The discovery and adaption of bacterial clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated (Cas) systems has revolutionized the way researchers edit genomes. Engineering of catalytically inactivated Cas variants (nuclease-deficient or nuclease-deactivated [dCas]) combined with transcriptional repressors, activators, or epigenetic modifiers enable sequence-specific regulation of gene expression and chromatin state. These CRISPR–Cas-based technologies have contributed to the rapid development of disease models and functional genomics screening approaches, which can facilitate genetic target identification and drug discovery. In this short review, we will cover recent advances of CRISPR–dCas9 systems and their use for transcriptional repression and activation, epigenome editing, and engineered synthetic circuits for complex control of the mammalian genome. The development of methods that can accurately control gene expression contributes to our understanding of cellular physiology, which is essential for both basic biological research and the advancement of medicine. Gene expression is a multistep process that involves coordinated control of transcription, translation, and turnover of messenger RNAs (mRNA) and proteins4. Precise regulation of the process by which DNA becomes RNA on the transcriptional or epigenetic level is the first step to fully control this sophisticated process.Many pathological conditions such as metabolic disorders, cardiovascular diseases, cancer, or other common diseases are often attributed to dysregulated gene expression17. According to their protein sequence homology and CRISPR repeat identity, the CRISPR–Cas systems discovered so far have been categorized into two major classes and six types using bioinformatics methods20. The class 1 CRISPR system, which requires a large complex of several effector proteins, is divided into types I, III, and IV. In contrast, in the class 2 CRISPR system, which is divided into types II, V, and VI, only one RNA-guided endonuclease is required to mediate the cleavage of invading genetic elements21. Due to their simplicity, the class 2 CRISPR–Cas systems have been mostly employed for genome-engineering applications. In particular, the type II CRISPR–Cas9 systems have been used in a variety of organisms including microbes25, fungi29, plants40, and animals46.In the past few years, RNA-guided sequence-specific genome editing and regulation technologies have been developed based on the discovery of the clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated (Cas) systems. The rapid development of these tools has come after years of research on CRISPR biology, which reveals that bacteria and archaea use CRISPR-associated, RNA-guided DNA endonucleases to defend themselves from invading foreign genetic elements10. The CRISPR–Cas9 complex is recruited to the target DNA site by its guide RNA, which has a ~20 nucleotide sequence complementary to its target. The DNA target must be adjacent to a short stretch of DNA sequence termed protospacer-adjacent motif (PAM)47, which is compatible with the type of Cas9 being employed. The endonuclease activity of Cas9 thus causes a double strand break (DSB) at the target site8. To simplify the use of the CRISPR–Cas9 systems for genome-engineering applications, a seminal study demonstrated that crRNA and tracrRNA could be engineered into a chimeric single guide RNA (sgRNA), which is easily programmable and portable  will be triggered, which often results in insertion/deletion (indel) mutations at the site of editing. Alternatively, by providing a separate DNA template containing sequences homologous to the regions flanking the DSB, Cas9 can facilitate targeted incorporation of the repair template into the genomic DNA by homology-directed repair (HDR). A summary of CRISPR–Cas9-based genome-engineering applications is provided inIn the type II CRISPR–Cas systems, a Cas9 endonuclease and a guide RNA, which consists of a DNA-targeting CRISPR-associated RNA (crRNA) and the trans-activating crRNA (tracrRNA), establish a functional guide RNA–Cas9 complexortable 6. Adapt56. This is achieved by ablating the nuclease activity of Cas9 by creating mutations in the RuvC and HNH nuclease domains, which are conserved among Cas9s from various bacterial species. The resulting nuclease-deactivated Cas9 (dCas9) is a generic RNA-guided DNA-binding molecule which cannot cleave DNA but still retains its ability to bind to specific DNA sequences57. dCas9 can be further engineered into programmable artificial transcription factors in eukaryotic cells to modulate gene expression when coupled with transcriptional repressors or activators, as illustrated below. The structural information about the CRISPR–Cas system has guided, and will continue to guide, the engineering efforts for applications58.Beyond gene editing, CRISPR–Cas9 has been repurposed as a genome-docking platform that allows for a broad range of genome-engineering applications 53,55,61  of fluorescent reporter genes or tested endogenous genes in mammalian cells64. It is possible that the dCas9–sgRNA complex alone is not sufficient to fully block the action of the RNAP complex in eukaryotic cells. To improve the repression efficiency, dCas9 has been fused with a number of repressive transcriptional or epigenetic effector domains, including the KRAB (Krüppel-associated box) domain of Kox1, the CS (chromoshadow) domain of HP1α, the WPRW domain of Hes1, or four concatenated copies of the mSin3 interaction domain (SID4X)66. Among these, KRAB–dCas9 fusion-mediated transcriptional repression is proven to be relatively robust, which can lead to downregulation of the endogenous gene in the range of 90 to 99% with a properly designed sgRNA66  content of sgRNA are not critical factors in successful CRISPRi implementation66.To understand the rules for designing sgRNAs for effective transcriptional repression, high-throughput screens using 54,810 sgRNAs tiled within a 10 kilobase window near the transcription start sites (TSS) of 49 genes have been performed in K562 myelogenous leukemia cellsEscherichia coli59. Further tool development is needed for the practical implementation of CRISPRa in bacterial cells. For instance, characterization of additional transcriptional activators that function in bacterial cells is necessary for enhanced activation efficiency. Furthermore, testing how a given transcriptional activator functions in broad species of bacteria will be important to understand the true utility of the method in the kingdom of microbes.In addition to coupling with transcriptional repressors, dCas9 can be fused with a transcriptional activator to drive target gene expression . This CR68. While these simple fusion proteins are able to activate the expression of reporters or endogenous genes, the potency of these constructs in transcriptional activation is quite modest, about 2-fold to 5-fold on average when using a single sgRNA71. The effectiveness of CRISPRa can be increased by using multiple sgRNAs tiled across the promoter of the target gene, which is tedious and sometimes challenging, as it requires co-delivery of many sgRNAs simultaneously70.In contrast to those in microbes, more CRISPRa tools have been developed for mammalian cells. dCas9 has been fused to various transcriptional activators, including the transactivation domain of NF-κB p65 subunit (p65AD), the Herpes simplex viral protein 16 (VP16), or multiple tandem copies of VP16, such as VP64  fused to VP64  (VPR) in tandem 74. The 75. This system is composed of a modified sgRNA containing two copies of an MS2 RNA hairpin (from the MS2 bacteriophage). Each MS2 hairpin recruits a pair of its cognate RNA-binding protein MS2 bacteriophage coat protein (MCP), which is fused with p65AD and heat shock factor 1 (HSF1). When combined with dCas9–VP64, the SAM system is shown to robustly activate endogenous coding and non-coding genes and has been employed for genome-wide screening for genes that confer resistance to a BRAF inhibitor75.A third approach is to use sgRNAs as scaffolds to recruit multiple transactivators that can function synergistically in enhancing the activation of endogenous genes. This method is referred to as the synergistic activation mediator (SAM) system 75. This76. Moreover, these systems function effectively in a variety of mammalian cell types, including human, mouse, andDrosophila. Attempts to further enhance efficiency by combining elements from VPR, SAM, and SunTag have been unsuccessful, suggesting that our understanding of the synthetic activation of endogenous genes in the genome is still