for pre-mRNAs. Our result shows that the expression profiles of those genes were consistent with our previous microarray analysis of nascent mRNA [Gabpa resulted in the upregulation of pre-mRNA levels of the bookmarked genes at 1 h after release  acts as a transcriptionally suppressive bookmarking factor ,44,45. Nent mRNA   and those in “interphase and mitosis cells” (genes bookmarked by GATA1) . SimilarWe also revealed that multiple histone acetylation marks are retained or increased at upstream regions of the bookmarked genes in mitotic-arrested tsFT210 cells relative to those in asynchronous cells, whereas global histone acetylation levels are decreased during mitosis. The correlation between GABPA binding and histone acetylation states in asynchronous cells has been reported , whereasSkp promoter, with the resultant complex suppressing Skp gene transcription [Previous studies indicated that histone acetylations at several upstream regions of genes is elevated during the M/G1 transition ,8. Convecription . In addicription . Thus, iGabpa suggested that, at the early G1 phase, GABPA initially facilitates deacetylation of histone H4K5 and may function as a transcriptional suppressor for bookmarked genes. Thus, we have identified GABPA as a novel bookmarking factor that coordinates histone acetylation states and may suppress transcription during the M/G1 transition. Moreover, although these histone acetylation states between bookmarked genes, and unbookmarked and GABPA-unbound genes are significantly different at the all analyzed time points, these differences at the late time points tended to be greater than early time point  are reported to negatively regulate transcription ,33,34,35me point . TherefoGabpa indicated that there was no significant difference in transcriptional reactivation between the bookmarked and unbookmarked genes. These results raised the possibility that in present study the suppression of transcriptional reactivation at 1 h after release by knockdown of Gabpa is due to function of GABPA through cell cycle rather than the mitosis-specific function. However, described in the previous paragraph, the difference of the histone acetylation levels between bookmarked genes, and unbookmarked and GABPA-unbound genes is more different at the late phase of M/G1 transition. Therefore, it is also possible that the apparent effect of Gabpa knockdown involved in transcriptional reactivation of bookmarked genes may be detected at late phase of M/G1 transition. To address the issue that how GABPA functions as a bookmarking factor, there are two points of technical limitations. The first is that as our ChIP analysis targeted only limited regions near the transcription start sites, we cannot exclude the possibility that GABPA binds to other proximal or distal genomic regions and participates in mitotic bookmarking. It is generally considered that TF binding sites at proximal regulatory regions are widely distributed from upstream to downstream of the TSS. Indeed, the sites bound by known bookmarking factors in mitosis present at not only proximal promoter but also gene body and enhancer regions [In addition, our knockdown experiment of  regions ,11,18,19 regions ,19. TherIn conclusion, we identified GABPA as a novel bookmarking factor that marks the various tested genes in cooperation with multiple histone acetylations in mitosis and may act as a suppressor for genes reactivated during the M/G1 transition by regulating histone H4K5AC deacetylation. More precise analysis of the action of GABPA will provide further understanding of the molecular mechanism of mitotic bookmarking that regulate the transmission of transcriptional memory through cell division.tsFT210 cells—a Cdc2 temperature-sensitive mutant strain of mouse mammary FM3A cells—were cultured and synchronized as described in our previous study .tsFT210 cells were washed once with PBS (−), cross-linked in 4% paraformaldehyde at room temperature for 10 min. The cells were washed twice in PBS (−) and then fixed on a slide glass  by incubated at 37 °C for 40 min. The slides were washed twice with PBS (−), followed by permeabilization with 0.1% Triton X-100 at 4 °C for 5 min. After washes with PBS (−), cells were blocked for 1 h with 5% BSA in PBS (−). Primary antibody  diluted in 1% BSA in PBS (−) was added and incubated at room temperature for 1 h. After three washes with PBS (−), secondary antibodies (coupled to AlexaFluor 564) and DAPI  diluted in 1% BSA in PBS (−) were added and incubated at room temperature for 1 h. The slides were washed again three times with PBS (−) and mounted with fluorescence mounting medium . The fluorescence images were obtained using a BZ-X700 microscope .Asynchronous or mitotic-arrested tsFT210 cells were collected and fractionated into cytoplasmic and chromatin fractions using an EzSubcell Extract  following the manufacturer’s protocol.Asynchronous, mitotic-arrested, and released cells were lysed in 1% sodium dodecyl sulfate (SDS) in PBS (−) or fractionated into cytoplasmic and chromatin fractions. The lysates were then separated by SDS polyacrylamide gel electrophoresis, transferred to polyvinylidene fluoride membranes, blocked in 5% skim milk, and then probed with antibodies. Immunoreactive bands were visualized using the ECL western detection reagent  and LAS-4000 pro image analyzer . Primary antibodies were used as follows: anti-GABPA , anti-SP1 , anti-GAPDH , anti-histone H4 , anti-H3S10p , anti-H3K9/14AC , anti-H3K27AC , and anti-H4K5AC .6) were mixed with 200 pmol siRNA against Gabpa , MSS274444(#2)) or Negative Control siRNA  in 100 µL OPTI-MEM, then the mixture was transferred into 2 mm gap cuvettes. Cells were electroporated at 200 V for 2.5 ms twice using a NEPA21 electroporator . After dilution with 10 mL culture medium, the cells were transferred into a 10 cm dish and incubated for 48 h prior to further treatment.tsFT210 cells ) for at least 4 h at −20°C. Fixed cells were washed three times with staining buffer and then labeled with staining buffer containing 50 µg/mL propidium iodide  in the dark. Analysis of DNA content was performed by measuring the intensity of the fluorescence produced by propidium iodide using the FACSCalibur instrument .Asynchronous, mitotic-arrested, and released tsFT210 cells were fixed with 70% EtOH in staining buffer for at least 4 h at −20 °C. Fixed cells were washed two times with staining buffer and then permeabilized by 0.33% Triton X-100 in PBS (−). Permeabilized were washed one time with staining buffer, followed by incubation in staining buffer with phospho-H3 antibody  for 2 h and then with secondary antibody (coupled to AlexaFluor 488) for 30 min. Subsequently, the cells were resuspended in staining buffer containing 50 µg/mL propidium iodide and 10 µg/mL RNaseA, then incubated for 30 min at 37 °C in the dark. These cells were measured using an SH800 cell sorter .6 cells and then incubated for 10 min at 4 °C. Resuspended cells were sonicated in a bioruptor device   and spun down for 10 min at 8 °C at maximum speed. Supernatants were diluted 10 times with ChIP dilution buffer . Then, to avoid contamination of nonspecific binding substances, Dynabeads protein G (Thermo Fisher Scientific) were added and incubated for 1 h with rotation at 4 °C. Beads were immobilized on a magnet and supernatants were collected. Collected supernatants were incubated with the antibody against GABPA  or normal rabbit IgG  overnight with rotation at 4 °C. The next, day, Dynabeads protein G were added and incubated for 1 h with rotation at 4 °C. Then, the beads were immobilized on a magnet and washed three times in low-salt buffer , twice in high-salt buffer , once in LiCl buffer , 1 mM EDTA, 10 mM Tris pH 8.1), and once in TE buffer. DNA was then eluted from the beads by incubating with 200 µL ChIP elution buffer  for 6 h at 65 °C. Supernatants were treated with RNase A for 30 min and proteinase K for 1 h. After the treatment, DNA was purified using the Wizard SV Gel and PCR Clean-Up System .For the ChIP assay to detect GABPA binding, asynchronous or mitotic-arrested tsFT210 cells were cross-linked in 1% formaldehyde at room temperature for 10 min and quenched with 150 mM glycine for 5 min at room temperature. Cells were washed twice in PBS and resuspended in 200 µL SDS lysis buffer  pH 8.0, 1% SDS, 1 mM phenylmethyl sulfonyl fluoride (PMSF), complete in EASYPack protease inhibitor cocktail) per 5.0 × 10® Enzymatic Chromatin IP Kit (Magnetic Beads) following manufacturer’s protocol. Antibodies used: anti-SP1 , anti-histone H3 , anti-H3K9/14AC , anti-H3K27AC , anti-H4K5AC , anti-Pol II , and anti-BRD4 .For ChIP assay to detect histone H3, H3K9/14AC, H3K27AC, H4K5AC, SP1, Pol II, and BRD4 binding, asynchronous, mitotic-arrested, or released tsFT210 cells were cross-linked in 1% formaldehyde at room temperature for 10 min and quenched with glycine solution (10×) for 5 min at room temperature. Subsequent assays were performed using the SimpleChIPChIP-quantitative PCR and RT-PCR were performed using the KOD SYBR qPCR Mix . The sequences of each primer are described in


