In this study, we constructed an ATAC-seq platform suitable for filamentous fungi and generated ATAC-seq libraries of Aspergillus niger and Aspergillus oryzae grown under a variety of conditions.The identification of open chromatin regions and transcription factor binding sites (TFBs) is an important step in understanding the regulation of gene expression in diverse species. ATAC-seq is a technique used for such purpose by providing high-resolution measurements of chromatin accessibility revealed through integration of Tn5 transposase. However, the existence of cell walls in filamentous fungi and associated difficulty in purifying nuclei have precluded the routine application of this technique, leading to a lack of experimentally determined and computationally inferred data on the identity of genome-wide Aspergillus species, during different culture conditions, and among specific TF-deleted strains. The syntenic orthologues of accessible regions were responsible for the conservative functions across Aspergillus species, while regions differentially changed between culture conditions and TFs mutants drove differential gene expression programs. Importantly, we suggest criteria to determine TFBs through the analysis of unbalanced cleavage of distinct TF-bound DNA strands by Tn5 transposase. Based on this criterion, we constructed data libraries of the in vivo genomic footprint of A. niger under distinct conditions, and generated a database of novel transcription factor binding motifs through comparison of footprints in TF-deleted strains. Furthermore, we validated the novel TFBs in vivo through an artificial synthetic minimal promoter system.We applied the ATAC-seq assay for filamentous fungi to delineate the syntenic orthologue and differentially changed chromatin accessibility regions among different We characterized the chromatin accessibility regions of filamentous fungi species, and identified a complete TFBs map by ATAC-seq, which provides valuable data for future analyses of transcriptional regulation in filamentous fungi.The online version contains supplementary material available at 10.1186/s12915-021-01114-0. Aspergilli genus [Aspergillus section Nigri is the fungal genus with the most sequenced genomes, as genomes from 27 species are already publicly available [Saccharomyces cerevisiae, the knowledge of genome-wide regulatory mechanisms in Aspergilli is lagging. Transcription factors (TFs) are key regulators of biological processes that function by binding to transcriptional regulatory regions to control the expression of target genes. The cis-regulatory elements (CREs) related to TF binding play pivotal roles in the regulation of gene expression, and each TF recognizes a collection of similar DNA sequences, known as binding site motifs [Aspergillus genomes is an important step in understanding the regulatory functions of TF binding and gene expression. Analysis of genome sequences has revealed an average of 600 putative transcription factors in each Aspergillus fungus genome [Aspergillus genus have only been identified and not been studied further [Aspergillus genome have not been experimentally determined or computationally inferred, and the sites remain unknown.There have been 339 species identified in the li genus , and thevailable , 3, 4. Gvailable , 6. Howee motifs . TherefoAspergillus TFs or tagged target proteins for the more than 600 TFs in Aspergillus has prevented the widespread application of this method in Aspergillus [Aspergillus TFs, including CrzA [Aspergillus fumigatus; WetA of Aspergillus nidulans [Neurospora crassa [Fusarium graminearum [MoCRZ1 of Magnaporthe oryzae [A. nidulans [Aspergillus oryzae could not be effectively replicated [The gold-standard method for identifying in vivo CREs for TFs of interest is chromatin immunoprecipitation DNA sequencing (ChIP-seq) . Howeverergillus . So far,ing CrzA , SrbA [1ing CrzA , MetR [1ing CrzA , and Atring CrzA  of Aspernidulans ; CRE-1 oa crassa ; Tri6 ofminearum ; MoCRZ1 e oryzae  and somenidulans , 21. Thenidulans , 23. Thenidulans . For thecis-regulatory regions and DNA footprints in humans [Drosophila [Caenorhabditis elegans [Arabidopsis thaliana [S. cerevisiae [Aspergillus species, the existence of cell walls and the purification of nuclei preparation prevented the routine application of this technique. To overcome this obstacle, we performed an ATAC-seq assay for Aspergilli by protoplast preparation under cultivation conditions. We combined ATAC-seq and RNA-seq of different Aspergillus species and TF mutants to profile chromatin accessibility and identify gene regulatory elements in vivo on a genome-wide scale. Furthermore, we characterized the identified CREs in vivo by the synthetic minimal promoter driving expression of the reporter gene. Collectively, this study is an important step towards the meticulous analysis of industrial microbial transcriptional regulatory networks and provides valuable resource for future research aimed at characterizing or using gene regulatory elements.Assay for transposase accessible chromatin sequencing (ATAC-seq) is a recently developed technique used to identify accessible regions and DNA footprints , 26. Tn5n humans , mice [2n humans , zebrafin humans , Drosophosophila , Caenorh elegans , Arabidothaliana , S. cererevisiae , and so Aspergillus species by adding a step that released native nuclei by detergent lysis of protoplasts prior to the transposition step . After Tn5 transposition, PCR and electrophoresis were performed to detect the discrete nucleic acid bands  in A. niger CBS513.88 and SH2 ATAC-seq data sets on a genome scale revealed that they were similar to each other, and the Tn5 integration regions of naked genomic DNA were uniformly distributed along the entire chromosome . In total, 1641 of the amyR-specific peaks, 1156 of the prtT-specific peaks, 773 of the cpcA-specific peaks, 1301 of the pacC-specific peaks, and 1305 of the creA-specific peaks in the promoter regions exhibited significantly higher accessibility (FDR < 0.05) than those in the corresponding TF-deleted strains . A total of 161 specific peaks were enriched, of which 97 (60.24%) peaks could be mapped with delprtT and 112 (69.57%) peaks with WT Fig. c. The coAspergillus species are frequently silent or inactive under normal laboratory conditions due to a tendency to be located in subtelomeric regions with a high degree of heterochromatin condition; however, these genes can be activated by changing the chromosomal state of the SM gene clusters from heterochromatin to euchromatin [Aspergilli. Deletion of LaeA in filamentous fungi decreased the virulence of the strains and the production of secondary metabolites. And it has been reported that deletion or overexpression of LaeA could be used to explore numerous secondary metabolite clusters [Aspergilli, we constructed ATAC-seq libraries of dellaeA and OElaeA and identified the ATAC-seq peaks with significantly changed accessibility (FDR < 0.05) in dellaeA-vs-WT (4725 DAPs) and OElaeA-vs-WT (5572 DAPs).  [A. oryzae OElaeA and dellaeA mutants significantly changed accessibility (FDR < 0.05) to induce significant regulation of 42 and 32 SM biosynthetic genes, respectively  to induce significant regulation of the corresponding SM backbone genes in OElaeA and dellaeA mutants, which contained 7 NRPSs, 4 PKSs, and 1 DMAT  was in the region of high chromatin accessibility, while the coactivator aflJ (AO090026000015) became highly expressed following the overexpression of laeA. The other sequences from AO090026000020 to AO090026000031 were in inactive chromatin regions in which no ATAC-seq peaks were identified, and biosynthesis genes had no expression or the lowest level of expression. The AF biosynthesis pathway components were located in a laeA-dependent SM biosynthetic gene cluster. Taken together, the reason for the lack of AF biosynthesis in A. oryzae might be inactive chromatin regions around the AF biosynthesis pathway.The biosynthetic gene clusters of secondary metabolites (SMs) in hromatin . LaeA haclusters –39, althclusters . To inveeA-vs-WT 725 DAPs  (SMURF) . The chreA-vs-WT 725 DAPs eA-vs-WT 725 DAPs wellington_footprints.py” function of the pyDNase package [A. niger genome from 7297 and 7697 ATAC-seq peaks of CBS513.88 and SH2, respectively  were enriched in GO categories “structural constituent of the ribosome” and “translation”  promoter of A. niger was chosen as the core element due to the high-level expression of the amyB gene. The glucose oxidase goxC (An01g14740) was used as a reporter, the expression of which would be revealed by a colored colony. The repression under ER stress (RESS) element identified in our prior study [amyB core element, the ATAT sequence, and the AT-rich spacer was constructed   Fig. b. AlthouFurthermore, to investigate whether instances of TF binding drove the expression of target genes, we used TF binding motif sites in ATAC-seq footprints combined with RNA-seq data for the changes in gene expression between the SH2 cultured in MPY and the corresponding TF-deleted strains Fig. a. The exagdB), An03g06550 (glaA), and An05g02100 (amyA). These AmyR binding motifs drove the expression of the reporter gene, resulting in colored colonies. Three footprints containing the PrtT binding motif in the promoter of peptidase genes, including An04g00410 (dipeptidyl peptidase III), An06g00190 (Sedolisin family secreted protease), and An08g00430 (serine-type carboxypeptidase), also drove the expression of the reporter gene. In addition, footprints containing CCAAT box or AreA binding motifs can also function as transcription activator  as a positive control  is the transcriptional regulator that mediates carbon catabolite repression [glaA (An03g06550), amyA (An12g06930), and amyR (An04g06910) were able to upregulate the expression of the reporter gene  and a low proportion at intergenic regions (~ 5%), which was contrary to humans [A. niger genome (35 Mb) [A. niger.The chromatin accessibility regions of o humans , Arabidoo humans , and tom (35 Mb) . TherefoPrior works found that the accessible chromatin regions were positively correlated with gene expression changes of the nearest target genes , 32, 49.Aspergillus species [A. niger and A. oryzae species, we discovered that syntenic orthologues of 1564 accessible regions across A. niger and A. oryzae drive the expression of a collection of target genes that are significantly enriched in housekeeping genes functioning in ribosomes, translation, and energy. The synteny of open chromatin regions between different species may be due to the conservation of noncoding regions [Aspergillus species, which act as protein expression cell factories, exhibit the same potential functional elements in protein synthesis regulation.Comparative genomics focuses on the comparison of DNA coding regions between different species, revealing the eukaryotic genomic evolution of different  species . In comp regions , indicatcis-regulatory DNA elements [The accessible chromatin regions identified by ATAC-seq are particularly valuable for the identification of elements , 48, 49.elements , 42, 52.elements  developeA. niger CBS513.88 and SH2  and basic helix-loop-helix (motif TCACGTGATC) families  and cpcA (amino