limited76. Next-generation CRISPRa systems should incorporate novel activation domains, very likely by combining them with synergistic epigenetic modifiers to drive highly effective gene activation.While these CRISPRa systems all exhibit significant enhancement in terms of target gene activation efficiency compared to dCas9–VP64 fusion, systemic comparisons reveal their ability to robustly activate gene expression in a range between 10-– and 1,000-fold depending on the specific gene being perturbed81. Modifications of the chromatin DNA or associated histones are correlated with distinct transcription states and disease phenotypes. For instance, promoters with silenced transcription exhibit distinct methylation or acetylation marks , while promoters with active transcription are associated with other unique patterns of modifications (e.g. histone acetylation or histone H3 lysine 4 [H3K4] methylation). Tools that allow us to precisely modify epigenetic marks at a given locus will be critical for understanding the basic and translational epigenetics. Since CRISPR–dCas9 allows for highly specific genomic targeting, its site-specific recruitment of chromatin-modifying epigenetic enzymes has been tested for sequence-specific epigenome editing (Epigenetic modifications of the genome provide an important mechanism for heritable gene expressionediting .82. Decreased expression of target genes is correlated with reduced levels of H3K4 dimethylation (H3K4me2) and H3K27 acetylation (H3K27ac) near the enhancer regions. Loss of expression of these pluripotency maintenance genes eventually causes morphological changes in embryonic stem cells82. Interestingly, the dCas9–KRAB fusion protein can also induce the repressive trimethylation of H3K9 (H3K9me3) when targeted to the HS2 enhancer of the human beta-globin locus, thereby inhibiting the expression of globin genes83.By coupling histone demethylase LSD1 with dCas9, this fusion protein is able to effectively repress pluripotency maintenance genes (e.g. Oct4 and Tbx3) by using sgRNAs to target the enhancer regions of these genes in mouse embryonic stem cells84. Furthermore, integrating the catalytic domain of histone methyltransferase PRDM9 with dCas9 or zinc finger (ZF) proteins has been shown to increase the level of trimethylated H3K4 (H3K4me3) and reactivates silenced target genes in mammalian cells85. The maintenance of the reactivated state, however, is strongly dependent on the DNA methylation status of the CpG islands at their promoters. For example, gene re-expression achieved by targeted epigenetic editing can be maintained in DNA hypomethylated loci (e.g. PLOD2 in C33a cells), in contrast to transient reactivation observed in hypermethylated loci (e.g. EpCAM in HeLa cells). Stable gene reactivation depends on the presence of methylation marks on histone H3 lysine 79 (H3K79me), which is required for the stability and maintenance of H3K4me3. Epigenetic editing to enrich H3K4me3 by dCas9–PRDM9 and H3K79me by dCas9–DOT1L is able to sustain gene reactivation in a hypermethylated locus when DNA methyltransferase is inhibited85.For activating epigenetic modifications, the catalytic domain of the human acetyltransferase p300 has been fused to dCas9, which is able to increase the level of H3K27ac at the enhancer and promoter of targeted genes, resulting in their transcriptional activation89. The dCas9–TET1 fusion can demethylate 30 to 60% of the CpG islands at tested promoters, which drives the transcriptional activation of target genes in various cell types including embryonic stem cells, cancer cell lines, fibroblasts, and primary neurons89. Alternatively, tethering of the full-length or catalytic domain of DNA methyltransferase 3A (DNMT3A) to dCas9 is shown to induce methylation of the CpG islands at a range of 30 to 50% of the sgRNA-targeted genomic loci, thus leading to reduced expression of those targeted genes in various cell types91. Interestingly, triple recruitment of DNMT3A, DNMT3L, and KRAB via different fusion constructs is able to achieve up to 100% of methylation of the CpG islands and results in stable loss of expression of the targeted genes92. Gene silencing mediated by co-recruitment of such epigenetic modifiers is resistant to external transcriptional activation stimuli, for instance dCas9–VP160 or dCas9–p300, but can be reversed by targeted DNA demethylation mediated by dCas9–TET192.Gene expression can also be modulated by dCas9-based regulation of DNA methylation. Fusion of the catalytic domain of the DNA demethylase TET1 to dCas9 can induce targeted DNA demethylationTogether, these studies have demonstrated how to utilize dCas9-based epigenetic modifiers for locus-specific epigenetic editing in mammalian cells. In the future, it will be intriguing to investigate how epigenetic modifications alter local genomic structure. Meanwhile, further expanding and combining novel epigenetic modifier tools may serve as the key to improve regulatory controls of endogenous gene expression. The dCas9 epigenetic editing toolkit will become a key component for understanding the relationship between chromatin states, gene regulation, and cellular phenotypes.One of CRISPR–dCas9’s unique strengths is its ability to regulate the expression of multiple genes in a simultaneous and inducible manner. Novel regulatory approaches that combine Cas9 or dCas9 with optogenetics, chemical biology, RNA, and protein engineering have been created to facilitate the dynamic and spatiotemporal control of target genes .94. By decoupling dCas9 from its transcriptional effector (e.g. VP64 or p65AD) and fusing each member to a light-inducible heterodimerizing pair of proteins (e.g. CRY–CIB system), effectors can be recruited to dCas9 to activate endogenous genes in a rapid and reversible manner upon exposure to blue light  and FKBP rapamycin binding (FRB) , thereby permitting the precise regulation of CRISPRi activity by this drug96.For instance, an optogenetic transcriptional control system can be integrated into CRISPR–dCas9e light . Furtherg (FRB) . In the 99. For instance, Cas9 fromStreptococcus pyogenes andNeisseria meningitidis displays distinct patterns in its recognition of target sequences and therefore can mediate independent transcriptional repression and nuclease activity97. Furthermore, orthogonal dCas9 regulators that utilize multiple chemically induced dimerization systems have been developed to allow the temporal control of gene regulation101. In a screen of chemical- and light-inducible heterodimerization systems to control the association of dCas9 with effectors, the potent chemical inducers abscisic acid (ABA) and gibberellin (GA) were shown to mediate efficient gene activation and repression in mammalian cells100  to offer fine-tuned control of the targeted gene’s regulation103  to expand the utility of CRISPR–dCas9 systems . The scRion103 . Additio3 111, engineered allosteric protein or RNA switches, and novel optogenetic or chemogenetic systems have also been applied to the CRISPR–Cas9 method for gene editing for the purpose of generating conditional gene knockouts and for reducing the levels of off-target effects119. Expanding these approaches to the CRISPR–dCas9 systems will likely result in new features of regulation for dCas9-based control of gene expression.Approaches such as using split Cas9 variants124. A number of genome-targeting technologies such as ZF proteins128 or transcription activator-like effector nucleases (TALENs)135 have been devised for gene-editing applications, which are achieved by fusing endonuclease catalytic domains with modular DNA-binding proteins to induce DSBs at the targeted genomic loci. Targeting strategies based on protein–DNA interaction using ZF and TALENs can also be applied for gene regulation or epigenome medication when coupled to the transcriptional repressor, activator, or epigenetic modifiers mentioned earlier. Compared to these targeting techniques, CRISPR–dCas9-based gene regulation systems are easier to design, highly specific and efficient, cost effective, and well-suited for high-throughput and multiplexed gene regulation across many cell types and organisms. Nevertheless, limitations do exist for CRISPR–dCas9-based gene regulation systems depending on the application of interest. For instance, RNAi-mediated gene silencing and/or ORF overexpression techniques can be applied to study the function of gene splice variants. Comparisons of CRISPRi/a versus existing common gene repression or activation systems are summarized inThere are several existing methods for gene repression, gene activation, and epigenome modification. For