To better understand the impact of chromatin structure on regulation of the prostate cancer transcriptome, we develop high-resolution chromatin interaction maps in normal and prostate cancer cells using in situ Hi-C. By combining the in situ Hi-C data with active and repressive histone marks, CTCF binding sites, nucleosome-depleted regions, and transcriptome profiling, we identify topologically associating domains (TADs) that change in size and epigenetic states between normal and prostate cancer cells. Moreover, we identify normal and prostate cancer-specific enhancer-promoter loops and involved transcription factors. For example, we show that FOXA1 is enriched in prostate cancer-specific enhancer-promoter loop anchors. We also find that the chromatin structure surrounding the androgen receptor (AR) locus is altered in the prostate cancer cells with many cancer-specific enhancer-promoter loops. This creation of 3D epigenomic maps enables a better understanding of prostate cancer biology and mechanisms of gene regulation. In prostate cancer, chromatin structure can impact the transcriptome. Here, the authors develop high resolution chromatin interaction maps in prostate cancer cells using in situ Hi-C, revealing prostate cancer-specific TADs and enhancer-promoter loops surrounding the androgen receptor (AR) locus. Unlike normal prostate cells, prostate cancer cells have greatly dysregulated transcriptome profiles, causing uncontrolled cell proliferation3. Clearly, new insights into the mechanisms by which the prostate cancer transcriptome is controlled would provide valuable information for diagnosis and treatment.Prostate cancer is the leading cause of new cancer cases and the second most common cancer in men and the fourth most common tumor type worldwide. Multiple genetic and environmental factors including genetic susceptibility, family history, age, and race contribute to prostate cancer risk6. Although previous studies have found that the boundaries of most TADs are conserved across cell types8, the epigenomic profiles (and thus the chromatin states) of a TAD can differ by cell type. Also, as cells change from one cell type to another, certain TADs transition between active and inactive chromatin states or vice versa. The epigenetic state of a TAD can influence the general expression level of genes within a given TAD. Moreover, genes are most often regulated by enhancers located within the same TAD. Alteration of the chromatin loops that occur between pairs of regulatory elements bound by CTCF can bring together (or split apart) a promoter from a distal regulatory element, causing changes in gene expression. Thus, the transcriptome can be affected by changes in TAD boundaries. Finally, cancer-specific changes in the activity of regulatory elements such as enhancers (caused by the gain or loss of TFs) can also cause alterations in expression of specific genes due to changes in long-range enhancer–promoter loops10.The human genome is organized in three-dimensional (3D) space in the nucleus into active and inactive compartments and regions of high within contact frequency called topologically associating domains (TADs). Protein–protein interactions involving cohesin complexes and CTCF mediate long-range chromatin looping. The general activity of a TAD can be determined by its epigenomic profile (i.e. which types of modified histones are bound), being classified as either open (active) or closed (repressive)11. By performing in situ Hi-C and increasing the sequencing depth of the in situ Hi-C libraries, high-resolution intra-TAD chromatin interactions between regulatory elements such as promoters and enhancers can be found13. Moreover, the epigenetic state of the interacting regions can be characterized using ChIP-seq of specifically modified histones, which mark regulatory elements. TFs that are involved in the chromatin interactions can be inferred from motif analyses using methods such as DNase-seq, ATAC-seq, or NOMe-seq (Nucleosome Occupancy and Methylome sequencing), which define nucleosome-depleted regions (NDRs) that correspond to TF-binding platforms, and the binding sites of TFs can be further identified by ChIP-seq.To study these chromatin interactions, various chromatin conformation capture assays have been developed. Hi-C, a genome-wide chromatin conformation capture assay, has been particularly useful for mapping the very large structural TADsTo better understand the mechanisms by which the prostate cancer transcriptome is controlled, we have used a combination of these methods in normal prostate and prostate cancer cells to (a) map TAD boundaries, (b) investigate the epigenetic state of the TADs, and (c) identify and characterize normal- and cancer-specific enhancer–promoter loops. We performed high-resolution in situ Hi-C in normal prostate cells and prostate cancer cells, sequencing ~1 billion reads per cell line. We also performed ChIP-seq for modified histones and CTCF, NOMe-seq, and RNA-seq in normal and prostate cancer cells. This characterization of TADs and chromatin loops provides more detailed epigenetic mechanisms of prostate tumorigenesis.14. More than 80% of TADs are reproducible between replicates ; see Fig. Using in situ Hi-C with a 4-cutter restriction enzyme MboI, we created high-resolution chromatin contact interaction profiles  in normal prostate (RWPE1) and prostate cancer (C42B and 22Rv1) cells , we identified ~520 large size TADs in normal cells that correspond to ~850 smaller TADs in cancer cells. Interestingly, we found that in these altered TADs, relatively more genes showed increased expression in cancer cells than in normal cells     Fig. . Among ~The above analyses identified TADs that have different boundaries in normal and cancer cells and correlated these boundary changes with changes in gene expression. However, they did not provide information concerning the overall nature of the chromatin state of the TADs or how the epigenetic state may influence the expression level of the genes within the TADs. Therefore, we further characterized the TADs by performing ChIP-seq in normal and prostate cancer cells with antibodies that demarcate active and inactive regions Fig. . We usedHaving characterized the epigenetic states of all TADs in RWPE1, C42B, and 22Rv1 cells, we next specifically examined the epigenetic states and expression levels within the sets of common, normal-specific, and cancer-specific TADs. We found that normal-specific TADs have a higher percentage of H3K9me3-enriched TADs than either the cancer-specific TADs or the common TADs  Fig. . As showp value < 5.93e-05, H3K9me3 vs H3K36me3: adj. p value < 7.44e-25, H3K27me3 vs H3K36me3: adj. p value < 1.80e-13, Fisher’s exact test). An example of a common TAD found at chromosome 6q23 that has a different epigenetic state in normal cells (H3K27me3) and cancer cells (H3K36me3) is shown in Fig. p value < 0.05)  and very few H3K36me3 TADs changing state (17.5%) Fig.  , active enhancers (defined as H3K27ac ChIP-seq peaks that are not near a TSS), and CTCF-binding sites (defined as CTCF ChIP-seq peaks that are not overlapping with the sets of promoters or enhancers). Using a q-value cutoff of 0.05, we found that ~70% of the promoter and enhancer regions and ~90% of the CTCF peaks overlapped with a chromatin interaction anchor. In the top 20 most frequent chromatin interaction categories, most loops had a CTCF site at one or both anchor regions, providing evidence in support of the robustness of the analysis methods. We also identified sets of loops involving both enhancers and promoters . It is important to note that although ~70% of the promoters are involved in loops, less than 50% of the promoters looped to enhancers . We then further subdivided genes having the enhancer–promoter loops into genes having loops from a promoter to a common enhancer vs from a promoter to a normal-specific or cancer-specific enhancer. Interestingly, the genes regulated by promoters looped to cancer-specific enhancers show higher gene expression in the cancer cells, as compared to genes regulated by promoters looped to normal-specific or common enhancers   in normal and prostate cancer cells using the Fit-HiC programers Fig. . The looers Fig. . Similarers Fig. . We next06) Fig. , suggest16 can, upon binding to regulatory elements and recruitment of HATs, cause the creation of a cell-type-distinguishing H3K27ac epigenomic (enhancer) profile. Also, chromatin interaction studies of different cell types have identified TFs that are specifically involved in looping17. Therefore, we next identified the TF-binding motifs that are found within the active enhancers that loop to promoters in normal (RWPE1) and prostate cancer (C42B) cells. H3K27ac ChIP-seq peaks are broad and cover many more nucleotides than the actual TF binding platforms  located at chromosome 8q22.3 is identified by NOMe-seq; motif search on this NDR identified a FOXA1 motif  are key regulators that can drive changes in transcription of numerous genes along pathways by binding to DNA regulatory elements. Cell-type-specific TFsrms Fig. . Howevertif Fig. . Therefotif Fig. . Both sep value < 1.5e-07)   of the cancer-specific