acid starvation). The function of other bZip TFs are associated with amino acid starvation (jlbA); oxidative stress ; and sulfur metabolism (cys-3/metR), and they have mainly been characterized in homologous species, such as A. nidulans [A. fumigatus [A. oryzae [Neurospora crassa [The bZip family of TFs that have been functionally analyzed in nidulans –55, A. fumigatus , and A. . oryzae , 57. Thea crassa  reveals sclR/srbB, anbH1, srbA, palcA, INO4, and devR, have not been well characterized in A. niger. However, in other species, the bHLH TFs have been postulated to be involved in hyphae growth and differentiation as well as specific metabolic pathways [A. nidulans genome sequence analysis [A. niger have more unknown functions, and further characterization of bHLH TFs is urgently needed. The bHLH TFs recognize a consensus core element named the E-box (5′-CAVVTG-3′), and the G-box (5′-CACGTG-3′) is the most common form [P value compared to all de novo previously unidentified TF binding motifs. GO functional analysis showed that this new motif CTGCCTGAGGCA drives the expression of target genes, and the GO molecular function categories include the cellular components of “ribosome” and “mitochondrial inner membrane;” the biological processes are related to “translation” and “metabolism.”The 10 TFs in the bHLH family, including homologous genes of pathways , 59. Themon form , 61. TheA. niger ATAC-seq-predicted binding sites containing TFBs in the absence of other omics data . Our de novo motifs identified from enriched from ATAC-seq footprints were able to drive the expression of the targeted gene in vivo.We constructed a minimal synthetic promoter suitable for filamentous fungi that was based on the yeast minimal promoter . We usedA. niger wild-type strain and its TF-deleted strains. Footprints for these known TF binding motifs identified by ATAC-seq data were also verified as functional TFBs in vivo. Compared with A. niger CBS513.88, the enrichment P value of the TF motif in A. niger SH2 was significantly higher; the most differential values were observed for the CCAAT box, which represents a gene transcriptional activation domain [A. niger SH2 is a more suitable host for exogenous protein expression [creA, amyR, pacC, and prtT revealed that these transcription factors are involved in decentralized functions and do not cluster in categories directly related to TF function; this is even true for the pathway-specific transcription factor PrtT, which has a variety of functions that are not directly related to TF function that is clustered. Such results are ubiquitous in other studies using RNA-seq to study the function of transcription factors [. Our results contradict the fact that CreA is the repressor for CCR. It can only be speculated that CreA may play an unknown activation role in gene transcriptional regulation or that the predicted binding sites contain an activated binding motif for other unknown transcription factors.We further determined the enrichment of known TF binding motifs from ATAC-seq footprints by comparing ATAC-seq data from the n domain , and then domain . This supression  at the T factors , 63, whi factors  or ChIP- factors , 13. The factors , 64, 65. factors , so that factors . (iii) Tcis-acting elements provide a large number of basic modules for artificially synthesized promoters, and our ATAC-seq data set will provide a rich resource for the identification of functional TFs in A. niger. In the future, ATAC-seq may be effectively applied to study other filamentous fungi whose genomes and transcriptomes are available but whose regulatory mechanisms have not yet been explored.These data representing the ATAC-seq landscape of TF footprints will help in the exploration of genome-wide regulation of genes active in filamentous fungi, and the data will help to discover new regulatory factors and their potential sites of action. We demonstrated the usefulness of this resource by testing 25 noncoding DNA sites with predicted TF binding motifs driving reporter gene expression in the host strain. Future experiments will be required to validate the functional activity of more noncoding sites and investigate the role of specific TF footprints in controlling gene expression. The sites with E. coli Mach 1 T1  was used for molecular cloning and was cultured in Luria-Bertani (LB) medium  with 100 μg/mL ampicillin at 37 °C (both solid and liquid) while shaking at 200 rpm. Conidial Aspergillus niger CBS513.88 and Aspergillus oryzae niaD300 were cultured in PDA medium for spore germination, and they were cultured in DPY  medium  for protoplast preparation. Aconidial Aspergillus niger SH2 (ΔkuΔpyrG) was used as the host for the knockout of transcription factors and was cultured in modified liquid Czapek-Dox medium (CD) containing the following substances to support mycelial growth: 2% glucose, 0.3% NaNO3, 0.1% KH2PO4, 0.05% MgSO4·7H2O, 0.2% KCl, and 0.01% FeSO4·7H2O. When the OD reached 2.0, 1 ml of mycelia was inoculated into 100 ml of DPY medium and grown in a thermostatic shaker at 250 rpm and 30 °C for 40 h. Mycelia were harvested for protoplast preparation. To study the influence of carbon sources on the chromatin accessibility, the glucose in DPY was replaced with 2% maltose (MPY) [A. niger HL-1 [goxC (An01g14740). Solid CD (2% agarose) with 1% O-dianisidine (dissolved in methanol), 18% glucose, and 90 U/mL horseradish peroxidase was used to assess the color reaction following goxC expression.The specific genotypes of strains used in this study are shown in Additional file se (MPY)  or straise (MPY) . A. nigeger HL-1  was usedA. niger strain CBS513.88, SH2 (including TF deletion strains and different culture conditions) and A. oryzae niaD300 (including laeA deletion and overexpression mutants) were grown to mid-log phase in DPY medium or conditional induction medium. Then, 1 g of mycelia per library was harvested using miracloth, and they were then rinsed with cold water and 0.8 M NaCl. Protoplasts were prepared by incubating mycelial samples in enzymatic lysis buffer composed of 0.8 M NaCl, 2% cellulase, 1% helicase, 1% lyticase, and 0.5% lysozyme, which were dissolved in the corresponding medium and were then filtered with miracloth and washed with cold STC buffer . Subsequently, 5 × 104 protoplasts (cells) were incubated with 200 μl of lysis buffer  IGEPAL CA-630, 1 mM PMSF and 1xPIC (EDTA free)) for 10 min at 4 °C, washed with lysis buffer (without IGEPAL CA-630), and then incubated with 5 μl of Tn5 Transposase of TTE Mix V50 in 45 μL of 1× TTBL buffer  at 37 °C for 30 min. PCR was subsequently performed as previously described [A. niger CBS513.88 naked genome DNA), 5 ng of genomic DNA was used for the Tn5 transposase reaction. All the ATAC-seq data were submitted to the NCBI The escribed . LibraricreA [amyR [cpcA [pacC [prtT [laeA [Aspergillus genome database (www.aspgd.com), and homologous arms for gene knockout were designed based on the 1000-bp sequence flanking the CDS region of each gene, which were then amplified with primer sets listed in Additional file pyrG from A. nidulans was used as a screening marker for TF knockout. The upstream and downstream homologous arms of each TF obtained by PCR amplification were introduced along with the pyrG marker into a pMD20 T-Vector  by NEBuilder , to obtain TF knockout vectors . The knockout cassettes that were linearized with XbaI, EcoRI, ApaI, EcoRI, EcoRI, and BamHI were introduced into A. niger SH2 and A. oryzae niaD300 by PEG-mediated protoplast transformation. In brief, protoplasts were prepared as the description in ATAC-seq library preparation. Protoplasts were resuspended in a certain amount of STC, and transformation system was made up of 100 μL linearized plasmid, 160 μL protoplasts, and 60 μL PEG. The mixture was incubated on the ice for 30 min, and then added another 1.5 mL PEG for 25 min at the room temperature. Finally, the mixture was pooled down on the hyperosmotic sucrose CD plate. After 5 days cultivated at 30 °C, transformants were obtained and identified. The cassettes for laeA overexpression digested with ApaI were transformed into A. oryzae niaD300 to yield the OElaeA strain. The TF knockout mutants in which homologous integration occurred were analyzed by PCR amplification for upstream and downstream localization, and they were further validated by qRT-PCR  strain, in which the TF PrtT was drove by PglaA and labelled by 3 × FLAG tagging, for ChIP-seq analysis. Fungal conidia (106/mL) were incubated in 100 mL DPY media at 30 °C under shaking at 200 rpm for 40 h. The mycelia was harvested, dried with two layers of miracloth, and transferred into buffer A for cross-linking. Cross-linking was done according to the protocol of [To confirm the ATAC-seq data, we constructed PrtT-FLAG . Reverse transcription was performed with a PrimeScript RT-PCR Kit . Quantitative real-time PCR (qRT-PCR) was performed using an ABI 7500 Fast Real-Time PCR System to analyze TFs and the report gene Aspergillus genome (Ensembl/ASM285 for A. niger and Ensemble/ASM18445 for A. oryzae) using Bowtie2 with parameters “--trim5 5 --trim3 15” and other default parameters. All reads aligned to the + strand and the − strand were offset by ± 5 bp, respectively, due to the Tn5 transposase introducing two cuts that were separated by 9 bp [http://broadinstitute.github.io/picard/).After removing adaptors using Trimmomatic , 50 bp p by 9 bp . Mapped  by 9 bp . DuplicabamCoverage tool in deepTools2 with a bin size of 1 bp and with RPKM normalization. Heatmaps and average plots from the ATAC-seq data matrix were also generated using the “computeMatrix,” “plotHeatmap,” and “plotProfile” functions in the deepTools2 package [To visualize mapped reads, BAM format files were converted to bigwig format using the  package . Genome  package  and bigwannotatePeaks.pl tool of the HOMER program [Aspergillus niger CBS513.88 genome. Peaks that were 1 kb upstream of the TSS were associated with the nearest genes. These genes were then analyzed for overrepresented gene ontology and KEGG pathway using FungiFun 2.2.8 BETA (https://sbi.hki-jena.de/fungifun/) [Accessible regions and peaks of each sample were identified using MACS2  with the program  was usedngifun/) .To identify differentially mapped reads, we used Diffbind . We usedFootprints were identified with pyDNase  using thAspergillus promoter for functional verification of CREs in vivo  promoter of A. niger, which facilitates successful loading of the transcription initiation complex, thereby initiating transcription by RNA polymerase. To ensure that the TATA box can be successfully opened during the transcription process, we manually added 8 AT-enriched sequences in front of the TA box to reduce the bond energy of the DNA [goxC (An01g14740) was used as the reporter gene, which could catalyze the oxidation of D-glucose at carbon 1 into D-glucono-1, 5-lactone and hydrogen peroxide. Then the peroxidase catalyzes the decomposition of hydrogen peroxide while oxidizing O-anisidine, thus resulting in a red phenotype [pyrG was integrated before the footprints to separate the footprints from other genomic sequences, ensuring that transcription of the core sequence was not affected by other sequences. The footprints