example, techniques based on RNA interference (RNAi), which consists of small interfering RNAs (siRNA) or short hairpin RNAs (shRNA), allow for sequence-specific repression of endogenous genes of interest in eukaryotic organisms. This gene silencing effect is mediated by transcript-specific degradation due to Watson–Crick base-pairing between mRNA and siRNA or shRNA (for reviews, see75. Integrating the dCas9 transcriptional or epigenetic tools with tools based on Cas9 gene editing, RNAi tools on the RNA level, and other molecular tools will undoubtedly constitute the next-generation toolkit for controlling inheritance and the central dogma. We imagine the diversity, plasticity, and flexibility of CRISPR–dCas9 systems will allow researchers to develop more advanced genome-engineering tools for a wide range of applications in basic research and translational medicine.The discovery of CRISPR–Cas as an RNA-guided DNA endonuclease system has inspired the development of revolutionary gene editing tools that allow for studying the function of the genome on a cellular and organismic level. In addition to the complete loss-of-function perturbations made possible by nuclease Cas9, the development of dCas9-based CRISPRi and CRISPRa technologies has enabled reversible, multiplexed, and loss- and/or gain-of-function studies of genes of interest. Furthermore, the ability to site-specifically target chromatin modifiers fused to dCas9 will contribute to our understanding of epigenomic regulation. Genome-wide screening based on CRISPR–dCas9 systems are helping to untangle complex biological processes and identify key genetic players of diseases


Nrl is nearly indistinguishable from that of native cones, indicating that Nrl is required for selective chromatin closure in rods. Finally, we identified distinct enrichments of transcription factor binding sites in rods and cones, revealing key differences in the cis-regulatory grammar of these cell types. Taken together, these data provide insight into the development and maintenance of photoreceptor identity, and highlight rods as an attractive system for studying the relationship between nuclear organization and local changes in gene regulation.Rod photoreceptors are specialized neurons that mediate vision in dim light and are the predominant photoreceptor type in nocturnal mammals. The rods of nocturnal mammals are unique among vertebrate cell types in having an ‘inverted’ nuclear architecture, with a dense mass of heterochromatin in the center of the nucleus rather than dispersed clumps at the periphery. To test if this unique nuclear architecture is correlated with a unique epigenomic landscape, we performed ATAC-seq on mouse rods and their most closely related cell type, cone photoreceptors. We find that thousands of loci are selectively closed in rods relative to cones as well as >60 additional cell types. Furthermore, we find that the open chromatin profile of photoreceptors lacking the rod master regulator  Rho) and mediate vision in dim lightOpn1sw and Opn1mw, respectively) and mediate bright light vision as well as color vision2Photoreceptors are light-sensitive neurons that express opsins tuned to specific wavelengths of light. In the mouse retina >95% of photoreceptors are rods, which express rhodopsin  and their target genes11Emerging evidence indicates that the three-dimensional organization of chromatin within the nucleus is essential for regulating gene expression57Lbr) and lamin A/C (Lmna)14Otx2 and Crx—whose binding specificity is determined, in part, by a lysine (K) in position 50 of the homeodomainOtx2 provides a necessary signal for photoreceptor specification17Otx2 then directly activates Crx (first detectable at E12.5), which is also required for photoreceptor maturation1920Crx−/− retinas has shown that Crx regulates additional photoreceptor TFs as well as components of the phototransduction machinery22Crx−/− photoreceptors lack outer segments and fail to respond to lightCrx at the core of the photoreceptor transcriptional network.At the molecular level, the inverted nuclear organization of rods depends on the silencing of key nuclear envelope proteins, including lamin B receptor  Nr2e332EsrrbMef2cThe decision for a photoreceptor progenitor to differentiate into a rod versus a cone photoreceptor is driven by the TF Expression profiling of wild-type and TF mutant mouse retinas has rapidly advanced the understanding of how photoreceptor TFs are organized into regulatory networks23282936assay for transposase accessible chromatin using sequencing (ATAC-seq)Nrl−/− photoreceptors. In addition, we performed RNA-seq on flow-sorted rods and Nrl−/− photoreceptors, in order to correlate changes in chromatin accessibility with changes in gene expression. Strikingly, we find that mouse rods display a global reduction in open chromatin , and that this reduction depends on Nrl. Through comparative analysis of these datasets, we define thousands of photoreceptor class- and subtype-specific candidate CREs, and we find that distinct subsets of these elements are enriched for different sets of transcription factor binding sites (TFBSs). Taken together, these data reveal that Nrl mediates a uniquely closed chromatin architecture in rods, and they provide a framework for elucidating the cell type-specific cis-regulatory grammar of rods and cones.To begin to elucidate the epigenomic landscape of individual photoreceptor subtypes, we utilized the Nrl-eGFP mice (Opn1mw-eGFP mice (Nrl−/− photoreceptors (putatively blue cones) from Nrl−/−; Nrl-eGFP mice   on dissociated retinas harvested from 8-week-old mice harboring transgenic reporter constructs . SpecifiGFP mice 28, nativGFP mice 43, and NGFP mice 28. We peRNA-seq) .Rho (rod-specific), Opn1mw (cone-specific), and Opn1sw (cone-specific)  . In genepecific) 383940. Tic genes . While wic genes . This muAlthough the majority of mouse retinal cells are photoreceptors, we hypothesized that many previously identified whole-retina DNase-seq peaks derive from non-photoreceptor cell types. To compare the chromatin accessibility profiles of flow-sorted photoreceptors and whole retina, we first merged peak calls from cell type-specific ATAC-seq  and wholNrl−/− photoreceptors were nearly indistinguishable, indicating that the well-described cone-like features of Nrl−/− photoreceptors2530Nrl−/− photoreceptors preferentially express the short-wavelength opsin (Opn1sw), we will henceforth refer to these cells as ‘blue cones’.We also found that the open chromatin profiles of green cones and In our global comparison of rod and cone open chromatin profiles, we noted a significant excess of cone-specific open chromatin relative to rods , red boxNrl−/− photoreceptors, in contrast, these rod-closed regions are open to a similar extent as in other tissues, demonstrating that Nrl is necessary for the global chromatin closure phenotype in rods.To quantify this observation, we examined the distribution of open chromatin signal (ATAC-seq or DNase-seq reads) across the mouse genome in 64 additional cell types and tissues . We diviWe next asked if global differences between the accessible chromatin landscapes of rods and cones were correlated with changes in gene expression. To address this, we mapped individual rod and blue cone ATAC-seq peaks to the nearest transcription start site (TSS) and examined the expression of the corresponding gene  and S6. Lbr) or lamin A/C (encoded by Lmna) is required to maintain a conventional nuclear architecture in non-rod cell typesLbr locus harbors a single open chromatin peak overlapping the TSS, with comparable ATAC-seq signal in rods, green cones and blue cones  and “enhancers” (>1 kb upstream or >100 bp downstream of the nearest TSS), in light of work demonstrating that cell type-specific regulatory elements are preferentially enriched among TSS-distal elementsTo identify TFBSs enriched in photoreceptor ATAC-seq peaks, we tested 319 known sequence motifs curated by the HOMER suite of sequence analysis tools for overrepresentation  and S846128GG), NR (AGGTCA), GATA (GATA), and bZIP (TGANTCA) families. The enrichment of non-CRX binding sites is of considerable interest, as it suggests that specific TFs may cooperate with CRX to shape the regulatory activity of photoreceptor-specific CREs. RAX, for example, is the most highly expressed Q50 HD TF (which has glutamine [Q] in position 50 of the homeodomain) in both rods and cones. It has recently been shown that RAX plays an important role in photoreceptor development and is essential for the survival of mature conesWhile CTCF and CRX were by far the most enriched motifs in photoreceptor