enhancers that are involved in enhancer–promoter loops in C42B prostate cancer cells are bound by FOXA1, suggesting that FOXA1 is a major regulator of the cancer transcriptome  as well as the androgen receptor (AR) and androgen-responsive genes (e.g. GRHL2) are target genes of FOXA1-bound enhancers  .Using a dilution Hi-C method, a previous studyTBX3 and PRMT6, which are known to be involved in prostate cancers24. The findings that transcriptionally active TADs (H3K36me3-enriched TADs) are smallest in size than other histone mark-enriched TADs  as the CTCF/cohesin loops, suggesting that any enhancer–promoter loops not detected in our studies are likely to be quite weak. The low interaction frequency of the enhancer–promoter loops may be due to the fact that, unlike CTCF which is stably bound to the chromatin, TFs that mediate these loops bind to DNA in a dynamic manner33.The high resolution of in situ Hi-C also allowed the identification of chromatin loops (in addition to the TADs). As anticipated, the loops we identified by in situ Hi-C are mostly found between pairs of CTCF/cohesin complexes, providing assurance that our experimental and analytical results are robust. Interestingly, only a small percentage of the loops we identified are between enhancers and promoters (even with the high depth of sequencing of the Hi-C libraries). It is possible that targeted sequencing methods such as promoter capture Hi-C16. On the contrary, prostate-cancer-specific enhancers had motifs for FOXA1, GRHL2, AR, and ETS. AR, FOXA1, and GRHL2 (a co-regulator of AR) are key TFs that promote prostate tumor progression34. ETS family TFs such as ERG, ETV1, and ETV4, are known prostate oncogenic regulators35. Using ChIP-seq data for the most enriched TF FOXA1, we also revealed target genes of prostate-cancer-specific enhancers. For example, HOXC6 and DLX1 genes, which are biomarkers and key players of prostate cancer development36 as well as genes involved cell cycle  and androgen signaling  are found.To gain insight into the TFs that are bound at the strongest enhancer–promoter loops, we performed NOMe-seq to call NDRs and performed motif analyses using the nucleosome-depleted regions within the looped enhancers. We identified distinct TF motifs at enhancers that loop to promoters in normal vs cancer cells. For instance, normal-specific enhancers had motifs for AP-1, TP63, and NFE2, which are known to be enriched in open chromatin in several types of normal, differentiated cellsAR locus . AR-V7 contains the N-terminal transactivation and DNA-binding domains of AR, but lacks the ligand-binding domain that is present in full-length AR (AR-FL). The presence of AR-V7 is known to be associated with resistance to hormone therapy37. The identified enhancers involved in cancer-specific enhancer–promoter loops may have an effect on expression of AR gene, which includes AR-V7 isoform. Others have shown that a regulatory element can be an oncogenic driver for advanced prostate cancer38. Moreover, as targeting AR splice variants have proved to be challenging39, further investigation of this AR-V7 enhancer will be beneficial for understanding the etiology of prostate cancer subtypes as well as potentially developing future clinical treatments for CRPC.An example locus that includes cancer-specific enhancer–promoter loops is the cus Fig. . 22Rv1 c40. These findings support the model that chromatin interactions and structural changes can be key contributors for gene regulation in prostate cancer transcriptome. However, there are still many unanswered questions concerning mechanisms of TAD boundary formation and gene regulation. For example, the effect on gene expression upon deletion of CTCF-binding sites varies depending on their locations in the genome and cell types40. Enhancer and CTCF enrichment signals detected by ChIP-seq, distance between gene and regulatory elements, CTCF motif direction, and chromatin interaction frequency may be potential factors that can contribute to this variability, but there is not yet a clear formula that can predict the degree of effects. Other studies have shown that loss of cohesin eliminates most chromatin interaction loops but only a few genes near a subset of enhancers showed expression changes41. Clearly, further studies on the mechanisms that mediate chromatin structure formation and gene regulation are needed. Moreover, additional high-resolution chromatin contact maps are required to further investigate the chromatin interaction loops in other normal and prostate cancer subgroups. Although we have found that majority of genes that changed expression by TAD structure, epigenetic states, and loops do not have genetic alterations such as copy number variations and mutations . Cells were grown at 37 °C in 5% CO2; the corresponding culture medium for each cell line (RPMI 1640 for C42B and 22Rv1 and Keratinocyte Serum Free Medium for RWPE1) was supplemented with 10% fetal bovine serum  and 1% penicillin and streptomycin. All cell stocks were authenticated at the USC Norris Cancer Center cell culture facility by comparison to the ATCC and/or published genomic criteria for that specific cell line; all cells were documented as free of mycoplasma.The human prostate cancer C42B cells were obtained from ViroMed Laboratories  whereas the human prostate cancer 22Rv1 (ATCC # CRL-2505) and normal prostate RWPE1 (ATCC # CRL-11609) cells were obtained from American Type Culture Collection (ATCC) (5 with minor modifications (such as the use of a 4-cutter restriction enzyme (MboI) instead of a 6-cutter restriction enzyme) as we have performed previously42. In situ Hi-C was performed in triplicate for C42B and in duplicate for 22Rv1 and RWPE1 (5 × 106 cells were used for each experiment). One hundred units of MboI restriction enzyme  was used to digest the chromatin. For ligation, 2000U of T4 DNA Ligase  was added and samples were incubated at room temperature for 4 h with slow rotation. Hi-C chromatin was sheared to a size of 300–500 bp using a Covaris instrument . Biotin-tagged DNA was pulled down using Dynabeads MyOne Streptavidin C1 beads  with 2× Binding Buffer (2× BB: 10 mM Tris-HCl (pH 7.5), 1 nM EDTA, 2 M NaCl). Each Hi-C library was amplified with 14 cycles of PCR, using Illumina primers. Each library was sequenced (75 bp paired-end) to produce ~500 M read pairs using an Illumina HiSeq 2000 per replicate (Supplementary Data 43 and HiC-Pro version 2.8.0 (ref. 44). Raw fastq files were processed through the HiC-Pro pipeline version 2.8.0 (ref. 44) to create raw contact count matrices at multiple resolutions . The matrices were normalized using the iterative correction method (iced python library). After demonstrating that the individual Hi-C libraries were of high quality and reproducible, the Hi-C replicate datasets for a given cell line were pooled to increase the sequencing coverage. Hi-C data generated in this study are submitted to the NCBI GEO with accession number GSE118629.In situ Hi-C experiments were performed using RWPE1, C42B, and 22Rv1 cells following the original protocol by Rao et al.https://www.encodeproject.org/data-standards/). Each ChIP-seq experiment was performed in duplicate and ChIP-seq libraries were sequenced on an Illumina Hiseq machine. All ChIP-seq data were mapped to hg19 and peaks were called using MACS2 (ref. 45) after preprocessing data with the ENCODE3 ChIP-seq pipeline (https://www.encodeproject.org/chip-seq/). To call reproducible peaks from two replicates, the IDR tool (https://github.com/nboley/idr) for TF datasets or the naïve overlap tool for histone mark datasets was used, as suggested in the ENCODE3 ChIP-seq standards document (https://www.encodeproject.org/pages/pipelines/) and performed previously46. ChIP-seq data generated in this study are submitted to the NCBI GEO with accession number GSE118629. H3K27ac and CTCF ChIP-seq datasets, which are used to annotate active regulatory elements, are generated in previous studies40 and available from ENCODE (https://www.encodeproject.org/). FOXA1 ChIP-seq data in C42B19 were obtained from GSE40050 , H3K27me3 , and H3K36me3  antibodies, according to the ENCODE standards  was used to generate weighted Venn diagrams. Histone-mark-enriched TADs were defined as TADs that intersected with top 30k of ChIP-seq peaks (top 25%) and having most enriched average ChIP-seq signals (top 25%). Bedtools (https://github.com/arq5x/bedtools2) was used to intersect genomic regions and multiBigwigSummary function from deepTools47 was used to calculate average ChIP-seq signals per TAD using a fold change ChIP-seq bigwig file generated from MACS2 (ref. 45) using each histone-mark ChIP-seq vs input. To test whether TADs are functional units, we first chose H3K36me3-enriched TADs which has an average size of ~350 kb. We randomly generated 100 sets of TADs, which are in the range of 280 and 440 kb in the genome. Next, we counted how many TADs were enriched for H3K36me3 marks in randomly generated TADs to calculate empirical p value as we have done to call H3K36me3-enriched TADs. Gene desert TADs were defined as TADs that lack of genes . Gene poor TADs were defined