contained a transcription factor binding site (TFBS) that helped stabilize RNAP to enhance transcription efficiency. By constantly changing footprints and monitoring the transcription of downstream reporter genes, it was possible to identify whether the footprints containing the TFBs function in vivo. The 1 kb flanking sequence of the glucoamylase gene (glaA) acts as a homologous arm, and the aim was that the sequence successfully integrated into the glucoamylase gene locus, ensuring that all open reading frames were at the same position in the genome [XbaI and transformed into A. niger by PEG-mediated protoplast transformation.With reference to the yeast minimal promoter screening system , we desiTPI gene  was used the DNA . These eB An05g0200 promothenotype  (AdditioB An05g0200 promote genome . All thefindMotifsGenome.pl tool of the HOMER program to identify overrepresented transcription factor sites (transcription factor motifs). Using the annotatePeaks.pl tool of HOMER with the –m parameter, HOMER de novo motifs were then used to search the original set of sequences to identify all instances of motifs.ATAC-seq footprints that were identified from each sample were used to discover de novo transcription factor motifs. The boundaries of the start and stop coordinates of ATAC-seq footprints were lengthened by 10 bp upstream and downstream. We then used the seq2profile.pl tool of HOMER. The known motifs were then used to search the footprints of each sample to identify all instances of motifs using the annotatePeaks.pl tool of HOMER with the –m parameter.The known motif files in the HOMER format were created manually with the Additional file 1: Figure S1. Fragment length distribution of Tn5 transposase integration. Figure S2. qRT-PCR analysis of A. niger cultured in different condition. Figure S3. Enrichment of PrtT binding motif from the ChIP-seq data. Figure S4. Visually display of the PrtT binding site. Figure S5. Clustering analysis of ATAC-seq peaks for Aspergillus oryzae niaD300 and its laeA mutants. Figure S6. Comparison of ATAC-seq peaks and RNA-seq signal among A.oryzae niaD300 and laeA mutant. Figure S7. De novo motifs of SH2 TF-deficient strains. Figure S8. GO analysis of 3 de novo predicted over-represented TFBs targeting genes. Figure S9. The minimal promoter structure and the verification of its function. Figure S10. In vivo functional verification of AreA targeting sites. Figure S11. qRT-PCR verification of TF knockout strains of A.niger SH2 and A.oryzae niaD300.Additional file 2: Supplementary Table S1. Sequencing data quality and mapping rate analysis of the ATAC-seq samples.Additional file 3: Supplementary Table S2. Chromatin accessible regions (Peaks) of each sample identified by MACS2.Additional file 4: Supplementary Table S3. Syntenic orthologues of ATAC-seq peaks identified between A. niger CBS513.88 and A. oryzae niaD300.Additional file 5: Supplementary Table S4. Differential peaks analysis of A. niger and its mutants.Additional file 6: Supplementary Table S5. Differential peaks and SM cluster analysis of A. oryzae and its laeA mutants.Additional file 7: Supplementary Table S6. DNA footprints of A. niger wild-type strains and TF-deleted strains.Additional file 8: Supplementary Table S7. De novo TFBs of A. niger wild-type strains and TF-deleted strains with a P value threshold of 1E-50 by HOMER.Additional file 9: Supplementary Table S8. The physical position and gene function of DNA instances containing the TFBs mapped to the A. niger genome.Additional file 10: Supplementary Table S9. Motif instances of known TFs from footprints by comparing A. niger WT strains and the TF-deleted strains.Additional file 11: Supplementary Table S10. Genotype of strains used in this study.Additional file 12: Supplementary Table S11. Primers used in this studyAdditional file 13: Supplementary Table S12. FPKM value of all the A. niger RNA-seq samples.Additional file 14: Supplementary Table S13. Original data of all the figures and additional files.


Development is a complex process regulated both by genetic and epigenetic and environmental clues. Recently, long non-coding RNAs (lncRNAs) have emerged as key regulators of gene expression in several tissues including the brain. Altered expression of lncRNAs has been linked to several neurodegenerative, neurodevelopmental and mental disorders. The identification and characterization of lncRNAs that are deregulated or mutated in neurodevelopmental and mental health diseases are fundamental to understanding the complex transcriptional processes in brain function. Crucially, lncRNAs can be exploited as a novel target for treating neurological disorders. In our review, we first summarize the recent advances in our understanding of lncRNA functions in the context of cell biology and then discussing their association with selected neuronal development and neurological disorders. For a long time, scientists believed that functional genetic information was only contained in protein-coding genes. Proteins were considered the main protagonists in cellular functions, while RNAs were thought to be mere intermediaries between DNA and proteins .https://encodeproject.org, v117, accessed on 28 May 2021) . Th. Th20]. RNA-binding domains. Thanks to their ability to base pair with other RNAs, lncRNAs can recognize and bind mRNAs, miRNAs and other lncRNAs, modulating target levels and function;Protein-binding domains. Proteins are a major partner of lncRNAs, forming ribonucleoprotein complexes (RNPs) that act as chaperones, transport aids or effectors (including phase-separation seeding). This type of interaction involves conformational changes in the protein, RNA or both;DNA-binding domains. Currently, there is a lack of extensive evidence for direct and functional interaction between lncRNAs and DNA as well as a lack of a consensus regarding the role and function of these interactions. However, it is known that RNA–DNA hybrids or triplex structures can allow single strands of RNA to interact with DNA duplexes through pair–base interactions. These direct interactions can efficiently and selectively direct RNA signals to genomic loci through base-pairing interactions. However, such interactions can also expose the genome to deamination and damage;Conformational switch. LncRNAs can act as regulatory devices by allosterically coupling binding domains with the switching of structural conformations and thereby activating or suppressing linked functional domains.A significant part of non-coding transcripts is represented by lncRNAs, which are RNA transcripts longer than 200 nts. The biogenesis of lncRNAs resembles that of messenger RNAs (mRNAs). They are transcribed by polymerase II (Pol II) and can be polyadenylated, spliced and 5′-capped ,21,23. TSense lncRNAs, which overlap one or more exons of neighboring mRNAs on the same strand; antisense lncRNAs, which overlap one or more exons of neighboring mRNAs on the opposite strand; intronic lncRNAs, which are transcribed from introns of a second transcript (sometimes may represent pre-mRNA sequences);Promoter upstream lncRNAs, which are located upstream of a promoter; promoter-associated lncRNAs, which are close to the promoter;Intergenic lncRNAs, which lie within the genomic interval between two genes;Bidirectional lncRNAs, which have promoters in common with protein-encoding genes but are transcribed in the opposite direction; 3′UTR-associated lncRNAs, which are transcribed from a protein-coding gene’s 3′UTR region.LncRNAs can be classified based on their biogenesis, structure, localization or mechanism of action ,26,27. BAnother approach in the classification of lncRNAs is based on their subcellular localization, which can be linked to their function  or to tcis-acting lncRNAs, trans-acting lncRNAs  and competing endogenous lncRNAs, which share sequence and function similarities with mRNAs and compete with them for function . Th. ThGOMAFsplicing  [3,23,50molog 4) ,192,205. changes ,188,192.s miRNAs ,192,203.DISC1-AS lncRNA has been linked to SZ (DISC1 expression [DLG2AS (antisense to discs large homolog 2) dysregulation has also been found in SZ patients’ brains. Through the control of DLG2 gene expression (downregulated in the hippocampus of SZ patients), these lncRNAs impact brain development, long-term synaptic potentiation and axonal guidance signaling [The ed to SZ , as it npression ,188,192.LncRNAs associated with the nuclear factor-κB (NF-κB) protein family have also been linked with SZ pathophysiology. This protein family has an important role in neurodevelopment, interacting with crucial genes/pathways for neurogenesis such as Notch, Shh and Wnt, and it also regulates inflammatory response . In SZ pLncRNAs regulate several processes during brain development, neurogenesis, cell fate decision, maturation and differentiation  and are


Lactate is an end product of glycolysis. As a critical energy source for mitochondrial respiration, lactate also acts as a precursor of gluconeogenesis and a signaling molecule. We briefly summarize emerging concepts regarding lactate metabolism, such as the lactate shuttle, lactate homeostasis, and lactate-microenvironment interaction. Accumulating evidence indicates that lactate-mediated reprogramming of immune cells and enhancement of cellular plasticity contribute to establishing disease-specific immunity status. However, the mechanisms by which changes in lactate states influence the establishment of diverse functional adaptive states are largely uncharacterized. Posttranslational histone modifications create a code that functions as a key sensor of metabolism and are responsible for transducing metabolic changes into stable gene expression patterns. In this review, we describe the recent advances in a novel lactate-induced histone modification, histone lysine lactylation. These observations support the idea that epigenetic reprogramming-linked lactate input is related to disease state outputs, such as cancer progression and drug resistance. Cell behavior is dynamically educated by metabolic flux-mediated adaptation to the microenvironment . Lactate+ have a crucial role in cellular plasticity , so-called epigenetic changes, which are often heritable and reversible, allowing fine regulation of cell identity . Therefoasticity , 5. Impoasticity , and theasticity .Here, the relationship between lactate metabolism and function , as wellvia cytosolic lactate dehydrogenases (LDHs) rather than entering the TCA cycle  cycle to be used in oxidative phosphorylation (OXPHOS). A total of 36 adenosine triphosphate (ATP) molecules per glucose molecule are produced by this process . HoweverCA cycle . LDH is CA cycle . In 1923via OXPHOS, prompting rapid ATP synthesis in the cytoplasm  (via hypoxia-inducible factor 1α (HIF-1α) in response to hypoxic conditions to facilitate exportation of lactate , G protein-coupled receptors  , and hyd, GPR81) . Mechani, GPR81) . And end, GPR81) . MCT4 is lactate . Via end lactate .via MCT2  Increased glucose uptake is determined by elevated expression as well as translocation of glucose transporters. 2) The expression and activity of glycolytic enzymes, especially LDHA, are induced by HIF-1α, c-MYC and p53 dysregulation. 