open chromatin, we also observed modest enrichments of additional motifs that again corresponded to binding sites recognized by well-characterized photoreceptor TFs . These iMotifs overrepresented in photoreceptor ATAC-seq peaks were enriched for co-occurrence  , suggestin vivo  (in vitro studies have shown that CRX exhibits a strong preference for the consensus CTAATCCC3ATTA), a well-known dimer configuration of HD TFs533CTTA or TAAT[N]3CTTA). This finding indicates that, in certain contexts, the fourth position of the TAAT homeodomain core tolerates a ‘G’ better than would be expected from quantitative gel shift assaysde novo motif, they were highly enriched for the canonical CRX monomer motif (CTAATCC), the 3′ G variant (CTAAGCC), as well as homotypic (TAAT[N]3ATTA or TAAG[N]3CTTA) and especially heterotypic (TAAT[N]3CTTA) dimer configurations  . While purations .cis-regulatory activity of individual photoreceptor CREs (3CTTA), or heterotypic dimeric (TAAT[N]3CTTA) k-mers. However, we did observe a significant repressive effect for the homotypic TAAT dimer configuration (TAAT[N]3ATTA)  . FurtherN]3ATTA) . Accordi3ATTA CRX motifs, we asked if additional motifs enriched in photoreceptor open chromatin contributed to photoreceptor CRE activity. Consistent with the original analysis by White et al., we did not observe significant differences in reporter activity among endogenous CRX-bound sequences due to the presence or absence of CRX sites, suggesting the importance of additional sequence features and context  photoreceptor-specific peaks were enriched for the factors discussed above . InteresIn this study, we presented genome-wide maps of open chromatin and gene expression in individual photoreceptor subtypes. These data revealed a striking depletion of accessible chromatin in rods relative to cones and other cell types, which we hypothesize is related to the unique nuclear organization of rods. Furthermore, we leveraged cell type-specific open chromatin maps to identify sequence features that define shared photoreceptor-specific, rod-specific, and cone-specific regulatory elements.5–106 bp) domains and biased towards gene-sparse regions of the genome with lower transcriptional activity in photoreceptors. Thus, while inverted nuclear organization may reflect selection for certain optical properties, precisely how the nucleus is re-packaged may be additionally constrained by the gene expression programs essential for photoreceptor function.The inverted nuclear architecture of the rods of nocturnal mammals is thought to enhance visual sensitivity in dim light environmentsLbr and LmnaLmna transcript present in adult cones but not rods, suggesting that rods selectively inhibit Lmna transcription. In addition, we find two open chromatin peaks (candidate regulatory elements) at the Lmna locus that are selectively closed in rods. We note that these peaks are open in both endogenous cones and Nrl−/− photoreceptors, indicating that Nrl mediates selective closure of these elements, though additional experiments are needed to determine if this is a direct or indirect effect. Nevertheless, these observations constitute a first step towards localizing changes in the expression of key nuclear envelope genes within rod-specific gene regulatory networks.An important outstanding question with respect to inverted nuclear architecture is how it is regulated. As described above, previous work has shown that rod nuclear organization depends on silencing the nuclear envelope proteins Nrl results in a partial conversion of rods into cones and can delay photoreceptor degeneration in a mouse model of retinitis pigmentosaNrl knockout. It will be interesting to determine whether the dynamics of chromatin closure in developing rods temporally correlates with the acquisition of resistance to reprogramming observed in our prior study. Furthermore, if rod-specific chromatin closure is indeed related to the cell’s inverted nuclear architecture, adult human rods, which have a conventional chromatin architecture, may prove more responsive to direct reprogramming strategies than mouse rods.We previously showed that acute knockout of et al. also evaluated the cell type-specific epigenomic profile of mouse rodset al. identified differential DNA methylation in rods and cones, which revealed a striking rod-specific enrichment of hypomethylated DNA in closed chromatin. Mo et al. suggest that many of these regions represent ‘vestigial enhancers’—regulatory elements active earlier in development that retain hypomethylation marks in adult cell types despite loss of activityNrl is required for chromatin closure in rods, Mo et al. also profiled Nr2e3−/− retinas, which demonstrate an intermediate epigenetic phenotype between that of Nrl−/− and WT retinas. This finding suggests that rod-specific nuclear organization depends at least in part on TFs downstream of Nrl.Recently, Mo In addition to defining the genome-wide chromatin accessibility profile of individual photoreceptor subtypes, our analysis suggests a simple taxonomy of photoreceptor regulatory elements based on TF motif content and their proximity to genes. Consistent with previous work, we found that promoters and enhancers are distinct with respect to size, sequence content and specificity. In particular, promoters tend to be shared across cell types and are enriched for binding sites corresponding to ubiquitous transcriptional regulators, whereas enhancers exhibit greater cell type specificity and are enriched for binding sites corresponding to photoreceptor TFs. Furthermore, enhancers are highly enriched for CTCF binding sites, most of which are shared with non-photoreceptor cell types (likely reflecting ubiquitous TADs), though some are photoreceptor-specific . Enhancers containing CTCF motifs were largely devoid of motifs for photoreceptor TFs, whereas enhancers without CTCF motifs are highly enriched for the latter. Taken together, these findings suggest that CREs can be divided into three classes: promoters, CTCF-bound enhancers, and non-CTCF-bound enhancers. We suggest that this tripartite classification is applicable to other cell types.Six6 is expressed at markedly higher levels in adult cones than in rods. While Six6 is essential for retinal development in vertebrates6061Six6 has not been described in mammals. Nevertheless, Six6 has been shown to mediate photoreceptor differentiation in medakaSix7, has recently been shown to regulate cone-specific gene expression and survival in zebrafish64Six6 plays an analogous role in mouse cones.With respect to non-CTCF-bound enhancers, our motif enrichment analysis identified a set of candidate TFBSs that extend the ‘vocabulary’ of photoreceptor regulatory elements beyond K50 HD (CRX) binding sites, suggesting key roles for Q50 HD, bHLH, NR, MADS, MAF and bZIP TF family members. In parallel, our expression analysis identified TFs that were robustly expressed in rods and/or cones that likely bind these motifs. With respect to K50 HD TFs, we noted that Drosophilacis-regulatory logic to control photoreceptor subtype-specific expression. Such analyses in primary photoreceptors (both in culture and in vivo) are now possible given recent innovations in sequencing-based multiplex reporter assays525568In addition to identifying binding sites for TFs that likely cooperate with CRX, our analysis suggests that CRX binding sites themselves harbor considerable complexity, including both monomeric and dimeric configurations with distinct nucleotide preferences. That key photoreceptor enhancers contain multiple K50 HD sites capable of binding CRX dimers has been shown previously22in vivo—either autonomously or in combination with non-cell type-specific bZIP TFs.We note that while nearly all motifs enriched in photoreceptor enhancers corresponded to known photoreceptor TFs, we were unable to unambiguously assign the cone-specific enrichment of non-MAF bZIP motifs (TGANTCA) to a candidate regulator. Nevertheless, we suggest that NRL might mediate selective closure of these elements in rods, given that bZIP TFs, including NRL, bind DNA as flexible homotypic or heterotypic dimers that tolerate a range of binding sites. NRL in particular has been shown to bind non-MAF bZIP sites as a heterodimer with either Fos or Juncis- and trans-acting factors.Overall, the patterns of motif enrichment we describe yield comprehensive, single-nucleotide resolution maps of regulatory sequence features that can inform functional studies of photoreceptor-specific enhancer activity. These data suggest that—even when comparing highly related cell types—cell type-specific regulatory activity is encoded by complex interactions among shared and cell type-specific TFs acting cooperatively and/or competitively to bind target sequences. Thus, a complete understanding of cell type-specific regulatory logic will likely require an integrated analysis of both 2 inhalation and cervical dislocation) were conducted in accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, and were approved by the Washington University in St. Louis Institutional Animal Care and Use Committee.Mouse husbandry and all procedures (including euthanasia by CORetinas were harvested from adult (8-week-old) mice, fixed in 4% paraformaldehyde in phosphate buffered saline (PBS) overnight at 4 °C, equilibrated in 30% sucrose in PBS, embedded in Tissue-Tek O.C.T (Sakura), and stored at −80 °C until sectioning. 