as TADs that have one to five genes per TAD. Gene-enriched TADs were defined as TADs that have more than five genes per TAD.To identify TADs, the normalized Hi-C contact matrices, binned at 40 kb resolution, were used and domains were called using the TopDom program15 . The anchors of the loops were intersected with active regulatory elements using a sequential classification scheme to sort the elements into promoter, defined as ±2kb windows of the TSS of all expressed genes (as determined using from RNA-seq data from the specific cell line), enhancer , and insulator . The top 20 most frequent chromatin interaction categories are shown in Fig. p value < 0.01). Enhancer–promoter loops found from each cell line are listed in Supplementary Data p values accounting for multiple comparison issues . Using the RCircos program48, Circos plots for FOXA1-binding sites and target genes of FOXA1-bound enhancers are generated  were selected for each cell line using the Fit-Hi-C programted Fig.  and the 42. After preparing cDNA using the SuperScript® VILO™ cDNA Synthesis Kit , RNA-seq libraries were made using KAPA Stranded mRNA-Seq Kit with KAPA mRNA Capture Beads  and sequenced on an Illumina NextSeq 500 with 75 bp single end reads or on a HiSeq 3000 with 50 bp single end reads. Reads were mapped to hg19 GENCODE version 19 using STAR 2.4.1d49 and aligned reads were quantified at the gene level using Partek® Flow® software Quantify to annotation model . The RPKM normalization method was used and log2 transformed. Genes expressed having a log2(RPKM + 1) > 1.5 on average from the triplicates were selected as actively expressed genes for active promoter identification. Differentially expressed genes between normal and cancer cells were selected by using the Gene Specific Algorithm from Partek® Flow® software using the upper quartile normalization method    and the quality of RNA was assessed using a 2100 Bioanalyzer instrument , as we have performed previously18. Chromatin was treated with the M.CviPI methyltransferase , which methylates GpC dinucleotides that are not protected by nucleosomes or other proteins that are tightly bound to the chromatin. Following bisulfite treatment of the M.CviPI-methylated chromatin and subsequent genomic sequencing, we identified endogenous methylation (CpG) and accessibility (GpC) in the same sequencing reaction. The RWPE1 NOMe-seq library was sequenced using an Illumina HiSeq 2000 (100 bp paired-end), and NOMe-seq data were deposited in the NCBI GEO accession number, GSE118629; the C42B NOMe-seq library was previously generated46 (GSE102616). Each fastq file was aligned to a bisulfite-converted genome (hg19) using BSMAP50 and processed using the software programs Picard (http://picard.sourceforge.net) and SAMtools (http://samtools.sourceforge.net). To identify the methylation status of CpG sites  and GpC sites  from the bam file, the Bis-SNP51 program was used. For identification of NDRs, the find NDRs function in the aaRon R package (https://github.com/astatham/aaRon) was used with the p value cutoff 10−8. Top 50k of NDRs were used to find enhancer NDRs for motif analyses 54 to discover known motifs at enhancer NDRs under enhancer–promoter loop anchors in normal (RWPE1) and tumor (C42B) prostate cells. The top 15 enriched motifs in these NDRs were identified by ranking motifs using q-values.We used the findMotifsGenome.pl script from HOMER  data in RWPE1 normal prostate and 22Rv1 prostate cancer cells3 was downloaded from the National Cancer Institute GDC Data Portal . Normalized gene expression level of FOXA1 gene (log2(RSEM + 1)) was used to generate a Supplementary Fig. t-test was used to measure the gene expression difference between normal and tumor samples.RNA-seq data of prostate tissues  for The Cancer Genome Atlas (TCGA)Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Reporting Summary


Cells engaging in inflammation undergo drastic changes of their transcriptomes. In order to tailor these alterations in gene expression to the requirements of the inflammatory process, tight and coordinate regulation of gene expression by environmental cues, microbial or danger-associated molecules or cytokines, are mandatory. The transcriptional response is set off by signal-regulated transcription factors (SRTFs) at the receiving end of pathways originating at pattern recognition- and cytokine receptors. These interact with a genome that has been set for an appropriate response by prior activity of pioneer or lineage determining transcription factors (LDTFs). The same types of transcription factors are also critical determinants of the changes in chromatin landscapes and transcriptomes that specify potential consequences of inflammation: tissue repair, training, and tolerance. Here we focus on the role of three families of SRTFs in inflammation and its sequels: signal transducers and activators of transcription (STATs), interferon regulatory factors (IRFs), and nuclear factor κB (NFκB). We describe recent findings about their interactions and about their networking with LDTFs. Our aim is to provide a snapshot of a highly dynamic research area. Inflammation is a rapid response of the innate immune system to infection or sterile causes of trauma and tissue damage. Its main purpose is to alert, recruit, and activate cells of the immune system, mobilize the adaptive immune system, remove the infectious agent or other proinflammatory stimuli and, ultimately, repair the tissue damage inflicted by both the trigger of inflammation and the inflammatory process . These eThe progression to a proinflammatory state necessitates dramatic transcriptome changes of the participating cells. Cells such as macrophages with a pivotal role in orchestrating inflammation acquire an appropriately structured genome during differentiation . In molein vitro by using IFNγ/LPS (M1) or IL4 (M2), represent extremes with most likely no direct in-vivo equivalent , interferon regulatory factors (IRFs) and nuclear factor κB (NFκB) are major players among SRTFs. Different family members function in the establishment as well as the resolution or prevention of inflammation. This dual mode of macrophage activity during inflammation is represented by the polarization of macrophages into the proinflammatory M1 type and the inflammation-resolving M2 type. While these types, generated uivalent –9, they For in-depth information and additional references concerning these transcription factor families the reader is referred to comprehensive reviews –15.de-novo. Dimerization is stabilized by reciprocal phosphotyrosine (pY) interactions with SH2 domains which are, among transcription factors, a distinguishing feature of STATs . All family members function predominantly in the context of cytokine-responsive, two-component JAK-STAT pathways. When cytokine receptors bind their cognate ligands, one or more receptor-associated Janus protein tyrosine kinases (JAKs) are activated and phosphorylate latent STATs on a single tyrosine residue. In some STATs this leads to a reorientation of preformed dimers into a parallel arrangement  whereas s Figure . Homo-or 3−4GAA; ]. In con 3−4GAA; ]. The IS 3−4GAA; –30. We a 3−4GAA; –33. Unli 3−4GAA; .The original description and eponymous function of IRFs derives from their activity as regulators of the genes encoding type I IFN . The minPhosphorylation-dependent IRFs function downstream of toll-like receptors (TLR) and cytosolic nucleic acid receptors , 3. The Various canonical and non-canonical NFκB complexes are formed by members of the Rel family of transcription factors which contain a Rel homology domain (RHD) for DNA binding and, in case of the RelA, RelB, and c-Rel family members, a C-terminal transactivation domain . The p52There are several conceptual possibilities how transcription factors form networks Table . NetworkThe changes in genome structure occurring during macrophage differentiation set the stage for appropriate responses of the mature cells to challenges such as infection or inducers of sterile inflammation Figure . As outlNot all enhancers of inflammatory gene expression are established during differentiation. Activation of terminally differentiated macrophages also causes the binding of both LDTFs and SRTFs to “latent” enhancers, i.e., sequences embedded into nucleosomes that have not been previously remodeled and marked by deposition of H3K4me1. Both IFNγ and the alternative M2 polarization factor IL4 (see below) convert latent into active enhancers by providing STAT1 and STAT6, respectively . UnexpecLeishmania major  remodeling complex including the ATPase BRG1 . In addiListeria monocytogenes. They include the genes encoding iNOS (NOS2) or IL6. Mechanistically the cooperativity at these two genes is explained by NFκB predominance in the recruitment of histone-modifying enzymes, the BET protein Brd4 and the TFIIH and pTEFb complexes needed for the phosphorylation of the RNA polymerase II (Pol II) carboxyterminal domain  or the mannose receptor Mrc1 are expressed in adipose tissue macrophages, but also in tumor-associated macrophages or in macrophages fighting parasitic infections , 64. UnlIFNγ/LPS .