3) Mitochondrial function is decreased primarily by dysregulated p53 expression. 4) Lactate generation, accumulation and secretion are increased because of the mass effect of accelerated glycolysis . 5) The ironment .Making space for the expansion of tumor growth and extracellular matrix (ECM) degradation, local tissue invasion, sustained angiogenesis, and migration are required .. For in+ T cells or modulating the CD4+ T cell phenotype towards Th17 cells during chronic inflammation might be harmful  production via nuclear pyruvate kinase M (PKM2)/signal transducer and activator of transcription 3 (STAT3) signaling. The measurement of synovial lactate is a rapid diagnostic approach used to verify patients with septic arthritis   and to aMacrophages, a heterogeneous cell population, act as scavengers, modulate the immune response and maintain tissue homeostasis . Macrophvia the stabilization of HIF-1α and a reduction in the level of the cofactor NAD+, which inhibits pADP-R synthesis  often exhibit proinflammatory and antitumor activities . Howeverynthesis . Next, uynthesis Figure 1Cellular plasticity is derived from the ability to respond and adapt to the environment , as demoSince the regulatory mechanism by which epigenetic control of transcription is strict, metabolic pathways are obviously modulated. For example, blocking glycolysis increases H3K4me3 and decreases H3K9me3 in the IL6 and TNFA gene promoters, thereby inhibiting the training of human monocytes . Next, tvia the regulation of acetyl-CoA, which is not only a metabolite but also a substrate of acetyltransferases .Lactate plays a significant role in epigenomic reprogramming, which has been shown directly in pancreatic ductal adenocarcinoma . Metabolin vitro requires HDAC3, and IL-4 and transforming growth factor (TGF)-β signaling are inhibited in the BMDMs of HDAC3 knockout mice (Lipopolysaccharide (LPS) is often used to evoke a proinflammatory response in macrophages. LPS tolerance is altered substantially under the modulation of epigenetic mechanisms at the molecular level. It is unclear whether the molecular mechanisms are involved in tolerance drivers; however, recruitment of the nuclear receptor corepressor (NCOR)-histone deacetylase 3 (HDAC3)-p50 suppressive compound to targeted genes in bone marrow-derived macrophages (BMDMs) is related to NF-κB . In factout mice .in vitro and in vivo assays have shown that lactate is an endogenous HDAC inhibitor that induces HDAC-dependent gene deregulation at concentrations that arise in nature  instead of lysine acetylation (Kac) was reduced by lactate inhibition. In addition, when LDH was genetically deleted, lysine lactylation was abolished  glucose supplementation; (2) the inhibitor rotenone, which promotes glycolysis; (3) hypoxia; and (4) M1-polarized macrophages. On the basis of these studies, a novel histone modification with special modulation of lactate is established and suggests that lysine lactylation is regulated by alterations in glucose metabolic dynamics of glucose and lactate levels.During M1 macrophage polarization, histone lactylation increases in a pattern closely correlated with time , which i-/- BMDMs in response to TLR binding (B cell adapter for PI3K (BCAP) functions as the upstream regulator of Toll-like receptors (TLRs) and is required for optimal glycolysis after microbial stimulation . In dext binding . The add binding .Indeed, to evaluate the functional purpose of lactylation, RNA sequencing was conducted, and there was notable enrichment of genes enhanced by lysine lactylation in wound healing, especially homeostasis genes, which are essential to maintain biological homeostasis and are related to M2-like macrophages. For instance, in M1 macrophages treated with exogenous lactate, lysine lactylation enrichment at the Arg1 promoter and increased gene expression were observed. Analogously, histone lactylation and Arg1 expression decreased because of the absence of LDHA in M1 macrophages.These data revealed that the produced lactate is necessary for proper histone lactylation that induces stimulation of gene expression, resulting in the promotion of an M2-like phenotype at later stages of M1 macrophage polarization, eventually maintaining homeostasis.Convincing evidence has indicated that upregulation of glycolysis in lung fibroblasts, smooth muscle cells and endothelial cells contributes to the progression of lung fibrosis , 83. In In somatic cells, a metabolic shift from OXPHOS to a state that depends on glycolytic flux during induced pluripotent stem cell (iPSC) processes has been observed , 86.Gli-like transcription factor 1 (Glis1), a member of the Krüppel-like zinc finger transcription factor subfamily, enables senescent cells to convert to pluripotent cells in cellular reprogramming by multilevel epigenetic and metabolic remodeling. At earlier stages, Glis1 shuts off somatic genes such as SET binding protein 1 (Setbp1) and Thy-1 cell surface antigen (Thy1) while turning on glycolysis genes. Owing to enhanced glycolytic flux, the levels of acetyl-CoA and lactate in cells increase, thus promoting acetylation  and lactylation  at the loci of pluripotency genes, mainly the Yamanaka factors POU class 5 homeobox 1 (Oct4), SRY-box transcription factor 2 (Sox2), Krüppel-like factor 4 (Klf4) and MYC proto-oncogene (c-Myc), to facilitate cellular reprogramming . Additiovia the expression of M2 genes, such as Arg1 , mitochondria (27%), and cytoplasm (25%)  .For instance, MAPK was identified to be lactylated at K60. Citrate synthase is a rate-limiting enzyme in the TCA cycle and was found to be lactylated at K401. At multiple sites of two eukaryotic translation initiation factor 5A (eIF5a), proteins were modified by lactate . The proOne caveat in interpreting the connections between lactate metabolism and epigenetic events is that metabolic pathways are interconnected and coordinately regulated .Studies in stem cells have identified a role for acetyl-CoA in maintaining the pluripotency program: it was shown that both H3K27Ac and H3K9Ac were enhanced by acetate and that these acetylation modifications were generally diminished during differentiation . MechaniIn the facilitation of pluripotency reprogramming by Glis1, a time-dependent correlation is observed between the increase in Glis1 expression and the alteration of acetylated and lactylated histones . ChIP-se+ Th1 cells demonstrated that glycolysis is important for acetyl-CoA levels during T cell differentiation  is largely responsible for the glycolytic phenotype in cancers . For insEvidence suggests that p300 is not only a histone acetyltransferase  but alsoOne critical question that is currently unanswered is how bulk changes in histone acetylation or lactylation are specifically targeted to defined gene programs. Insight into this topic will expand our understanding of the mechanisms that link lactate and acetyl-CoA fluctuations to specific cellular decisions .The discovery of lactylation introduces the intriguing possibility of a new window for the Warburg effect. Some possible biochemical links between lactate and lactylation have been proposed, including two metabolic mechanisms, lactyl-CoA is closely related to enzymatic lactylation, and lactyl-glutathione is involved in the acyl-transfer of non-enzymatic lactylation. Further, lactyl-CoA has been detected by liquid chromatography mass spectrometry in mammalian cells and tissues . ElucidaFurther investigation will clarify more details about how histone lactylation marks are written in a gene-specific manner and how they regulate transcription, as well as about the biochemical process that precisely regulates histone lactation, which may become an important future research topic .Because of the changing microenvironment, the main macrophage phenotype transition is a dynamic process . Mouse Bvia histone lactylation, and the mechanisms by which lactate fluctuation can control a specific gene set in a given tissue are unclear.In this context, understanding the precise relationship between the presence of lactate and histone lactylation, as well as other interconnected metabolite-epigenetic events, on a temporal scale requires further investigation. For instance, the mechanisms controlling the concentration of lactate in microdomains within the nucleus, the lactate concentration required to drive epigenetic reconnection The function of lactate and lactylation in various pathophysiological conditions might vary. It will be interesting to explore whether lactate homeostasis can be restored once these conditions have been established.via lactate and lactylation. Lactate and its transporters are gaining attention as novel therapeutic targets in such diseases , Zhejiang Provincial Natural Science Foundation (LGF19H030004), and Zhejiang medical and health technology project (2018PY039).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Here, Fursova et al. investigated the role of BAP1, an H2AK119ub1 deubiquitylating enzyme, in regulating gene expression in mouse ESCs. Using inducible genetic perturbations and quantitative genomics, they show that BAP1 plays a widespread role in promoting gene expression and that this relies on BAP1 counteracting pervasive H2AK119ub1. In the absence of BAP1, accumulation of H2AK119ub1 throughout the genome leads to widespread reductions in transcription. Drosophila has been characterized as a Polycomb group gene. Together, these observations reveal that the transcriptional potential of the genome can be modulated by regulating the levels of a pervasive histone modification.Histone-modifying systems play fundamental roles in gene regulation and the development of multicellular organisms. Histone modifications that are enriched at gene regulatory elements have been heavily studied, but the function of modifications found more broadly throughout the genome remains poorly understood. This is exemplified by histone H2A monoubiquitylation (H2AK119ub1), which is enriched at Polycomb-repressed gene promoters but also covers the genome at lower levels. Here, using inducible genetic perturbations and quantitative genomics, we found that the BAP1 deubiquitylase plays an essential role in constraining H2AK119ub1 throughout the genome. Removal of BAP1 leads to pervasive genome-wide accumulation of H2AK119ub1, which causes widespread reductions in gene expression. We show that elevated H2AK119ub1 preferentially counteracts Ser5 phosphorylation on the C-terminal domain of RNA polymerase II at gene regulatory elements and causes reductions in transcription and transcription-associated histone modifications. Furthermore, failure to constrain pervasive H2AK119ub1 compromises Polycomb complex occupancy at a subset of Polycomb target genes, which leads to their derepression, providing a potential molecular rationale for why the BAP1 ortholog in  In eukaryotes, DNA is wrapped around histones to form nucleosomes and chromatin, which packages the genome inside the nucleus. In addition to their structural role, histones are subject to a variety of posttranslational modifications (PTMs), which have been proposed to play important roles in regulation of gene expression and other chromosomal processes . If chroGenome-wide profiling has revealed that some histone modifications are