14 μm cryosections were prepared at −20 °C. Imaging was performed with a Zeiss LSM 700 confocal microscope.Retinas were harvested from adult (8-week-old) male mice unless otherwise noted  and dissATAC-seq was performed as described previouslyLibrary preparation was performed using 5 ng of total RNA. RNA integrity was assessed using an Agilent Bioanalyzer. cDNA was prepared using the SMARTer Ultra Low RNA kit for Illumina Sequencing-HV (Clontech) per manufacturer’s instructions. cDNA was fragmented using a Covaris E210 sonicator using duty cycle 10, intensity 5, cycles/burst 200, time 180 seconds. cDNA was blunt-ended, had an ‘A’ base added to the 3′ ends, and then had Illumina sequencing adapters ligated to the ends. Ligated fragments were amplified for 12 cycles using primers incorporating unique index tags. Replicate libraries from both cell types were pooled in equimolar ratios and sequenced on an Illumina HiSeq 2500 (single-end 50 bp reads) .http://picard.sourceforge.net). Finally, we removed alignments with an insertion size greater than 100 bp to enrich for nucleosome-free reads (NFR).Paired-end ATAC-seq reads were aligned to the GRCm38/mm10 mouse genome assembly using Bowtie2 (v2.2.3) in end-to-end mode with a maximum fragment size of 20002 for each peak for each replicate , specifying a maximum file size of 500 Mbeplicate  and calc2 for each gene for each replicate , using an index prepared for 50 bp reads and the RefSeq gene modeleplicate  and calcFor visualization in the UCSC genome browser, bedgraph files were generated for pooled replicates using HOMER (v4.8), specifying a maximum file size of 500 Mbhttps://www.encodeproject.org/) and processed identically to ATAC-seq data except that single-end reads were used when paired-end reads were not available and alignments were not filtered for NFR reads (insert size <100 bp). Individual datasets and accessions are listed in FASTQ files from DNase-seq datasets generated by ENCODE were downloaded from the ENCODE data portal (https://datashare.nei.nih.gov/nnrlMain.jsp)Nrl−/− CRX ChIP-seq. A single biological replicate of NRL ChIP-seq was run on an Illumina platform . Only this replicate was included in our analysis of NRL ChIP-seq data.FASTQ files from previously generated ChIP-seq datasets were downloaded from GEO and processed identically to ATAC-seq data except that single-end reads were used when paired-end reads were not available, alignments were not filtered for NFR reads (insert size < 100 bp), and peaks were called on ChIP-seq replicates (vs. input control) with MACS2 (v2.1.0) using default parameters and an FDR of 0.01. These data are presented in Nrl−/− photoreceptor ATAC-seq peaks in 5 bp bins distributed over a 2 kb window centered on the nearest TSS (promoter peaks) or peak summits (enhancers).ATAC-seq, DNase-seq, and ChIP-seq read depths as well as phylogenetic conservation (phastCons 60-way vertebrate conservation)For PCA of brain DNase-seq and photoreceptor ATAC-seq, peaks from each cell type were merged into a master list with BEDOPS (v2.4.14)To quantify the global distribution of chromatin accessibility, we partitioned the genome into 50 kb fixed windows and calculated read coverage over these windows for each cell type and tissue using bedtools (v2.24.0)2(fold change) greater than 1 at an FDR of 0.1Nrl−/− photoreceptors were used for differential accessibility analysis, with cone subtypes collapsed to a single level. The results of this analysis were used to partition photoreceptor ATAC-seq peaks into three subsets: “rod-specific” (significantly more open in rods), “cone-specific” (significantly more open in cones), and “shared” .ATAC-seq peaks from each photoreceptor type were merged into a master list with BEDOPS (v2.4.14)Nrl−/− photoreceptor RNA-seq data2(fold change) threshold of 1 and an FDR of 0.05.We used DEseq2 to test for differential expression between rods and cones using per gene read counts for rod and To assess the relationship between the accessibility of individual peaks and the expression of nearby genes, peaks were assigned to genes by nearest TSS. In this way, differential expression of individual genes or the distribution of expression of groups of genes could be putatively associated with ATAC-seq peaks.Enrichment of GO Biological Process term within rod- or cone-specific ATAC seq peaks was performed using GREAT (v3.0.0)de novo motif discovery were performed for photoreceptor ATAC-seq peaks as well as brain, liver, lung and B cell DNase-seq peaks using HOMER (v4.8)de novo motif enrichment results are presented in 2(observed pairs/expected pairs), where the number of expected pairs was estimated from the frequency of individual motifs: expected = (number of peaks with motif 1) × (number of peaks with motif 2)/. The pairwise co-occurrence enrichment matrix was plotted as a heatmap, with rows and columns clustered by Euclidean distance and average linkage. Preferential spacing between highly enriched motifs  was assessed by first centering shared photoreceptor ATAC-seq peaks on individual motifs, and then plotting the density of secondary motifs (using a relaxed log odds threshold of 5) on either strand upstream and downstream of the primary motif.Known motif enrichment and et al.Previously generated CRE-seq data were downloaded from the Statistical analyses were implemented in R (v3.3.0)Accession Codes: ATAC-seq data  and RNA-seq data  have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE83312.How to cite this article: Hughes, A. E. O. et al. Cell Type-Specific Epigenomic Analysis Reveals a Uniquely Closed Chromatin Architecture in Mouse Rod Photoreceptors. Sci. Rep.7, 43184; doi: 10.1038/srep43184 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Arabidopsis HDA9 (a RPD3-like histone deacetylase) in promoting the onset of leaf senescence. We found that HDA9 acts in complex with a SANT domain-containing protein POWERDRESS (PWR) and transcription factor WRKY53. Our genome-wide profiling of HDA9 occupancy reveals that HDA9 directly binds to the promoters of key negative regulators of senescence and this association requires PWR. Furthermore, we found that PWR is important for HDA9 nuclear accumulation. This study reveals an uncharacterized epigenetic complex involved in leaf senescence and provides mechanistic insights into how a histone deacetylase along with a chromatin-binding protein contribute to a robust regulatory network to modulate the onset of plant aging.Leaf senescence is an essential part of the plant lifecycle during which nutrients are re-allocated to other tissues. The regulation of leaf senescence is a complex process. However, the underlying mechanism is poorly understood. Here, we uncovered a novel and the pivotal role of DOI:http://dx.doi.org/10.7554/eLife.17214.001 The leaves of many plants turn yellow in the fall as nutrients are recycled to prepare for the winter months. However, if leaves age and yellow too early, it can limit how much energy the plant can harvest from light. Thus, it is crucial for plants to know when they should start the leaf aging process. This is also important for plant biologists because premature leaf yellowing can reduce both the yield and quality of crop plants.Certain aging-related genes tightly control when and how leaves age. Like in many other organisms, plant DNA is packaged around proteins called histones. As such, one of the ways that plants regulate the activity of their genes is by chemically modifying the DNA or histones to alter how tightly the DNA is packaged. For example, to switch particular genes off, enzymes known as histone deacetylases remove an acetyl group from their histones. However, it is not clear how these enzymes know which genes to modify and how this helps to make sure that leaf aging happens at the appropriate time.Arabidopsis. The experiments