−/− macrophages do not undergo M2 polarization during helminth infection . This explains in part why its target genes are different from those activated by STAT1. On the other hand, genome-wide analysis of STAT1 and STAT6 binding to GAS elements revealed a large number of sites occupied by STAT1 and STAT6, respectively, in IFNγ or IL4-stimulated cells  development in vivo  in a transcriptional network including RelB and Notch2 , 135. IR+ DC, generated in vitro with GM-CSF, for stimulation with LPS. Prominent LDTFs were Pu.1 and C/EBP as in macrophages. However, whether they occupy different sites in the two cell types has not been determined. In the LPS response the authors distinguished immediate and delayed response gene clusters that differed in priming factors  and dynamic association of the SRTFs IRF1 and NFκB. As might be expected from the kinetics of IFN production during the LPS response, STATs 1 and 2 associated with the delayed, but not the immediate LPS-responsive gene cluster.Similar to the studies defining the hierarchical action of transcription factors and the distinction between LDTFs and SRTFs in macrophages, Garber and colleagues defined analogous networks of preexisting pioneers (LDTFs) for lineage commitment, broad binders for priming, and dynamic factors (SRTFs) for execution . The autThe data in DC support the notion that the molecular principles governing enhancer accessibility, priming, and signal-regulated response are very similar between macrophages and DC, although the detailed usage of transcription factors for each stage of the transcriptional response during inflammation may differ.This review is focused on the role of macrophages in inflammation, with lesser attention to DC or non-hematopoietic cells. We realize this is only one chapter of a complex story but, based on available data, have focused on the cells allowing for the closest inspection of transcriptional networks in inflammation. Detailed views of the inflammatory response in other cells of the innate immune system are needed. In an organismic context, macrophages are shaped by their local environment . The impAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The handling Editor declared a past collaboration with one of the authors TD. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


SETDB1 (SET Domain Bifurcated histone lysine methyltransferase 1) is a key lysine methyltransferase (KMT) required in embryonic stem cells (ESCs), where it silences transposable elements and DNA repeats via histone H3 lysine 9 tri-methylation (H3K9me3), independently of DNA methylation. The H3K9 methylation reader M-Phase Phosphoprotein 8 (MPP8) is highly expressed in ESCs and germline cells. Although evidence of a cooperation between H3K9 KMTs and MPP8 in committed cells has emerged, the interplay between H3K9 methylation writers and MPP8 in ESCs remains elusive. Here, we show that MPP8 interacts physically and functionally with SETDB1 in ESCs. Indeed, combining biochemical, transcriptomic and genomic analyses, we found that MPP8 and SETDB1 co-regulate a significant number of common genomic targets, especially the DNA satellite repeats. Together, our data point to a model in which the silencing of a class of repeated sequences in ESCs involves the cooperation between the H3K9 methylation writer SETDB1 and its reader MPP8. Post-translational modifications of histones play key roles in DNA functions in the chromatin context. In this, methylation of histone H3 lysine 9 (H3K9) generally correlates with transcriptional repression and heterochromatin formation . The maiSetdb1-null mouse blastocysts fail to give rise to ESCs in vitro [Setdb1 knockdown (KD) in mESCs results in loss of Oct4 expression and abnormal expression of various differentiation markers and de-repression of many repeated elements [SET Domain Bifurcated histone lysine methyltransferase 1 (SETDB1 or ESET in mouse) is a key H3K9 lysine methyltransferase (KMT). SETDB1 is able to establish H3K9 mono, di- and tri-methylation, the latest in cooperation with its co-factor ATF7IP , which is necessary for the conversion of H3K9me2 to H3K9me3 ,5,6 and elements . Consistelements ,9,10.Methylated lysine residues serve as docking sites for numerous proteins that contain methyl-lysine-binding domains such as the chromodomain, the Plant HomeoDomain (PHD) or the Tudor domains . Among tExpression of MPP8 is especially high in stem and germ cells and thus may play key roles in these cells’ chromatin features. However, its role in ESCs has never been studied, contrary to the main H3K9 KMTs SETDB1, G9A/GLP and SUV39H1/2 that are extensively studied in mESCs  supplemented with 10% of fetal bovine serum (FBS-GE), 1% penicillin/streptomycin  and sodium pyruvate . HeLa-S3 cells were maintained at 37 °C and 5% CO2.HM1 and TT2 mESCs were cultured in ESCs media: DMEM media  supplemented with 15% fetal calf serum , 1% penicillin/streptomycin , 0.1 mM β-mercaptoethanol , 1 mM nonessential amino acids , and 1000 U/mL of Leukemia Inhibitory Factor (LIF) . All mESC lines were cultured in standard feeder-free conditions with 0.2% gelatin, maintained at 37 °C and 8% COSetdb1 cKO mESCs were established by the group of Prof. Yoishi Shinkai via standard gene targeting procedures [Setdb1 cKO mESC line, Cre recombinase and estrogen receptor (Cre-ER) fusion gene was introduced into a clone containing targeted Setdb1 cKO and KO alleles. To induce deletion of the Setdb1 cKO allele, TT2 mESCs were cultured in 800 nM 4-Hydroxy Tamoxifen  for 96 hours.ocedures . To geneHM1 ESCs were seeded in ESCs media to achieve 70–80% confluence and 24 h later were transfected with siRNAs  to achieve a final siRNA concentration of 25 pM using the Lipofectamine RNAiMax reagent and OPTIMEM . A second round of transfection was performed 24 h later using the same siRNA concentration. Cells were harvested after 72 h post first transfection. siRNA sequences are listed in the We used HeLa-S3 cell lines stably expressing Flag-HA tagged MPP8 (only chromobox or full-length), established by retroviral transduction of human full-length transgenes, as described in . A cell 2) to a final NaCl concentration of 300 mM, and incubated for 30 min on ice. Then, sucrose buffer was added to a final NaCl concentration of 100 mM. The nuclear extracts were treated with Micrococcal nuclease (0.0125 U/mL) and 1 mM CaCl2 at 37 °C during 15 min. Then, EDTA was added to 4 mM final concentration and subsequent sonication for 5 min  at medium frequency  was performed. The lysates were ultracentrifugated at 40000 rpm for 30 min and pre-cleared with protein G-agarose beads  during 2 h, at 4 °C. Immunoprecipitations were carried out overnight at 4 °C using 500 μg of nuclear extract and 5 μg of antibodies against SETDB1 , MPP8  and IgG . Pierce™ Protein A/G UltraLink™ Resin  was blocked overnight at 4 °C with 0.3% Bovine Serum Albumin (BSA). Immune complexes were recovered by adding pre-blocked protein A/G Ultralink beads and incubated for 2 h, at 4 °C. Beads were washed four times in Wash buffer  and the proteins were eluted in NuPAGE® LDS Sample Buffer  and 10X reducing agent at 96 °C during 10 min. Finally, the immunoprecipitates were tested by Western blot.40 million cells were lysed in Buffer A , 10% NP40 and SR buffer  sucrose) supplemented with protease inhibitor , 1 mM DTT and spermidine-spermine  to limit nuclei leak. Cell lysates were centrifuged at 2000 g for 5 min. The nuclei pellets were resuspended in sucrose buffer  and high salt buffer was added   and 1X NuPAGE MES SDS Running Buffer and transferred into nitrocellulose membrane  in 20 mM phosphate transfer buffer (pH 6.7). Membrane was blocked in 5% skim milk in PBST Buffer  and incubated overnight at 4 °C with the primary antibodies against SETDB1 , MPP8 . Membranes were incubated with the appropriate secondary antibody coupled to HRP, revealed using West Dura kit  and ChemiSmart 5000 system . When necessary, the TrueBlot secondary Ab  was used to reduce interference with the ~55 kDa heavy and ~23 kDa light chains of immunoprecipitating IgG.2 and 2 mM DiSuccinimidyl glutarate  diluted in DMSO  during 45 min at RT as described in [Cells were cross-linked directly in the culture plate with PBS supplemented with 1 mM MgClribed in . Then, aFive to fifteen nanograms of ChIPed DNA or un-enriched whole cell extract (Input) were prepared for sequencing on Illumina Hiseq 2000. We used the library kit  with modifications as follows: DNA fragments were repaired to blunt ends, purified with magnetic beads  and a step of A tailing was performed before Illumina adapters ligation. Two steps of DNA purification with magnetic beads were carried out to eliminate un-ligated adaptors and then amplified with 15 PCR cycles. To remove un-ligated adapters and un-sequenceable large DNA fragments, DNA libraries were selected on E-Gel  to obtain 280–330 bp DNA fragments (including 130 bp of adapters). Final library was quality checked by DNA high sensitivity chip  and for positive target enrichment by qPCR. Quality-controlled samples were then quantified by qPCR and picogreen . Libraries were pooled thanks to various