specifically enriched at gene promoters and distal regulatory elements , where tThe Polycomb repressive complex 1 (PRC1) is an E3 ubiquitin ligase that catalyzes monoubiquitylation of histone H2A (H2AK119ub1) . PRC1 isInterestingly, H2AK119ub1 is highly dynamic , and a nTo dissect how BAP1 controls H2AK119ub1 levels and gene expression, here, we integrate genome editing, inducible genetic perturbations, and quantitative genomics. We found that BAP1 functions to constrain pervasive H2AK119ub1 throughout the genome, with no preference for gene promoters or distal regulatory elements. We demonstrate that by counteracting pervasive H2AK119ub1, BAP1 plays a fundamental role in facilitating gene expression. In the absence of BAP1, elevated H2AK119ub1 broadly inhibits Serine 5 phosphorylation (Ser5P) on the C-terminal domain (CTD) of RNA polymerase II at gene regulatory elements and causes widespread reductions in transcription and transcription-associated histone modifications, without limiting chromatin accessibility. Finally, we discover that a subset of Polycomb target genes rely on BAP1 for their silencing and provide a mechanistic rationale for how BAP1 can indirectly support Polycomb-mediated gene repression. Together, these observations demonstrate how the levels of a pervasive histone modification must be appropriately controlled to enable the transcriptional potential of the genome.fl/flBap1) in which addition of tamoxifen (OHT) enables inducible removal of BAP1, allowing us to capture the primary effects that BAP1 loss has on H2AK119ub1 and gene expression. Importantly, tamoxifen treatment of fl/flBap1 cells resulted in a complete loss of BAP1 protein, while the levels of BAP1-interacting partners were largely unchanged . Importantly, the magnitude of H2AK119ub1 accumulation appeared to be largely uniform throughout the genome , where BAP1 has been previously proposed to function  and examined changes in H2AK119ub1 across these distinct states. This revealed that all chromatin states were significantly affected and displayed similar increases in H2AK119ub1 . Interestingly, these effects appeared to be less pronounced at Polycomb-enriched chromatin states , with higher initial levels of H2AK119ub1 likely accounting for the smaller apparent fold changes following BAP1 removal , possibly due to the previously proposed antagonism between the Polycomb system and transcription  showed at least a 20% reduction in expression. Of these, 2828 genes  were significantly reduced by at least 1.5-fold, indicating that BAP1 plays a broad role in promoting gene expression.Given that H2AK119ub1 plays a central role in PRC1-mediated gene repression , we wereSupplemental Fig. S3B). However, interestingly, these genes were often found in regions of the genome that had higher levels of H2AK119ub1 in wild-type cells and, in the absence of BAP1, also acquired higher levels of H2AK119ub1 than genes that were not significantly affected . Importantly, the increase in H2AK119ub1 was not specific to the promoters or enhancers of these genes but was evident across the entire gene and flanking regions . Together, these observations suggest that widespread reductions in gene expression following BAP1 removal likely result from pervasive accumulation of H2AK119ub1, with some genes being more susceptible to these effects than others.Although reductions in gene expression following BAP1 removal were widespread, expression of some genes was more severely affected than others. Importantly, the majority of genes showing significantly reduced expression were not classical Polycomb target genes  in which we could simultaneously disrupt BAP1 and inactivate PRC1 catalysis to remove H2AK119ub1 . Strikingly, in the absence of H2AK119ub1, removal of BAP1 no longer caused widespread reductions in gene expression , indicating that H2AK119ub1 was required for these effects. In contrast, Polycomb target genes were derepressed following catalytic inactivation of PRC1 regardless of whether BAP1 was disrupted . Therefore, we conclude that BAP1 counteracts accumulation of H2AK119ub1 throughout the genome, and in its absence elevated H2AK119ub1 causes widespread inhibition of gene expression.To directly test whether elevated H2AK119ub1 was responsible for gene repression in the absence of BAP1, we developed an inducible mouse ES cell line . The reduction in Ser2P in gene bodies was similar in magnitude to the decrease in total Pol II levels , suggesting that elevated H2AK119ub1 limits Ser5 phosphorylation on the CTD of Pol II, and this may lead to reduced transcription and gene expression.To understand how accumulation of H2AK119ub1 counteracts gene expression, we examined how RNA polymerase II (Pol II) was affected after BAP1 removal. To achieve this, we carried out cChIP-seq to quantitate total Pol II levels and also examined its phosphorylation states, which are associated with transcription initiation (Ser5P) and elongation (Ser2P) . When weI levels A,C,D, inSupplemental Fig. S4A,B,D), which were similar in magnitude . Importantly, these effects on Pol II in the gene body correlated well with changes in transcript levels , indicating that elevated H2AK119ub1 causes widespread reductions in transcription and gene expression , despite only a subset of genes being captured as having significantly reduced expression in cnRNA-seq analysis. Importantly, in contrast to Pol II occupancy, which was only modestly affected, Ser5P was markedly reduced at the promoters of all genes, including those whose expression did not change significantly after BAP1 removal . This suggests that the widespread reductions in transcription following BAP1 removal are likely linked to the observed reductions in Ser5P. Since the accumulation of H2AK119ub1 in the absence of BAP1 is not restricted to genes or their promoters . Together, these observations demonstrate that BAP1 functions broadly throughout the genome to support transcription from gene regulatory elements by constraining pervasive H2AK119ub1.Given that removal of BAP1 caused pervasive accumulation of H2AK119ub1 throughout the genome , we wondromoters D, we wonromoters . This reSupplemental Fig. S5A–C,E,F). Removal of BAP1 also compromised H3K4me3 at gene promoters, but this effect was on average much more modest and mostly limited to genes that showed significant reductions in expression . In contrast, H3K4me3 at enhancers was markedly reduced, despite the starting levels of this modification being considerably lower than at promoters . Finally, we also observed a modest but widespread decrease in H3K4me1 around promoters and enhancers, which was accompanied by a slight increase at the center of these regulatory elements . Therefore, we found that BAP1 removal leads to moderate and seemingly indiscriminate effects on transcription-associated histone modifications at both promoters and enhancers, which correlate with the effects on gene expression . This observation differs from previous studies that have implicated BAP1 and other PR-DUB subunits in directly recruiting chromatin-modifying transcriptional coactivators to either promoters or enhancers to specifically affect histone modifications at these sites . Instead, to our surprise, we found that, following BAP1 removal, chromatin accessibility was modestly increased throughout the genome, in a similar manner to the pervasive accumulation of H2AK119ub1 . Importantly, this demonstrates that H2AK119ub1 does not counteract transcription simply by limiting the access of regulatory factors to promoters and enhancers. Instead, pervasive accumulation of H2AK119ub1 in the absence of BAP1 broadly counteracts Ser5 phosphorylation of the Pol II CTD, resulting in widespread reductions in transcription and its associated histone modifications. Together, our findings illustrate how a pervasive histone modification that can inhibit transcription must be appropriately controlled to support the transcriptional potential of the genome.Given that some chromatin modifications have been proposed to function through making chromatin less accessible to gene regulatory factors , we sougDrosophila orthologs of BAP1  and other PR-DUB components as Polycomb group (PcG) transcriptional repressors , suggesting that reactivation of these genes following BAP1 removal is not due to reductions in these histone modifications. We then examined PRC1 and PRC2 occupancy at Polycomb target gene promoters and found that it was modestly reduced, despite the observed increases in H2AK119ub1 and H3K27me3 . However, strikingly, when we focused on the promoters of Polycomb target genes that were derepressed in the absence of BAP1, we found that they were on average occupied by much higher levels of PRC1 and PRC2 in untreated cells and showed much more dramatic reductions in their occupancy after BAP1 removal . Based on these observations, we conclude that this subset of Polycomb target genes are particularly reliant on high-level occupancy of PRC1 and PRC2 for their silencing and that the major decrease in Polycomb complex binding at their promoters caused by removal of BAP1 leads to their derepression. Given that both Polycomb repressive complexes can directly bind to H2AK119ub1  gives rise to PcG phenotypes in genetic assays, despite its role in counteracting H2AK119ub1. Furthermore, it reveals that limiting pervasive H2AK119ub1 throughout the genome is important for focusing Polycomb repressive complexes at target gene promoters, while enabling transcription elsewhere in the genome.To better understand the interplay between BAP1 and the Polycomb system, we investigated the effect that BAP1 removal has on Polycomb chromatin domains by examining the binding of PRC1 (RING1B), PRC2 (SUZ12), and levels of their respective histone modifications (H2AK119ub1 and H3K27me3) by cChIP-seq. This showed that, in the absence of BAP1, H2AK119ub1 increased across Polycomb chromatin domains at target gene promoters E, althouH3K27me3 E, and thAK119ub1 , we enviChromatin-modifying enzymes can function at defined gene regulatory elements to support cell type-specific gene expression patterns . Their rWe envisage that this generic mode of gene regulation could be particularly relevant during cellular differentiation and development when the transcriptional activity of the genome or large genomic regions needs to be coordinately modulated to support acquisition and maintenance of cell type-specific transcriptional states. In fact, support for this concept has recently emerged from studies of X inactivation where H2AK119ub1 was shown to accumulate across the entire silenced X chromosome to drive transcriptional repression and enable dosage compensation . Further6 H2AK119ub1 molecules decorate the genome of ES cells  supplemented with 15% fetal bovine serum (Labtech), 2 mM L-glutamine (Life Technologies), 1× penicillin/streptomycin (Life Technologies), 1× nonessential amino acids (Life Technologies), 0.5 mM β-mercaptoethanol (Life Technologies), and 10 ng/mL leukemia inhibitory factor (in-house). To induce conditional removal of BAP1, on its own or in combination with PRC1 catalytic activity, fl/flBap1 and CPM;Bap1fl/flPRC1 cells were treated with 800 nM 4-hydroxytamoxifen (OHT) for 96 h. To induce conditional removal