show that the HDA9 enzyme plays an important role in ensuring the leaves turn yellow at the right time. Without HDA9, the leaf aging process is delayed. HDA9 also needs the help of another protein called PWR that instructs HDA9 to remove acetyl groups from the histones of specific aging-associated genes in order to switch these genes off.Chen et al. studied a histone deacetylase called HDA9 in a flowering plant named The next challenge is to understand how HDA9 and PWR sense developmental and environmental signals to trigger the histone modifications. It will also be important to decipher how this enzyme works with other regulators to trigger leaf aging at the right time.DOI:http://dx.doi.org/10.7554/eLife.17214.002 SAGs) and transcription factors have been identified , two SIR2 (SILENT INFORMATION REGULATOR 2), and four plant-specific HD2 (HISTONE DEACETYLASE 2) based on sequence similarity and cofactor dependence (SAGs in the loss-of-function mutants (HDACs are highly conserved enzymes in eukaryotes. The flowering plant pendence . Geneticpendence . Certainpendence . Interplpendence . Functiopendence . For inspendence . HDA6 is mutants . HoweverHistone deacetylase 9 (HDA9) is a RPD3 type deacetylase, closely related to mammalian HDAC3 . Previoupwr mutants phenocopy hda9, indicating that this complex is biologically relevant. Furthermore, we demonstrate that PWR is important for HDA9 nuclear accumulation as HDA9 protein level is significantly reduced in the nucleus in pwr mutants. Thus, we propose that PWR acts at multiple levels to regulate HDA9 function. To our knowledge, this is the first genome-wide study on targeting and regulating mechanism for a histone deacetylase in plants. Together, this study reveals an uncharacterized epigenetic complex involved in leaf senescence and provides mechanistic insights into how a histone deacetylase along with a chromatin-binding protein contribute to a robust regulatory network to promote the onset of plant aging.In this study, we report the identification and characterization of a previous uncharacterized repressive complex containing HDA9 and a SANT domain-containing protein POWERDRESS (PWR) as novel regulators of leaf senescence. HDA9 promotes the onset of age-related and dark-induced leaf senescence by regulating the expression of genes involved in senescence. Our genome-wide profiling of HDA9 occupancy reveals that HDA9 directly binds to the promoters of key negative regulators and this binding requires PWR. PWR physically interacts with HDA9 and loss-of-function Arabidopsis transgenic plants expressing HDA9-3xFLAG driven by the native HDA9 promoter in hda9 mutant background  in WT background. Reciprocal IP-MS of PWR-FLAG also purified HDA9 . We generated AG, hda9  and H3K27 (H3K27ac) in vivo . Accordin plants . Given ttylation . We nexted to WT . Consisted to WT , no sign mutants .10.7554/hda9 and pwr, we performed H3K27ac chromatin immunoprecipitation followed by sequencing (ChIP-seq) in hda9 and pwr mutants. Consistent with the immunoblotting, we identified 11,372 and 7687 H3K27ac increased peaks in hda9 and pwr, respectively   , near thctively) . TogetheArabidopsis genes equally into five groups based on their expression levels and correlated them with HDA9 binding. Surprisingly, we found that HDA9 is preferentially enriched in the promoters of active genes but not silent genes  and the HDA9-FLAG complementation plants   . Consistp=0.025) .10.7554/hda9. Dark-induced leaf yellowing was attenuated in the hda9 mutant relative to WT  and decreased expression of senescence downregulated genes (SDGs) , SAG12, and SAG113 in hda9 (hda9 mutant and WT of two week-old young leaves (YL) as well as early senescence (ES) leaves. A previous study identified differential regulation of 3474 SAGs and 2849 SDGs during different stages of leaf senescence (SAGs (1023 out of 3474) increased in senescing leaves of both hda9 and WT compared to the young leaves (hda9 compared to WT (SDGs (20% of 2849) were impaired in hda9 senescing leaves  response genes known to promote the onset of leaf senescence, were significantly downregulated (The onset of leaf senescence is often accompanied by increased expression of senescence-associated genes (s (SDGs) . Consist in hda9 . To furtnescence . Althougg leaves , the foled to WT . Similarg leaves , suggestegulated , furtherhda9 early senescent leaves compared to WT (hda9. We found 222 genes (~28%) were shown to be bound by HDA9 and significantly upregulated in hda9   . Interes0) (hda9 . Similar0) (hda9  and maiz0)   and 354 out of 656 downregulated genes (54%) showed up- or downregulation in pwr, respectively  . Of the ectively . The numectively , indicatn in pwr . Besidesd in pwr . All togd in pwr  support APG9, WRKY57, and NPX1 where HDA9 are enriched   . Togethepwr mutation induced global H3K9 and H3K27 hyperacetylation  are directly targeted and repressed by HDA9  and CATALASE3 . Another difference is that our HDA9 affinity purification and MS analysis failed to detect Pol II subunits, which were reported to associate with HDAC in mammals  has been well studied , its rolhda9 mutants according to our RNA-seq analysis  was used as wild type (WT) for all experiments. The T-DNA insertion lines of hda9 (SALK_007123) and pwr (SALK_071811C) were obtained from the Arabidopsis Biological Resource Center (ABRC). Seeds were sown in soil and kept at 4°C for 2 days before transferring to 24 hr constant light at 22°C.WRKY53 was amplified and cloned into GST tagged protein expression vector pGOOD, modified from pGEX-6P by adding 6XHIS tag at the C terminus. Genomic DNA of PWR and HDA9 with their 1 kb promoters were amplified and cloned into pENTR/D-TOPO. These constructs were recombined into the pEarleyGate302 binary vectors  of 10-day-old seedlings and leaves of early senescent plants (ES) grown in constant light at 22°C. Total RNA was extracted with Trizol reagent (ThermoFisher) and treated with DNase I (NEB). One microgram RNA was reverse-transcribed into cDNA with SuperScript III (ThermoFisher) followed by quantitative PCR assay with SYBR Green Master Mix using CFX96 Real-Time System 690 . Relative transcript level to T method . DetaileFLAG and HA epitope tags were detected with horseradish peroxidase (HRP) conjugated anti-FLAG  and anti-HA , respectively. The α-tubulin antibody is from cell signaling (3878). The following histone antibodies were used: H3K9ac , H3K27ac , H3ac , H3 , H4K8ac , H4K12ac , H4K16ac , H4ac , H4 . All western blots were developed using ECL Plus Western Blotting Detection System .Arabidopsis reference genome (TAIR10) using Bowtie2 (v2.1.0) with default parameters. Reads that mapped to identical positions in the genome were collapsed into one read. Tophat (2.0.8b) and Cufflink (2.1.1) were used for differential expression analysis (http://bioinfo.cau.edu.cn/agriGO/). MACS (1.4.2) was used for peak calling with p=1e-03. BEDTools (2.17.0) and custom PERL scripts were used for further analysis. Increased H3K27ac peaks were identified by calling peaks in hda9 or pwr over WT with p=1e-03. In HDA9 binding profiling, log2 value of normalized HDA9 ChIP reads divided by WT reads was calculated and binned in 100 kb intervals. DNase I hypersensitive (DH) sites were from  and the Ovation Ultralow DR Multiplex System , respectively. Libraries were sequenced on a HiSeq2000 in the UW-Madison Biotechnology Center. Reads were aligned to the analysis . The genere from . All sta2, 5 mM EDTA, 0.6% Triton X-100, 0.4 mM PMSF, and protease inhibitor cocktail tablet ) with 1% formaldehyde for 20 min at room temperature. The homogenate was filtered through two layers of miracloth  and pelleted by centrifuging at 4000 rpm for 25 min at 4°C. The pellet was washed with Nuclei Isolation Buffer II , then resuspended with Nuclear Lysis Buffer  and kept on ice for 10 min. The lysates was diluted 10-fold with ChIP Dilution Buffer  and sheared by sonication. After centrifugation at 5000 rpm for 10 min, the supernatant was incubated with 5 μg antibody and 40 μl magnetic protein A/G beads (Life Technologies) overnight with rotation at 4°C. After sequential washes with Low salt Buffer , High Salt Buffer , LiCl Buffer  and TE Buffer , the DNA-protein complex was eluted with ChIP Elution Buffer  and reverse cross-linked at 65°C for over 6 hr. After proteinase K and RNase treatment, DNA was purified by standard phenol–chloroform method for qPCR. Antibodies used in histone acetylation ChIP were the same as used in western blot.Histone ChIP was performed as previously described . A two-g2, 5% Glycerol, 0.1% NP-40, 1 mM PMSF, and protease inhibitor cocktail tablet) and