adaptors and qPCR relative measurements. Cluster amplification and following sequencing steps strictly followed Illumina standard protocol.Sequenced reads were de-multiplexed to attribute each read to a DNA sample and then aligned to reference mouse genome mm10 with bowtie . After PCR duplicates removal, enriched regions were detected by MACS 1.4 software package , using ICyclophillin A or GAPDH. Primers are listed in the Total RNA was extracted using RNeasy mini-kit  following manufacturer’s procedures. DNase  treatment was performed to remove residual DNA. With High Capacity cDNA Reverse Transcription Kit , 1 μg of total RNA was reverse transcribed. Real-time quantitative PCR was performed to analyze relative gene expression levels using SYBR Green Master mix  following manufacturer indications. Relative expression values were normalized to the housekeeping genes mRNA RNA was isolated as described above. Three independent biological replicates were sequenced per cell condition. Libraries were generated using the TruSeq stranded mRNA library prep Kit, set A and B . The obtained directional libraries were controlled by Bioanalyzer DNA1000 Chips  and quantified by spectrofluorimetry . Sequencing was performed on a HiSeq 2500  in a 51 bases single read using a HiSeq SR Cluster kit v4 cBot HS  and a HiSeq SBS kit v4 HS 50 cycles . Sequences were demultiplexed using the Illumina pipeline  giving FASTQ formatted reads. Mus musculus GRCm38.9 GTF file was downloaded from Ensembl (https://www.ensembl.org) and the exon annotation lines were extracted from the file to use as GTF annotation file. FeatureCounts v1.6.0.2 [www.repeatmasker.org) and repeats annotated as “Low complexity” or “Simple repeat” were filtered out. RepEnrich [https://david.ncifcrf.gov/) [Using the Galaxy platform, high quality one-end reads for the three replicates  were mapped onto mouse genome (mm10) using Bowtie2 v2.3.4.1  with defv1.6.0.2  was usedv1.6.0.2 . mm10 reepEnrich  was usedepEnrich  was usedrf.gov/) ,28 was eThe collected data was analyzed using Statistical Package for Social Sciences . Normality of the data was assessed using the Shapiro-Wilk test. Results were presented as mean and standard deviation (SD) or median and interquartile range (IQR). Differences between groups were compared using t-test or Mann Whitney’s unpaired test based on normality test. Statistical significance was assessed at the α < 0.05 levels for RT-qPCR.https://www.ncbi.nlm.nih.gov/bioproject) under the accession number PRJNA565573.All NGS sequencing data that support the findings of this study are available in the BioProject database of NCBI -tag strategy coupled to mass spectrometry (MS), as previously described . To this end, we carried out HA-Flag double-affinity immuno-purification from either nuclear soluble or nucleosome-enriched protein fractions  of HeLa The H3K9 KMTs G9A, GLP and SETDB1 co-purified robustly with MPP8 B. IntereIn addition to the H3K9 methylation machinery, the MPP8 complex contained also DNA repair and maintenance machineries , chromatin remodeling complexes , RNA maintenance and processing factors , these proteins belong to the transcription process and RNA modification .To get more insights on MPP8 functions within chromatin, we next sought to identify post-translational modifications (PTMs) on the histones co-purified with MPP8 by in-gel propionylation and trypsin digestion and Nano LC coupled to Ion Trapp mass spectrometer, as described in . RegardiNext, we decided to focus on the significance of the MPP8/SETDB1 interaction. To this end, we performed experiments in a more physiological cellular model, namely mouse embryonic stem cells (mESCs). Indeed, MPP8 is known to be highly abundant in ESCs, where SEDTB1 and H3K9 methylation play key roles in transcriptional silencing, in the absence of a complete establishment of DNA methylation before cell differentiation.Thus, to further support our findings, we sought to confirm the interactions revealed by TAP-tag/MS at the endogenous level by performing co-immunoprecipitation (co-IP) experiments from nuclear extracts of mESCs, followed by WB analyses. Our results showed that immunoprecipitation of MPP8 co-precipitated SETDB1 C. ConverTo search for MPP8/SETDB1 common regulated genomic regions, we performed endogenous MPP8 ChIP-seq in mESCs (from the 129S1 mouse strain) and analyzed an already published SETDB1 ChIP-seq in mESCs .Our data showed that the distribution of MPP8 binding sites on the genome is almost 60% on intergenic regions (including repeated elements), 37% on introns and 4% on exons A.Since MPP8 co-purified with the H3K9 KMT SETDB1, we next studied the extent of MPP8 co-localization with SETDB1. We found MPP8 co-localization on 6.5% binding sites with SETDB1 B. We fouAltogether, the ChIP-seq data suggest that MPP8 cooperate with SETDB1 in transposable elements and satellite DNA repeats silencing in mESCs.MPP8 KD or SETDB1 knockdown (KD). RNA-seq data were further analyzed by differential expression pattern of genes and transposable elements using the scrambled siRNA condition as a control on the whole dataset.In light of the co-immunoprecipitation and ChIP-seq results described above, showing a physical interaction between MPP8 and SETDB1 and genomic co-binding in mESCs, we further investigated the possible functional interplay between MPP8 and SETDB1. We asked whether MPP8 and SETDB1 co-regulate gene expression in mESCs. To further confirm the functional overlap between MPP8 and SETDB1, we performed RNA-seq analyses in HM1 ESCs after MPP8 or SETDB1 in HM1 ESCs showed a 70% decrease in mRNA level (not shown) of the specific targets and about the same decrease at the protein level   . InteresETDB1 KD . Gene onETDB1 KD .MPP8 KD -centromeres are also de-repressed upon SETDB1 KD  [MPP8 and at the same time endogenous depletion of SETDB1 in these ESCs, in parallel to the ad hoc controls. MPP8 KD showed a 40% decrease in MPP8 mRNA level when depletion of SETDB1 was induced, and 67% decrease without OTH treatment. However, even though the efficiency of the MPP8 KD was not very high, a trend toward significance showing upregulation of minor and major satellites and LINE repeats upon MPP8 KD was observed, in accordance with our RNA-Seq data. Of note, the consensus sequence of the primers we used in RT-qPCR could amplify many families of satellite and LINE repeats, not only the specific ones that are upregulated in the RNA-seq. Interestingly, upregulation of major and minor satellites as well as LINE elements is significantly higher upon concomitant MPP8 and SETDB1 loss-of-function  , in whicfunction C, suggesFinally, the analysis of the MPP8 and SETDB1 ChIP-seq-associated reads confirmed a good recruitment on the GSAT and SYNREP repeats D.Altogether, these data suggest that SETDB1 and MPP8 cooperate in satellite DNA repeats silencing in mESCs.SETDB1 loss-of-function induces early embryonic lethality between 3.5 and 5.5 dpc [We have combined biochemical and genomic strategies to get insights on the functions of the major H3K9 methylation reader MPP8 in mESCs. We first characterized the MPP8 complex partners and confirmed that MPP8 form complexes with many H3K9 methylation machinery members, including G9A and GLP H3K9 KMTs, as already known. Interestingly, we found that MPP8 interacts more robustly with the H3K9 KMT SETDB1 and its co-factor ATF7IP. We showed a physical and functional interaction between MPP8 and the major H3K9 KMT SETDB1 in mESCs.  5.5 dpc ,31,32.Our data showed that in addition to co-regulating coding genes, the association of the H3K9 KMT SETDB1 with the H3K9 methylation reader MPP8 extend to more genomic elements, including major and minor satellite DNA as well as some LINE elements.MPP8 gene is present only in vertebrates, reminiscent of some other proteins that are linked to the H3K9 methylation epigenetic mark such as TRIM28/KAP1 and ATF7IP (the SETDB1 cofactor), while some others are not that conserved, such as Heterochromatin Proteins HP1. MPP8 has been proposed to be involved in “position-effect variegation” (PEV)-like in the human and mouse genomes in the HUSH complex [The  complex . MPP8 ha complex . In vert complex , two proMPP8 is especially high in stem and germ cells and thus may play key roles in these cells chromatin features. As H3K9 methylation is mainly located in repeated elements, so do the main H3K9 KMTs and effector proteins that bind these motifs. Among these repetitive elements, the major and minor satellite DNA, the LTR-containing retroelements ERVs and the non-LTR-containing retrotransposons LINE, are epigenetically repressed by H3K9 methylation in ESCs [Expression of  in ESCs ,35, whicLysine methylation is not known to directly regulate chromatin structure, since addition of a methyl group to a lysine does not affect the charge, in contrast to acetylation for example . InsteadIn the mouse, the centromeric and pericentromeric regions are enriched by two conserved tandem repeats, which are the minor and major satellite DNA  ,39. ThesIn summary, our data suggest that SETDB1 and MPP8 cooperate in the cell cycle-dependent repression of the satellite DNA.