of PRC1 catalytic activity on its own, PRC1CPM cells were treated with 800 nM OHT for 72 h. Cells were regularly tested for the presence of mycoplasma.E14TG2a mouse embryonic stem cells (ESCs) were grown on gelatin-coated plates at 37°C and 5% CO2 in Dulbecco's modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum (Labtech), 2 mM L-glutamine (Life Technologies), 1× penicillin/streptomycin (Life Technologies), and 0.5 mM β-mercaptoethanol (Life Technologies). Drosophila S2 (SG4) cells used for spike-in calibration of native cChIP-seq, cnRNA-seq, and cATAC-seq were grown adhesively at 25°C in Schneider's Drosophila medium (Life Technologies), supplemented with 1× penicillin/streptomycin (Life Technologies) and 10% heat-inactivated fetal bovine serum (Labtech).Human HEK293T cells used for spike-in calibration of cChIP-seq were grown at 37°C and 5% COfl/flBap1 cells were derived from E14TG2a ESCs by a two-step process. First, parallel loxP sites flanking exon 4 of the Bap1 gene were inserted using a targeting construct with homology arms of ∼1 kb and three different Cas9 guides specific for the Bap1 locus . Second, CreERT2 was inserted into the Rosa26 locus using a Rosa26-specific Cas9 guide (sgRNA target sequence: CGCCCATCTTCTAGAAAGAC). The same BAP1-specific targeting construct and Cas9 guides were used to generate CPM;Bap1fl/flPRC1 cells from a PRC1CPM parental cell line. Loss of BAP1 in response to OHT treatment in fl/flBap1 and CPM;Bap1fl/flPRC1 ESCs was confirmed using RT-qPCR and Western blot analysis.PRC1CPM cells were generated and characterized in a previous study (Ring1b in forward orientation (flanked by 100 bp of Ring1b intron 2/intron 3), followed by a mutant copy of exon 3 (encoding I53A and D56K mutations) in reverse orientation (flanked by splice donor and acceptor sites from mouse IgE gene). Both the wild-type and mutant versions of exon 3 were codon-optimized at wobble positions to minimize sequence similarity. The wild-type/mutant exon 3 pair was flanked by doubly inverted LoxP/Lox2272 sites and ∼1-kb homology arms. The targeting construct was transfected into E14TG2a ESCs in combination with three different Cas9 guides specific for the Ring1b gene. Correctly targeted homozygous clones were identified by PCR screening, followed by RT-PCR and sequencing to check for splicing defects. Using a similar approach, the I50A/D53K mutation was constitutively knocked-in into both copies of the endogenous Ring1a gene. Finally, CreERT2 was inserted into the Rosa26 locus using a Rosa26-specific Cas9 guide.us study . Brieflyhttp://crispor.tefor.net/crispor.py). Targeting constructs with appropriate homology arms were generated by Gibson assembly using the Gibson Assembly Master Mix kit (NEB). Targeting constructs were designed such that Cas9 recognition sites were disrupted by the presence of the LoxP sites. ESCs (one well of a six-well plate) were transfected with 0.5 μg of each Cas9 guide and 2 μg of targeting construct using Lipofectamine 3000 (ThermoFisher) according to the manufacturer's guidelines. The day after transfection, cells were passaged at a range of densities and subjected to selection with 1 μg/mL puromycin for 48 h to eliminate nontransfected cells. Approximately 1 wk later, individual clones were isolated, expanded and PCR-screened for the desired genomic modifications.The pSptCas9(BB)-2A-Puro(PX459)-V2.0 vector was obtained from Addgene (62988), and sgRNAs were designed using the CRISPOR online tool . After 10 min incubation on ice, cells were recovered by centrifugation at 1500g for 5 min and resuspended in 3 vol of buffer A supplemented with 0.1% NP-40. The released nuclei were pelleted by centrifugation at 1500g for 5 min, followed by resuspension in 1 vol of buffer C  supplemented with 400 mM NaCl. The extraction was allowed to proceed on ice for 1 h with occasional agitation, then the nuclei were pelleted by centrifugation at 16,000g for 20 min at 4°C. The supernatant was taken as the nuclear extract. The Bradford protein assay (Bio-Rad) was used to compare protein concentrations across samples.For nuclear extraction, ESCs were washed with 1× PBS and resuspended in 10 volumes of buffer A  supplemented with 20 mM N-ethylmaleimide (NEM), incubated for 10 min on ice in RSB with 0.5% NP-40 and 20 mM NEM, pelleted by centrifugation at 800g for 5 min, and incubated in 2.5 mM MgCl2, 0.4 M HCl, and 20 mM NEM for 30 min on ice. After that, cells were pelleted by centrifugation at 16,000g for 20 min at 4°C, the supernatant recovered and precipitated on ice with 25% TCA for 30 min, followed by centrifugation at 16,000g for 15 min at 4°C to recover histones. Following two acetone washes, the histones were resuspended in 1× SDS loading buffer  and boiled for 5 min at 95°C. Finally, any insoluble precipitate was pelleted by centrifugation at 16,000g for 10 min and the soluble fraction retained as the histone extract. Histone concentrations across samples were compared using SDS-PAGE followed by Coomassie blue staining. Western blot analysis of nuclear and histone extracts was performed using LI-COR IRDye secondary antibodies, and imaging was done using the LI-COR Odyssey Fc system. The list of antibodies used in this study for Western blot and cChIP-seq analysis is in Supplemental Table S1.For histone extraction, ESCs were washed in RSB  were cross-linked in 10 mL of 1× PBS with 2 mM DSG (Thermo Scientific) for 45 min at 25°C, and then with 1% formaldehyde  for a further 15 min. Cross-linking was stopped by quenching with 125 mM glycine. Cross-linked ESCs were mixed with 2 × 106 human HEK293T cells, which have been similarly double-cross-linked, and incubated in lysis buffer  for 10 min at 4°C. Released nuclei were washed  for 5 min at 4°C. Chromatin was then resuspended in 1 mL of sonication buffer  and sonicated for 30 min using the BioRuptor Pico (Diagenode), shearing genomic DNA to an average size of 0.5 kb. Following sonication, Triton X-100 was added to a final concentration of 1%, followed by centrifugation at 20,000g for 10 min at 4°C to collect the clear supernatant fraction.For RING1B and SUZ12, cChIP-seq was performed as described previously . Briefly7 ESCs (untreated and OHT-treated) were cross-linked in 10 mL of 1× PBS with 1% formaldehyde  for 10 min at 25°C and then quenched by addition of 125 mM glycine. Cross-linked ESCs were mixed with 2 × 106 human HEK293T cells, which have been similarly single-cross-linked, and then incubated in FA-lysis buffer  for 10 min at 4°C. Chromatin was sonicated for 30 min using the BioRuptor Pico (Diagenode), followed by centrifugation at 20,000g for 10 min at 4°C to collect the clear supernatant fraction.For Pol II and its phosphorylated forms, cChIP-seq was done as described previously . Briefly3) and cross-linking was reversed overnight at 65oC with 200 mM NaCl and 2 μL of RNase A (Sigma). Matched input samples  were treated identically. The following day, ChIP samples and inputs were incubated with Proteinase K (Sigma) for at least 1.5 h at 56oC and purified using a ChIP DNA Clean and Concentrator kit (Zymo Research).For RING1B and SUZ12 ChIP, sonicated chromatin was diluted 10-fold with ChIP dilution buffer . For Pol II ChIP, 300 ug of chromatin per one IP was diluted in FA-lysis buffer up to a final volume of 1 mL. Diluted chromatin was precleared for 1 h using Protein A agarose beads (Repligen) that were preblocked with 1 mg/mL BSA and 1 mg/mL yeast tRNA. For each ChIP reaction, 1 mL of diluted and precleared chromatin was incubated overnight with the appropriate antibody, anti-RING1B , anti-SUZ12 , anti-Rpb1-NTD  as a measure of total Pol II occupancy, anti-Rpb1-CTD-Ser5P , and anti-Rpb1-CTD-Ser2P  as a measure of Pol II phosphorylation levels. To capture antibody-bound chromatin, ChIP reactions were incubated with preblocked protein A agarose beads (Repligen) for 2 h (RING1B and SUZ12) or 3 h (Pol II) at 4°C. For RING1B and SUZ12, ChIP washes were performed as described previously . For PolcChIP-seq libraries for both ChIP and Input samples were prepared using a NEBNext Ultra II DNA library preparation kit for Illumina, following the manufacturer's guidelines. Samples were indexed using NEBNext Multiplex oligos. The average size and concentration of all libraries were analysed using the 2100 Bioanalyzer high-sensitivity DNA kit (Agilent) followed by qPCR quantification using SensiMix SYBR (Bioline) and KAPA Illumina DNA standards (Roche). Libraries were sequenced as 40-bp paired-end reads in biological triplicate or quadruplicate on the Illumina NextSeq 500 platform.7 mouse ESCs (untreated and OHT-treated) were mixed with 2 × 107Drosophila SG4 cells in 1× PBS. Mixed cells were pelleted and nuclei were released by resuspending in ice-cold lysis buffer . Nuclei were then washed and resuspended in 1 mL of MNase digestion buffer . Each sample was incubated with 200 U of MNase (Fermentas) for 5 min at 37°C, followed by the addition of 4 mM EDTA to halt MNase digestion. Following centrifugation at 1500g for 5 min at 4°C, the supernatant (S1) was retained. The remaining pellet was incubated with 300 µL of nucleosome release buffer  for 1 h at 4°C, passed five times through a 27G needle using a 1-mL syringe, and spun at 1500g for 5 min at 4°C. The second supernatant (S2) was collected and combined with the corresponding S1 sample from above. Digestion to mostly mononucleosomes was confirmed by agarose gel electrophoresis of purified S1/S2 DNA.Native cChIP-seq for H2AK119ub1, H3K27me3, H3K27ac, H3K4me3, and H3K4me1 was performed as described previously . Briefly2, 2 mM EDTA, 0.1% Triton X-100, 10 mM sodium butyrate [for H3K27ac and H3K4me3 ChIPs], 10 mM N-ethylmaleimide, 1× PIC [Roche]). For each ChIP reaction, 1 mL of diluted nucleosomes was incubated overnight at 4oC with the appropriate antibody, anti-H2AK119ub1 , anti-H3K27me3 , anti-H3K27ac (3 μL CST D5E4), anti-H3K4me3 , or anti-H3K4me1 . Antibody-bound nucleosomes were captured for 1 h at 4°C using Protein A agarose (Repligen) beads, preblocked in native ChIP incubation buffer supplemented with 1 mg/mL BSA and 1 mg/mL yeast tRNA, and collected by centrifugation. Immunoprecipitated material was washed four times with native ChIP wash buffer  and once with TE buffer (pH 8). ChIP DNA was eluted using 100 μL of elution buffer  for 30 min at room temperature, and then purified using a ChIP DNA Clean and Concentrator kit (Zymo Research). For each ChIP sample, DNA from a matched input control  was purified in the same way. Native cChIP-seq library preparation and sequencing was performed as described above for cChIP-seq.For ChIP, S1/S2 nucleosomes were diluted 10-fold in native ChIP incubation buffer  were mixed with 4 × 106Drosophila SG4 cells in 1× PBS. Nuclei were isolated in 1 mL HS lysis buffer  for 1 min at room temperature, and then recovered by centrifugation at 1000g for 5 min at 4°C, followed by a total of three washes with ice-cold RSB buffer . Nuclei integrity was assessed using 0.4% Trypan blue staining (Thermo Scientific). Pelleted nuclei were resuspended in 1 mL of TRIzol reagent (Thermo Scientific), and RNA was extracted according to the manufacturer's protocol, followed by treatment with the TURBO DNA-free kit (Thermo Scientific) to remove any contaminating