sheared by sonication. After centrifugation at 5000 rpm for 10 min, the supernatant was incubated with Anti-FLAG M2 magnetic beads  overnight with rotation at 4°C. After wash with IP Binding Buffer containing 500 mM NaCl, the protein-DNA complex was eluted with ChIP Elution Buffer and reverse cross-linked at 65°C for 6 hr. After proteinase K and RNase treatment, DNA was purified by standard phenol–chloroform method for qPCR analysis or sequencing.HDA9-FLAG and PWR-FLAG ChIP were slightly modified from . After centrifugation at 10,000 g for 15 min, the supernatant was incubated with anti-FLAG M2 magnetic beads  with rotation at 4°C for 3 hr. The bead-bound complex was washed 4 times with IP Binding Buffer at 4°C for 5 min each. Bound protein was released by two 10 min incubations with Elution Buffer  containing 150 ng/μl 3×FLAG peptide . The eluted protein complexes were precipitated with trichloroacetic acid, further digested with Trypsin, and analyzed on an Orbitrap mass spectrometer .Affinity purification and mass spectrometry analysis of HDA9-FLAG and PWR-FLAG were performed as previously described . ApproxiHPLC separation employed a 100 x 365 μm fused silica capillary micro-column packed with 20 cm of 1.7μm-diameter, 130 Angstrom pore size, C18 beads (Waters BEH), with an emitter tip pulled to approximately 1 μm using a laser puller (Sutter instruments). Peptides were loaded on-column at a flow-rate of 400 nL/min for 30 min and then eluted over 120 min at a flow-rate of 300 nl/min with a gradient of 2% to 30% acetonitrile, in 0.1% formic acid. Full-mass profile scans were performed in the FT orbitrap between 300–1500 m/z at a resolution of 60,000, followed by ten MS/MS HCD scans of the ten highest intensity parent ions at 42% relative collision energy and 7500 resolution, with a mass range starting at 100 m/z. Dynamic exclusion was enabled with a repeat count of two over the duration of 30 s and an exclusion window of 120 s.For data analysis, the acquired precursor MS and MS/MS spectra were searched against a Mus musculus protein database  using SEQUEST, within the Proteome Discoverer 1.3.0.339 software package (ThermoFisher Scientific). Masses for both precursor and fragment ions were treated as mono-isotopic. Oxidized methionine (+15.995 Da) and the gly-gly footprint on lysine (+114.043 Da) were allowed as dynamic modifications and carbamidomethylated cysteine (+57.021 Da) was searched as a static modification. The database search permitted for up to two missed trypsin cleavages and ion masses were matched with a mass tolerance of 10 ppm for precursor masses and 0.1 Da for HCD fragments. The output from the SEQUEST search algorithm was validated using the Percolator algorithm. The data were filtered using a 1% false discovery rate  , based oArabidopsis plants co-expressing HDA9-HA and PWR-FLAG. Total extracts were incubated with 25 µl FLAG magnetic beads for PWR-FLAG purification and the HDA9-HA was detected by using anti-HA-Peroxidase High Affinity 3F10 antibody .Co-immunoprecipitation was performed in 1.5 g F1 GST tag only and GST-WRKY53 proteins were induced with 200 μM IPTG  for three hours at 37°C. HDA9-FLAG protein was purified from HDA9-FLAG transgenic plants using IP methods described above. Purified HDA9-FLAG and GST tagged protein were incubated in the pull down buffer  for one hour then incubated with Glutathione Sepharose 4B beads  for one hour at 4°C. After washed with pull down buffer for three times with 5 min per wash, protein-bead complex was boiled in SDS loading buffer, subjected to SDS-PAGE gel, and detected with anti-GST and anti-FLAG antibodies.hda9 and HDA9-FLAG/hda9 pwr plants were used. Nuclear-cytoplasmic fractionation of HDA9-FLAG was performed as previously described  and two reviewers, one of whom is a member of our Board of Reviewing Editors. The reviewers have opted to remain anonymous.Thank you for submitting your work entitled "POWERDRESS recruits HISTONE DEACETYLASE 9 to chromatin to promote ageing in eLife.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in As you will see, both of the reviewers expressed concerns about how the data were interpreted in the manuscript, as well as the lack of supporting evidence for some conclusions. The reviewer 1 also pointed out a serious disconnect between the genome-wide data sets and the specific analysis for genes related to leaf senescence. These issues significantly weakened the manuscript.Reviewer #1:The manuscript by Chen et al. used combined biochemical, genomic, genetic and molecular approaches to implicate a SANT domain protein and a histone deacetylase in joint promotion of senescence. In addition, a WRKY transcription factor is implicated in tethering the co-repressor complex to target loci. Regulation of chromatin modifying enzyme activity is a topic of broad general interest of relevance for development and response to the environment alike. My enthusiasm for this study was dampened however by the lack of logical overlap between the individual findings as outlined below.hda9 and pwr mutants and then go on to study in detail the impact of HDA9 and PWR on four genes with a role in leaf senescence . Given that HDA9 binds 8000/24000 loci, the 277 gene list is thus not enriched in HDA9-bound genes. Likewise, the genes upregulated in hda9 mutants are not enriched in HDA9 bound loci.1) My biggest concern is that none of the genome-wide datasets produced are linked to the detailed molecular analyses. The authors identify 277 genes that are upregulated in both T1, NPX1 , 6). Howhda9 mutants. While the latter can be attributed to redundantly acting HDACs, this nevertheless raises the question why HDA9 is present at active loci. Of note, the authors also report a global reduction in two active marks H3K9ac and H3K27ac in hda9 mutants on Westerns. One explanation could be that HDA9 resides at genomic loci in an inactive, latent form that needs to be activated or unblocked to have enzymatic activity. Another possibility is that HDA9 binding may prevent binding of other, more active HDAs, to these loci. In either case, one would expect high levels of H3K9ac or H3K27ac at the HDA9 bound highly expressed loci. This should be tested- either genome-wide or at select HDA9 targets in this category. If indeed H3K9ac and H3K27ac levels are high at HDA9-bound loci, HDA9 binding is not directly linked to altered transcriptional output. A complementary approach, monitoring changes in histone acetylation levels genome-wide in hda9 and pwr mutants relative to the WT, might also help to understand the role of HDA9 in gene regulation.2) This leads me to the second concern. Surprisingly the authors find that –genome-wide – HDA9 binds to actively expressed genes, most of which are not differentially expressed in pwr plants, It seems the authors have tagged PWR plant lines in hand.3) The title claims that PWR recruits HDA9 to chromatin. This conclusion needs further supporting data – for example PWR binding to the same region as HDA9 on HDA9 targets on the basis of ChIP -, given that HDA9-FLA levels are reduced in the nucleus of Reviewer #2:Arabidopsis", the authors identified physical association between histone deacetylase HDA9 and PWR and characterized their function by new genome-wide analysis including ChIP-seq and RNA-seq. These results suggest that PWR recruits HDA9 to its genomic targets and functions to promote leaf senescence associated with age and darkness through transcription factor WRKY53.In the manuscript titled "POWERDRESS recruits HISTONE DEACETYLASE 9 to chromatin to promote ageing in Arabidopsis, and should be of interest for the readers of eLife. Overall the experiments were well designed and executed. The data presented are clear and support their conclusions. However, there are a few issues that should be further clarified before the manuscript is accepted for publication.This manuscript reports a novel function for HDA9 and PWR in regulating leaf senescence associated with age and darkness in hda9∆ RNA-seq analysis, the authors found that 95% of genes bound by HDA9 did not change gene expression when HDA9 is deleted. The authors interpreted it as either HDA9 is not a primary regulator of transcription for the majority of its targets or it is insufficient to regulate transcription. I think that it is most likely that gene expressions are regulated and repressed by multiple redundant or parallel repressors and eliminating one of them is usually not enough to derepress and activate transcription. There are such examples clearly described in yeast between HDAC Rpd3 and chromatin remodeling enzyme Isw2 .1) After the HDA9 