Polycomb group (PcG) proteins play critical roles in the epigenetic inheritance of cell fate. The Polycomb Repressive Complexes PRC1 and PRC2 catalyse distinct chromatin modifications to enforce gene silencing, but how transcriptional repression is propagated through mitotic cell divisions remains a key unresolved question. Using reversible tethering of PcG proteins to ectopic sites in mouse embryonic stem cells, here we show that PRC1 can trigger transcriptional repression and Polycomb-dependent chromatin modifications. We find that canonical PRC1 (cPRC1), but not variant PRC1, maintains gene silencing through cell division upon reversal of tethering. Propagation of gene repression is sustained by cis-acting histone modifications, PRC2-mediated H3K27me3 and cPRC1-mediated H2AK119ub1, promoting a sequence-independent feedback mechanism for PcG protein recruitment. Thus, the distinct PRC1 complexes present in vertebrates can differentially regulate epigenetic maintenance of gene silencing, potentially enabling dynamic heritable responses to complex stimuli. Our findings reveal how PcG repression is potentially inherited in vertebrates. Polycomb Repressive Complexes PRC1 and PRC2 catalyse distinct chromatin modifications to promote gene silencing. Here the authors use reversible tethering of Polycomb proteins to ectopic sites in mouse ESCs and find that canonical but not variant PRC1 can trigger sequence-independent propagation of Polycomb-mediated transcriptional repression. PcG proteins assemble into distinct multi-subunit complexes with inherent catalytic and non-catalytic activities. Among the two major families, Polycomb Repressive Complex 1 (PRC1) catalyzes monoubiquitination of lysine 119 on histone H2A (H2AK119ub1) and has the capacity to condense nucleosomes4 whereas PRC2 is responsible for mono-, di- and trimethylation of lysine 27 of histone H3(H3K27me2/3)5. While these activities are intimately linked to forming and maintaining repressive chromatin domains, the sequence of molecular events underpinning epigenetic repression remain poorly understood8.Epigenetic mechanisms support heritable transmission of differential gene expression patterns, stabilizing diverse cell types in metazoans. Silencing of key developmental genes by Polycomb group (PcG) proteins is arguably the premier paradigm for epigenetic regulation of cell fate inheritance9. This interaction is critical for cPRC1 recruitment to PRC2 target genes and transcriptional silencing11. Transmission of parental H3K27me3-marked nucleosomes to daughter strands could potentially serve as a cis-acting epigenetic signal for propagating Polycomb recruitment and gene repression through DNA replication and cell division14. However, the role of this histone mark as a carrier of epigenetic information remains controversial as DNA sequence elements contribute to PcG protein targeting in mammals19 and are continuously required for long-term heritable gene silencing in Drosophila21. Variant PRC1 (vPRC1) complexes, which harbor Rybp (Ring1B and Yy1 binding protein), or its homolog Yaf2, are recruited to chromatin independently of H3K27me323. vPRC1 exclusive targets are only moderately repressed24, suggesting distinct modes of transcriptional regulation compared to the concerted action of cPRC1 and PRC2. How the different PcG complexes and their chromatin-modifying activities achieve and transmit heritable gene silencing in vertebrates remains unresolved. However, the inability of vPRC1 to interact with H3K27me3 raises the prospect of alternative epigenetic mechanisms.In vertebrates, the PRC1 family has diversified into many heterogeneous complexes that can be broadly classified by the presence or absence of Cbx (chromobox-containing protein) subunits. In canonical PRC1 (cPRC1), Cbx confers the ability to bind H3K27me3cis-acting histone modifications promote a feedback mechanism for heritable cPRC1 targeting. Together, our findings provide insight into the mechanism of inheritance of Polycomb-dependent repression revealing fundamental differences in the contributions of canonical and vPRC1 complexes.Here, we use reversible tethering of Cbx7 and Rybp at ectopic loci in mouse embryonic stem cells (mESCs) to compare the capacity of cPRC1 and vPRC1 in formation and inheritance of repressive chromatin domains. Each PcG protein nucleates a distinct functional PRC1 complex that catalyzes repressive chromatin modifications and triggers transcriptional gene silencing. However, after release only Cbx7-initiated repressive chromatin can be maintained through genome replication and cell divisions. We show that sequence-independent propagation of gene silencing requires H3K27me3 and H2AK119ub1 arguing that OFF system. We generated two mESC lines that express a distinct PRC1 core subunit fused to a FLAG-Tet repressor domain (TetR). TetR DNA binding domain fusions bind to TetO sites, but this sequence-dependent recruitment is abrogated by addition of Doxycycline (Dox). The cPRC1-TetO line constitutively expresses FLAG-TetR-Cbx7 (TetR-Cbx7), a member of cPRC1. In contrast, the vPRC-TetO line constitutively expresses FLAG-TetR-Rybp (TetR-Rybp), a member of vPRC1  sites via the TetRC1 Fig. . This co29. Further, while tethering of Cbx7 or Rybp conferred distinct assemblies of cPRC1 or vPRC1, respectively, both cases resulted in Suz12 binding and H3K27me3, consistent with a role of H2AK119ub1 in signalling for PRC2 recruitment31.First, we examined if recruitment of different core subunits to an integrated landing site in the genome would direct the assembly of distinct PRC1 complexes and initiate silencing of an adjacent active reporter gene. Western blot analysis of immunoprecipitation using FLAG antibody revealed that TetR-Cbx7 and TetR-Rybp interact with the common catalytic subunit Ring1B. Moreover, TetR-Cbx7, but not TetR-Rybp, interacts with Phc1 suggesting the formation of distinct PRC1 complexes in solution , Ring1B , Rybp (vPRC1), or Suz12 (PRC2), and confirmed protein loss by Western blot  served as control. As expected, the initiation of GFP reporter silencing was lost in Cbx7 LOF cells, consistent with loss of TetR-Cbx7 expression  alleles in genes encoding different PRC1 and PRC2 components. We engineered cPRC1-TetO mESCs stably expressing Cas9 and validated sgRNAs targeting ion Fig. . In contive Fig. , similaring Fig. . In thesing Fig. , suggesting Fig.  suggestiSuz12 revealed that functional PRC2 was required to maintain, but not initiate, repression , which blocks catalytic activity dose-dependently without affecting the overall integrity of the PRC2 complexcis Fig. .9. To determine if this interaction is involved in maintenance of reporter gene repression, we transduced TetO-mESCs with a TetR-Cbx7 mutant encoding a LOF amino acid substitution in the aromatic cage responsible for binding methylated histone (Cbx7wt/TetR-Cbx7W35A)9. In addition, to discriminate the contribution of the endogenous wild-type allele, we expressed the TetR-Cbx7W35A mutant in TetO-mESCs with LOF mutation in the endogenous Cbx7 gene . However, similar to the reduction of endogenous protein, we did not observe additional expression of untagged Cbx7 in cPRC1-mESCs.Unexpectedly, both wild-type and Cbx7Dox Fig. . These dDox Fig. . To test36. TetR-Cbx7 fused to the Auxin-inducible degron (TetR-AID-Cbx7) and F-box protein TIR1 were transduced into TetO-mESCs as well as Cbx7KO TetO-mESCs, and clones with high TIR1 expression were isolated , which selectively binds to Cbx4/7 and disrupts the interaction with methylated histonesing Fig. . In the ing Fig. , in agre38. Indeed, Jarid2, an auxiliary component of PRC2, was recently shown to bind H2AK119ub1, the modification generated by PRC132. H2AK119ub1 might also contribute to silencing of gene expression7. To investigate the role of H2AK119ub1 in initiation and propagation of cPRC1-mediated gene repression, we ectopically expressed Bap1 together with a truncated version of Asxl1 (1–479 aa) to generate a hyperactive Polycomb Repressive-Deubiquitinase complex (PR-DUB) in cPRC1-TetO mESCs39  within DNA is controversial. Similarly, the emerging contribution of unmethylated CpG islands in directing PRC1 and PRC2 to target genes42 challenges the model of sequence-independent targeting mechanisms involved in inheritance of Polycomb-dependent gene repression in vertebrates. To address these challenging questions in basic epigenetics research, we have taken a reductionist approach enabling reversible, sequence-specific initiation of cPRC1- and vPRC1-dependent chromatin modifications at a synthetic reporter locus in mouse ES cells and evaluated their capacity to self-propagate through cycles of DNA replication and cell divisions in the absence of the initial stimulus. Our results suggest that in vertebrates Polycomb-repressive domains can be propagated by a selective feedback mechanism between cPRC1 and PRC2 which is sustained by cis-acting histone modifications . We find