DNA. Quality of RNA was assessed using the 2100 Bioanalyzer RNA 6000 Pico kit (Agilent). RNA samples were depleted of rRNA with the NEBNext rRNA depletion kit (NEB) prior to preparing cnRNA-seq libraries using the NEBNext Ultra (for fl/flBap1 and PRC1CPM ESCs) or Ultra II  Directional RNA library preparation kit (NEB). To quantitate the consistency of spike-in cell mixing for each individual sample, a small aliquot of nuclei was saved to isolate genomic DNA using phenol-chloroform extraction. This was followed by sonication of DNA for 15 min using the BioRuptor Pico (Diagenode), shearing genomic DNA to an average size of <1 kb. Libraries from sonicated genomic DNA were constructed as described above for cChIP-seq. Both cnRNA-seq and gDNA-seq libraries were sequenced as 80-bp paired-end reads on the Illumina NextSeq 500 platform in biological triplicate.For cnRNA-seq, 1 × 107 ESCs (untreated and OHT-treated) were mixed with 4 × 106Drosophila SG4 cells in 1× PBS and then lysed in 1 mL of HS lysis buffer  for 1 min at room temperature. Nuclei were recovered by centrifugation at 1000g for 5 min at 4°C and washed three times in ice-cold RSB buffer . The concentration and integrity of nuclei were assessed using 0.4% Trypan blue staining (Thermo Scientific). Next, 5 × 105 nuclei were resuspended in Tn5 reaction buffer  and incubated with Tn5 transposase    for 30 mLibraries for cATAC-seq and gDNA-seq were prepared by PCR amplification using the NEBNext high-fidelity 2× PCR Master Mix and custom-made Illumina barcodes . LibrariFollowing massive parallel sequencing, reads were mapped and processed as described previously . BrieflySupplemental Table S2.For cnRNA-seq, first, Bowtie 2 was used with “‐‐very-fast,” “‐‐no-mixed,” and “‐‐no-discordant” options to identify and discard reads mapping to the concatenated mm10 + dm6 rDNA genomic sequences (GenBank BK000964.3 and M21017.1). Next, all unmapped reads were aligned against the concatenated mm10 + dm6 genome using STAR . To imprSupplemental Table S3) and were merged for downstream analysis. Genome coverage tracks were generated using the pileup function from MACS2 .To visualize the cChIP-seq, cATAC-seq, and cnRNA-seq and quantitatively compare genome enrichment profiles, chromatin accessibility, and gene expression between conditions, the data were internally calibrated using dm6 or hg19 spike-in as described previously . Brieflyom MACS2  for cChIom MACS2  for cATAom MACS2  for cnRNom MACS2 . BigwigCSupplemental Figure S2B based on the underlying functional genomic annotations and their transcriptional activity. These included CTCF-bound insulators, distal gene regulatory elements (weak to highly active enhancers), actively transcribed promoters and gene body regions, Polycomb-repressed and bivalent chromatin domains, H3K9me3-enriched heterochromatin, and intergenic regions that are not enriched with any examined chromatin features. The genomic coordinates of chromatin states identified by ChromHMM were deposited in GEO: GSE161993.ChromHMM  was usedfl/flBap1 ESCs (untreated and OHT-treated) for four biological replicates using the dpeak function  from DANPOS2  or active promoters , based on their overlap with TSS ± 1-kb regions. To obtain the most complete set of TSS positions, we combined TSS annotations from the UCSC refGene , NCBI RefSeq , and GENCODE VM24  databases. To eliminate the contribution of gene body signal for Pol II cChIP-seq, only intergenic active enhancers (n = 4156), which did not overlap with any of the above gene annotations, were considered for the downstream analysis. To associate genes with putative distal regulatory elements, for each gene promoter we identified the nearest intergenic enhancer located within the 250-kb distance using the closest function from BEDTools. For differential gene expression analysis and quantification of cChIP-seq and cATAC-seq signal at promoters or over the bodies of genes, we used a custom nonredundant set of genes , derived from mm10 UCSC refGene genes by removing very short genes with poor sequence mappability and highly similar transcripts as described previously   were identified using MACS2 peak calling with the matching input control from BioCAP-seq (n = 6333). NMI-overlapping genes were further subdivided into PcG-occupied genes (n = 5582), if their promoters overlapped with both RING1B- and SUZ12-bound sites defined in a previous study (n = 8718), if they did not. The overlap between NMIs, RING1B- and SUZ12-bound regions with gene promoters (TSS ± 1 kb) was determined using the closest function from BEDTools. In the text, we refer to PcG-occupied genes as Polycomb target genes.Mouse genes in a custom nonredundant set   were claoCAP-seq . All genus study , and nonn = 20,633).For cChIP-seq and cATAC-seq, computeMatrix and plotProfile/plotHeatmap from deepTools were used to perform metaplot and heat map analysis of read density at regions of interest. Metaplot profiles represented the mean read density over a set of genomic regions, except for Pol II cChIP-seq, for which the median read density was plotted due to an extremely broad range of signal intensities across the intervals of interest. For chromosome-wide density plots, read coverage in 250-kb bins was calculated using a custom R script using GenomicRanges, GenomicAlignments, and Rsamtools Bioconductor packages  and visu2 fold changes for different genomic intervals were visualized using custom R scripts and ggplot2. For box plot analysis of cChIP-seq and cATAC-seq signal, read counts were normalized to the genomic region size (in kb) and log2 transformed following addition of a pseudocount of 1. For box plots, boxes show the interquartile range (IQR) and whiskers extend by 1.5 × IQR. ggcor function from the GGally R package was used to generate a correlation matrix for the association between log2 fold changes in gene expression (cnRNA-seq) and log2 fold changes in cChIP-seq signal for Pol II and transcription-associated histone modifications at gene promoters or bodies following OHT treatment in fl/flBap1 ESCs. All correlation analyses used the Pearson correlation coefficient to measure the strength of the association between the variables and were visualized using scatterplots colored by density with stat_density2d. Linear regression was plotted using the stat_poly_eq function from the ggpmisc R package, together with the model's R2adj coefficient of determination. To calculate statistical significance, we carried out Student's t-test using R, with samples considered to be independent and a two-tailed alternative hypothesis, unless specified otherwise.Normalized read counts and log2 fold changes using the original DESeq2 shrinkage estimator with an adaptive normal distribution as prior . This resulted in a set of 14,779 robustly expressed genes, which was used to estimate the proportion of expressed genes that showed reductions in expression following BAP1 removal. Log2 fold change values were visualized using R and ggplot2 with MA plots, heat maps, and box plots/violin plots. ComplexHeatmap R package (2 fold gene expression changes. For MA plots, the density of the data points across the y-axis was shown to reflect the general direction of gene expression changes. Venn diagrams were plotted using Vennerable R package. The significance of pairwise overlaps for Venn diagrams was calculated by a Fisher's exact test using GeneOverlap R package. HOMER v4.9.1 (To identify significant gene expression changes in cnRNA-seq, we used a custom R script that incorporates spike-in calibration into DESeq2 analysis  as descras prior . For vis package  was usedR v4.9.1  was usedPRC1CKO ESCs, GEO: GSE119619 (fl/flBrg1 ESCs, GEO: GSE87822 (https://github.com/nFursova/Calibrated_ChIPseq_RNAseq.The high-throughput sequencing data reported in this study have been deposited in GEO under the accession number GSE161996. Published data used in this study include BioCAP-seq, GEO: GSE43512 ; cnRNA-sSE119619 ; RING1B-SE119619 ; ATAC peSE119619 ; CTCF ChSE119619 ; ChIP-seGSE87822 ; and H3KGSE87822 . Custom


The placenta is a temporary organ that provides the developing fetus with nutrients, oxygen, and protection in utero. Defects in its development, which may be caused by misregulated gene expression, can lead to devastating outcomes for the mother and fetus. In mouse, placental defects during midgestation commonly lead to embryonic lethality. However, the regulatory mechanisms controlling expression of genes during this period have not been thoroughly investigated. Therefore, we generated and analyzed ChIP-seq data for multiple histone modifications known to mark cis-regulatory regions. We annotated active and poised promoters and enhancers, as well as regions generally associated with repressed gene expression. We found that poised promoters were associated with neuronal development genes, while active promoters were largely associated with housekeeping genes. Active and poised enhancers were associated with placental development genes, though only active enhancers were associated with genes that have placenta-specific expression. Motif analysis within active enhancers identified a large network of transcription factors, including those that have not been previously studied in the placenta and are candidates for future studies. The data generated and genomic regions annotated provide researchers with a foundation for future studies, aimed at understanding how specific genes in the midgestation mouse placenta are regulated. Mouse is a commonly used model to understand the genetic regulation governing the development and function of the human placenta4. In the mouse, placental abnormalities are strongly associated with embryonic lethality during midgestation, including lethality at embryonic day (e)9.55, emphasizing the importance of studying gene regulation at this developmental stage. At e9.5, the ectoplacental cone (EPC) is still present, and placental labyrinth formation has initiated with the fusion of the allantois and chorion. The labyrinth space is filled with fetal blood vessels7 and becomes the site of exchange between the maternal and fetal blood supply. While the placenta is not fully developed at this stage and still contains progenitor cells, understanding what regulates the gene expression patterns at e9.5 will provide a snapshot of the mechanisms that drive mature placenta formation.The placenta is an essential organ during development, providing the fetus with adequate nutrients, oxygen, and protection during gestation. Dysfunctions of gene regulation in the placenta can have detrimental effects on the health of the mother and fetus, as well as lead to a variety of placental disorders such as preeclampsia8 and have been implicated in development9 and cancer10.Several factors contribute to gene regulation, including transcription factors, cis-regulatory elements, and epigenetic modifications. Post-translational modifications on histones have been found to be important for the regulation of gene expression during development, and in response to environmental stimuli. Perturbations in histone modifications can alter the structure of chromatin, preventing interactions between specific regulating chromatin factors13, distinguishing such