that propagation of Cbx7-initiated repression involves H3K27me3 binding which can be abrogated by genetic or chemical PRC2 inactivation or by blocking of CBX methyl-lysine recognition domain Fig. . Togethecis-acting histone modifications arguing that ectopic, reversible Cbx7 tethering triggers a physiological sequence-independent feedback mechanism for PcG protein recruitment in mESCs. Hence, despite the synthetic nature of establishment, our findings provide proof-of-principle and reveal a potential mechanism of heritable Polycomb-dependent repression in vertebrates.Interestingly, our reductionist system reveals that propagation of cPRC1-dependent repression is sensitive to cellular Cbx7 abundance. In mESCs, endogenous levels of Cbx7 promoted only limited maintenance of gene silencing, yet this was significantly enhanced by additional ectopic expression. Elevated Cbx7 levels may favor cPRC1 assembly promoting maintenance of target-gene repression through enhanced H3K27me3 interaction. To this extent, it remains to be shown if propagation of Polycomb-dependent silencing is also enhanced in cell-types with high endogenous expression of Cbx7 or its Polycomb paralogs. Nevertheless, we find that silencing was sustained by cPRC1 and PRC2 interactions through 14, our results suggest that in the context of transcriptional antagonism, self-reinforcement of H3K27me3 requires additional feedback by CBX methyl-lysine recognition dependent cPRC1 activity, ensuring robust repression and installation of H2AK119ub1 to promote further PRC2 recruitment. Similar to its canonical counterpart, repressive chromatin-modifying activities of vPRC1 can induce gene silencing. However, without the ability to “read” H3K27me3, vPRC1 may not contribute to epigenetic propagation of repression  co-transfection of the desired construct and two packaging vectors VSV-G (Addgene #8454) and psPAX2 (Addgene #12260) in Lenti X 293T cells (Takara #632180). After 48–72 h, the virus was collected. mESCs were then transduced with the virus for 48 h in the presence of 8 µg/ml polybrene .43. TetO mESCs were cultivated without feeders in high-glucose-DMEM supplemented with 13.5% fetal bovine serum (Sigma), 10 mM HEPES pH 7.4, 2 mM GlutaMAX (Gibco), 1 mM sodium pyruvate (Sigma), 100 U penicillin/ml (Sigma), 0.1 mg streptomycin/ml (Sigma), 1× non-essential amino acids (Sigma), 50 µM beta-mercaptoethanol (Gibco) and recombinant LIF . TetO-mESCs with BFP and GFP reporters were generated by recombinase-mediated cassette exchange introducing the reporter DNA YR06  to mES cell culture medium.All mESCs used in this study were derived from haploid mESCs available at Haplobank repository2 prior to FACS. Selection of transgene expression by Thy 1.1 required surface staining with a Thy1.1 specific antibody. After incubation in PBS containing 1 % FBS with Fc-blocking antibody at 1:500 (Affymetrix eBioscience Anti-Mouse CD16/CD32 Purified) for 5 min at RT, mESCs were treated with Thy 1.1 antibody (Affymetrix eBioscience Anti-Mouse/Rat CD90.1 (thy-1.1) APC-eFluor 780) at 1:750 for 30 min. For the Flow cytometry-based strategy for the isolation and of wild-type and CRISPR mutant cPRC1- and vPRC1-TetO-mESCs, please see Supplementary Fig. All flow cytometry analyses were conducted on a LSR Fortessa (BD Biosciences) using BD FACS Diva or FlowJo software. For fluorescent cell sorting a FACS ARIA III (BD Biosciences) was used. Isolation of haploid mESCs entailed incubation with 20 µg/ml Hoechst 33342 (Thermo Scientific Fisher) for 30 min at 37 °C and 5 % CO6 mESCs were trypsinized for 6–8 min prior to quenching with FBS containing ES cell medium. 25 × 106 mES cells were collected, washed in once in 1× PBS and crosslinked with formaldehyde at a final concentration of 1% for 7 min. The crosslinking was stopped on ice and with glycine at final 0.125 M concentration. The crosslinked cells were pelleted by centrifugation for 5 min at 1200 × g at 4 °C. Nuclei were prepared by washes with NP-Rinse buffer 1  followed by NP-Rinse buffer 2 . Afterwards the cells were prepared for shearing by sonication by two washes with Covaris shearing buffer  and resuspension of the nuclei in 0.9 mL Covaris shearing buffer (with 1 × protease inhibitors complete mini (Roche)). The nuclei were sonicated for 15 min  in 1 ml Covaris glass cap tubes using a Covaris E220 High Performance Focused Ultrasonicator. Input samples were prepared from 25 µL sonicated lysate. Therefore, chromatin was RNase A and Proteinase K digested and crosslink reversed overnight at 65 °C. DNA was then precipitated and shearing of DNA was confirmed to be between 500 and 1000 bp by agarose gel electrophoresis. Crude chromatin lysate was further processed by spinning at 20,000 × g at 4 °C for 15 min and supernatant used for ChIP. An equivalent of 50 µg DNA was incubated overnight in 1× IP buffer  with following antibodies at 4 °C on a rotating wheel: 0.5 μl H3K27me3 , 3 μl Ring1B , 1.5 μl Suz12 , 1.5 μl H3K4me3 , 7.5 μl Mel18 , 2 μl Cbx7 , 1.5 μl RYBP , 1.5 μl FLAG , 1.5 μl H3K27ac , 1.5 μl H2AK119ub , 7.5 μl Gal4 . The overnight IPs were incubated with BSA-preblocked Protein G coupled Dynabeads (Thermo Fisher Scientific) for more than 6 h at 4 °C on a rotating wheel. IPs were subsequently washed 5× with 1× IP buffer , 3× with DOC buffer  and 1× with TE (+50 mM NaCl). The DNA was then eluted 2× with 150 µL Elution buffer  for 20 min each at 65 °C. The eluate was treated with RNase A and Proteinase K and crosslink reversed overnight at 65 °C. The IP DNA was PCIA extracted and precipitated and quantified using qPCR on a CFX Connect Real-Time PCR Detection System (Biorad). qPCR primers are listed in Supplementary Table For Chromatin Immunoprecipitation, 30–50 × 106 mESCs was obtained by lysis in Buffer A  followed by collection in RIPA buffer . Nuclear extracts were homogenized by sonication in a Diagenode Bioruptor and concentration was determined by Bradford assay (Biorad). 20 µg/lane total protein was run on Novex Life Technology NuPAGE 4–12% Bis-Tris gels in Invitrogen NuPAGE MES SDS Running Buffer and transferred on a Merck Chemicals Immobilon-P Membrane (PVDF 45 µm). The membrane was blocked  and incubated in 5% non-fat dry milk in 1× PBS and 0.1% Tween 20 with the primary antibodies as listed in Supplementary Table Nuclear extract from 10 × 106 mESCs was obtained by lysis in 500 µl Buffer B . Lysate was homogenized by sonication in a Diagenode Bioruptor followed by rotation for 3 h at 4 °C. After 30 min centrifugation at 4 °C protein concentration of the lysate was determined by Bradford assay (Biorad). In parallel, 30 µl Protein G coupled Dynabeads (Thermo Fisher Scientific) were prepared for each IP reaction as follows: 3x wash in Buffer B, incubation with 1.5 µg FLAG antibody  for 3 h at 4 °C, 1× wash in Buffer B and finally resuspension in 30 µl of Buffer B. For each IP, 30 µl of pre-bound Dynabeads were incubated with 3 mg protein extract in a final volume of 500 µl overnight at 4 °C. Finally, beads were washed four times with Buffer B and proteins were eluted at 95 °C in SDS sample buffer and analyzed by Western blots.Whole cell protein extract from 45 × 10Cbx7 gene and LOF mutations of endogenous PcG genes in cPRC1-TetO mESCs were obtained by CRISPR/Cas9 technology. CRISPR guide RNAs were designed using the online tool of the Zhang lab  and cloned in modified lentiviral CRISPR/Cas9 expression vectors expressing the gRNAs  with following chemical inhibitors: Ezh2 inhibitor GSK126 , increasing concentrations of negative control compound UNC4219, Cbx4/7 antagonist UNC3866 alone or in combination with 4 µM GSK12637. Dilutions of UNC3866 and UNC4219 were prepared in DMSO.4 × 105 respective mESCs were plated in the beginning. After 24, 48, and 72 h mESCs were collected and stained with trypan blue for counting . Cell counts were performed in duplicates.1 × 10KO TetO-mESCs were transduced with DB52 and DB53 and clones with high TIR1 and TetR-AID-Cbx7 expression were isolated. Parental TetO-mESCs were transduced with DB53 and DB64 and clones with high TIR1 and TetR-AID-Rybp expression were isolated. All cells were treated for 72 h in the presence or absence of Doxycycline  alone or in combination with Indole-3-acetic acid sodium salt (Auxin) .Parental TetO-mESCs and Cbx7TetO-mESCs were transduced with YR111 and YR112 and mCherry-positive clones were isolated. For genetic reversal of TetR fusion protein binding, reporter cell clones expressing conditional TetR fusions were transduced with Cre recombinase using the mouse ES Cell Nucleofector Kit (Lonza) and Thy1.1-positive cells were sorted out after 24–36 h. Flow cytometry analysis of mCherry and GFP expression was carried out after 96 h. Both nuclear protein extracts and genomic DNA were collected reporter cells prior (mCherry-positive) and after (mCherry-negative) transfection with Cre recombinase.Further information on experimental design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data