regions from poised enhancers12. Tri-methylation of the same lysine on the same histone (H3K27me3) has generally been associated with gene repression14. Mono-methylation and tri-methylation of lysine-4 on histone H3 (H3K4me1/H3K4me3) have instead been associated with specific genomic regions. H3K4me3 is typically enriched at the transcription start site (TSS) of active genes13 while H3K4me1 has been found to mark enhancers15.Histone acetylation is often associated with gene activation. Acetylation of lysine-27 on histone H3 (H3K27ac) is enriched in active gene promoters and in active enhancers12. H3K4me3 has been found at regions that are also frequently marked with either H3K27ac or H3K27me3. When H3K4me3 and H3k27me3 are identified together, these bivalent regions are generally thought to be associated with poised genes important during development16.Though each histone modification individually contributes to our understanding of gene regulation, when combined, these modifications can annotate the genome in more detail. For example, though H3K4me1 marks enhancers, the presence of H3K27ac with H3K4me1 marks active enhancers17 combined RNA-seq data and ChIP-seq data for several histone modifications, RNA polymerase II, and CTCF from e14.5 placenta and 18 other tissues to identify tissue-specific enhancers and promoters. Another study used histone modifications to identify promoters and enhancers in mouse and rat trophoblast stem cells18, focusing on identifying differences in the species-specific enhancers to gain insight into placental evolution. Other studies have also used histone modification ChIP-seq in placental cell lines to identify regulatory elements that are bound by transcription factors (TFs) or to identify regulatory elements that may control TF expression20. However a thorough annotation of the regulatory landscape in the e9.5 mouse placenta, after the chorion and allantois have merged and when the labyrinth and fetal vasculature are developing to allow adequate exchange of material21, has not been done.Previous studies have used multiple histone modifications to better understand the regulatory landscape of the mouse placenta. Shen et al.22, we employed ChromHMM23 to annotate the e9.5 placental genome, identifying potential repressors, enhancers, active promoters, and bivalent regions. Overall, these data provide a valuable resource for researchers trying to understand gene regulation in the midgestation placenta.Therefore, to identify cis-regulatory elements involved in gene regulation in the e9.5 placenta, we performed ChIP-seq to identify regions marked with the H3K27me3, H3K4me1, or H3K4me3 histone modifications. Using this data and a published H3K27ac ChIP-seq dataset14), H3K4me1 (enhancers15), and H3K4me3 (promoters15). After aligning, filtering, and calling peaks on each sample, we used principal component analysis (PCA) on peak scores and saw that replicates cluster based on the histone modification that was assayed and data from each histone modification were well separated . An example of a genomic region in the R state is shown around the Hoxa cluster of genes, which are globally silenced during development25  of certain Hoxa genes, such as Hoxa9, Hoxa10, and Hoxa13, which have known roles in placenta development28. State 4 regions contain high levels of H3K27me3, H3K4me1, and H3K4me3 activity and are most commonly found in promoter regions  in the UCSC genome browser containing averaged ChIP-seq read tracks for each histone modification as well as ChromHMM state information.39. Though we found several neuronal genes in the PP State, we also found a subset of genes that code for TFs with roles prior to mid-gestation, including stem cell differentiation (SATB240), trophoblast differentiation , and trophoblast migration (FOSL144). According to previously published RNA-seq data from the EPC at both e7.5 and e9.5 22 and the placental disc at e12.545, each of these genes shows decreasing expression as placental development progresses, suggesting these bivalent regions are becoming stably repressed   and embryonic lethality  associated with the AE state genes, whereas such placenta terms were not enriched for PE state genes  and, unsurprisingly higher than genes with an associated R state   RNA-seq data came from CD-1 mice, but the e12.5 placental disc RNA-seq data was from a cross of C57BL6 females and CAST/Ei males. Genetic background can impact placental morphology39. We identified several PP genes involved in differentiation that showed decreasing expression as placental development continued, including Satb2, Hand1, Ascl2, and Tcfap2a  characterized by the presence of all four histone modifications , and placenta specific protein 1 (Plac1). Interestingly, around e12.5 to e14.5 the placenta goes through drastic changes in gene expression. Genes upregulated before this switch, during the developing phase (~ e8.5– ~ e13.5), were found to be enriched for terms related to RNA processing and metabolism as well as those involved in the cell cycle, which are similar to a category of terms associated with the active promoters identified in this study  and conformed to the NIH Guidelines for the Care and Use of Laboratory Animals. To isolate the placenta, implantation sites were extracted from the uterine lining and the ectoplacental cone (EPC) and chorion, which has merged with the allantois to begin forming the labyrinth, were separated from the decidua, yolk sac, umbilical cord, and embryo, then collected. Three placentas were collected from the same litter and pooled into one biological replicate as previously described47. However, each biological replicate was from a different litter. ChIP was then performed as previously described for H3K27me347 with 10ug of chromatin and 4ug of H3K27me3 antibody  for a total of 4 biological replicates (where each replicate is from a different litter). H3K4me1 and H3K4me3 ChIPs were performed as previously described94 with the following modifications: 2.5ug of chromatin was precleared with 80ul of Protein G-agarose (Thermofisher 20422) in 1 ml of ChIP dilution buffer and incubated overnight with 2ug of H3K4me1 antibody  or 2ug of H3K4me3 antibody , generating 6 biological replicates for each antibody. Input DNA (control) was simultaneously prepared from chromatin for each replicate. The enrichment level (fold-change) for each histone modification was quantified using Real-Time qPCR with input DNA for normalization. Enrichment was calculated using the ΔΔCt method with 28S as a reference primer and input DNA as a control. Syt1 (H3K27me3), B4galt5 (H3K4me1), and Ldha (H3K4me3)  as described previously95 with the following modifications: 40ul (80%) of the purified ChIP DNA was used for library preparation for each biological replicate and gel size selection was performed by excising DNA fragments between 250 and 350 bp. 5 ng of input sample libraries were also prepared simultaneously as controls. Libraries were run on the Agilent 2100 bioanalyzer using the high sensitivity DNA kit to ensure proper size selection. Both ChIP and input libraries were diluted to 4 nM and pooled together. Further dilution of the samples and sequencing on Illumina HiSeq 3000 was performed by the Iowa State University DNA facility.ChIP-seq libraries were generated as previously described22). Read quality for all ChIP-seq samples was determined using FASTQC96 (v0.11.7) and reads were aligned to the mm10 genome using Bowtie297 . All samples had high average overall alignment rates (Supplementary Table http://broadinstitute.github.io/picard). BAM files for each experiment were then merged and converted to bigwig using bamCoverage from deepTools (v2.5.2) for browser visualization98.ChIP-seq data for the H3K27ac associated histone mark was obtained from GEO (GSE6580723 (v1.20) with 13 states, using ChIP-seq data and corresponding input DNA data as controls. The BAM files were also used for peak calling with MACS299 (v2.1.1), either broad peaks  or narrow peaks . Peaks within 500 bp were merged together using BEDTools2100  and PCA was run on H3K4me3, H3K4me1, and H3K27me3 biological replicates in order to determine correlation between replicates . Peaks were retained if they occurred in at least half of the corresponding biological replicates and did not overlap problematic regions that have high signal across all ChIP-seq data, likely due to amplification noise102. After ChromHMM regions were assigned to states, they were further intersected with MACS2 peaks, and only regions containing peaks for the appropriate histone marks were kept for further analysis. For the repressed (R) state, ChromHMM regions containing an H3K27me3 peak were retained. For the active enhancer (AE) and poised enhancer (PE) states, an H3K4me1 peak had to be present within the ChromHMM region. For the active promoter (AP) and poised promoter (PP) states, an H3K4me3 peak had to be present within the ChromHMM region. The genomic feature that ChromHMM regions were found in, and their location in relation to TSSs were identified using the R package ChIPseeker103 (v1.24.0).Filtered Bowtie2 BAM files were used in ChromHMM47. After removing duplicates, MACS2  was used to call narrow peaks. Peaks overlapping problematic regions were removed and peaks within 100 bp of each other were merged. Only peaks that were in at least two of the three replicates were kept for analysis.ATAC-seq data from the e9.5 placenta (EPC and chorion from CD-1 mice) were obtained from GEO (GSE120599) and processed as previously described22 (e7.5 and e9.5), GSE12421545 (e12.5)) and processed as previously described47. Reads were aligned to the mm10 mouse genome using HISAT2104  and transcript abundance was calculated by htseq-count from the HTseq105 software package. We then calculated transcript per million (TPM)106 for each gene, and TPMs for each gene were averaged across biological replicates.RNA-seq data used in this manuscript were previously published and obtained from the EPC at e7.5, EPC and chorion at e9.5, and the placental disc at e12.5. RNA-seq data was obtained from GEO 60  motif finding software and the mm10 genome. Only significant  transcription factors found were kept for analysis. Mouse transcription factors were identified using the Animal Transcription Factor Database108 (v3.0). Targets of enriched transcription factors were also identified using the HOMER software (findMotifsGenome.pl-find).Enrichment of transcription factors within active enhancer regions was determined using HOMER61 (v11.0) was used to build protein–protein interaction networks from enriched TFs. Networks were built with a confidence threshold of 0.40 and using all forms of evidence. Networks were analyzed using Cytoscape109 (v3.8.0) and hub nodes were defined as the top three nodes with the highest degree  and the top three with the highest betweenness score .The STRING database110 was used to carry out tissue-specific gene enrichment analysis using all of the tissue-specific genes from the mouse ENCODE data as background, and using default parameters. Tissue-specific gene sets with an adjusted p-value ≤ 0.01  were considered enriched, using the hypergeometric test.TissueEnrichSupplementary Information 1.Supplementary Information 2.