ChIP-seq and hda9. In either case, the exact numbers of genes containing the WRKY binding motif should be given with a p-value.2) The authors identified WRKY binding motif in HDA9 target sites. However, it is not clear whether the "target sites" simply means HDA9 ChIP-seq peak or it means those genes that both have HDA9 ChIP-seq peaks and altered gene expression in hda9 and pwr mutants and found substantial overlaps. Fisher's exact test p-values should be given for this analysis to show whether the overlap was significantly higher than by chance.3) The authors compared the up-regulated and down-regulated genes in hda9 by RNA-seq?4) The authors showed four genes in hda9 mutation should show higher chance of PWR binding. This would provide further support for the model if proven true.5) Since the model is PWR recruiting HDA9 to target genes, one would predict that genes with both HDA9 ChIP-seq peaks and up-regulated by [Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]Arabidopsis" for further consideration at eLife. Your revised article has been favorably evaluated by Jessica Tyler (Senior Editor), a Reviewing Editor, and 1 reviewer.Thank you for resubmitting your work entitled "POWERDRESS recruits HISTONE DEACETYLASE 9 to chromatin to promote aging in The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined in the review below. Point 1 cannot really be addressed, however, given your response to the previous comments and the clarification of candidate gene selection criteria now added to the manuscript, it will be fine to leave it as is. Please pay attention to address the points 2 and 3 in your revision.Reviewer #2:The revised manuscript is much improved by the additional data included.I have a couple of comments and clarifications for the points I had raised before.1) Overlap of genome-wide and gene-specific analyseshda9) and one of the two is also upregulated in pwr mutants (NPX1).The new logic presented in hda9 and pwr mutants there is perhaps a stronger increase in H3K27ac at HDA9 bound loci than at nonbound loci. Is that true? This could be tested statistically. One remaining question is how do the changes in H3K27ac in the mutant compared to the wild type link to the changes in gene expression in the same genetic backgrounds? The authors should include a Venn diagram for the overlap between genes bound by HDA9, upregulated in hda9 and genes with significantly increased H3K27ac in hda9. This is very easily done with the available data.2) Role of HDA9 at active loci. Adding the H3K27ac ChIPseq strengthens the manuscript and, in particular, helps solidify the link between PWR and HDA9. In addition, HDA9 bound genes have higher H3K27ac than nonbound genes, supporting the idea that HDA9 resides at active loci. In Also, I apologize for a typo in my comment: should have read " a global increase in two active marks".pwr (HDA9-FLAG hda9 pwr3) PWR recruits HDA9. The additional PWR ChIP data is nice. However, the authors need to rephrase their conclusions. Nuclear HDA9 levels are reduced in  [Editors’ note: the author responses to the first round of peer review follow.][…]As you will see, both of the reviewers expressed concerns about how the data were interpreted in the manuscript, as well as the lack of supporting evidence for some conclusions. The reviewer 1 also pointed out a serious disconnect between the genome-wide data sets and the specific analysis for genes related to leaf senescence. These issues significantly weakened the manuscript.Reviewer #1:The manuscript by Chen et al. used combined biochemical, genomic, genetic and molecular approaches to implicate a SANT domain protein and a histone deacetylase in joint promotion of senescence. In addition, a WRKY transcription factor is implicated in tethering the co-repressor complex to target loci. Regulation of chromatin modifying enzyme activity is a topic of broad general interest of relevance for development and response to the environment alike. My enthusiasm for this study was dampened however by the lack of logical overlap between the individual findings as outlined below.pwr are direct HDA9 targets, I found that only roughly one third are (91 genes). Given that HDA9 binds 8000/24000 loci, the 277 gene list is thus not enriched in HDA9-bound genes. Likewise, the genes upregulated in hda9 mutants are not enriched in HDA9 bound loci.1) My biggest concern is that none of the genome-wide datasets produced are linked to the detailed molecular analyses. The authors identify 277 genes that are upregulated in both hda9 and pwr mutants and then go on to study in detail the impact of HDA9 and PWR on four genes with a role in leaf senescence . HowNPX1 (AT5G63320) is indeed among the 277 genes that are upregulated in both hda9 and pwr mutants  for further investigation. We have now presented this selection strategy as a new WRKY57, APG9, NPX1) are also upregulated in the pwr mutant. While NPX1 is significantly upregulated , WRKY57 and APG9 are not defined to be significant based on our significance criteria. Thus, we performed RT-qPCR to further confirm their upregulation in pwr with additional biological replicates they RNA-seq ; and c) eplicates.hda9  and pwr  are indeed significant . Our GO analysis of differentially expressed genes in both hda9 and pwr shows their significant enrichment in senescence related pathways  upregulated in both  network . Two-thihda9 are not significantly enriched in HDA9-bound genes. As discussed in this manuscript, 95% of ~8,000 HDA9 binding genes do not exhibit a significant change in gene expression. We have further clarified it in our Discussion section, as illustrated below.We agree with this review that upregulated genes in “Analogous to reports on mammalian and maize HDACs , our ChIP-seq and RNA-seq analyses also reveals that the majority of HDA9 bound genes do not alter gene expression when HDA9 is deleted. […]It is possible that other HDACs (e.g. HDA6 and HDA19) or transcriptional repressors function redundantly with HDA9 to regulate gene expression, and thus loss of HDA9 itself is insufficient to release the transcriptional repression of its targets.”.2) This leads me to the second concern. Surprisingly the authors find that –genome-wide – HDA9 binds to actively expressed genes, most of which are not differentially expressed in hda9 mutants. While the latter can be attributed to redundantly acting HDACs, this nevertheless raises the question why HDA9 is present at active loci. Of note, the authors also report a global reduction in two active marks H3K9ac and H3K27ac in hda9 mutants on Westerns. One explanation could be that HDA9 resides at genomic loci in an inactive, latent form that needs to be activated or unblocked to have enzymatic activity. Another possibility is that HDA9 binding may prevent binding of other, more active HDAs, to these loci. In either case, one would expect high levels of H3K9ac or H3K27ac at the HDA9 bound highly expressed loci. This should be tested- either genome-wide or at select HDA9 targets in this category. If indeed H3K9ac and H3K27ac levels are high at HDA9-bound loci, HDA9 binding is not directly linked to altered transcriptional output. A complementary approach, monitoring changes in histone acetylation levels genome-wide in hda9 and pwr mutants relative to the WT, might also help to understand the role of HDA9 in gene regulation.hda9 and pwr mutants and showed global increase of H3K27ac in both mutants compared to the WT. These new data have been included in the Results section, as illustrated below.As suggested, we generated H3K27ac ChIP-seq in hda9 and pwr, respectively  The title claims that PWR recruits HDA9 to chromatin. This conclusion needs further supporting data – for example PWR binding to the same region as HDA9 on HDA9 targets on the basis of ChIP -, given that HDA9-FLA levels are reduced in the nucleus of pwr induced H3K27 hyperacetylation is correlated with HDA9 binding. These new datahave been included in the Results section, as illustrated below.As suggested, we performed ChIP-qPCR in PWR-FLAG plants. Additionally, we compared the H3K27ac levels of HDA9 bound genes over non-HDA9 bound genes andfound that APG9, WRKY57, and NPX1 where HDA9 is enriched  (“We found that 9 of the 11 randomly chosen HDA9 bound loci showed significant enrichment of PWR . Furtherenriched . […..]To2.2e-16) . TogetheReviewer #2:[…]This manuscript reports a novel function for HDA9 and PWR in regulating leaf senescence associated with age and darkness in Arabidopsis, and should be of interest for the readers of eLife. Overall the experiments were well designed and executed. The data presented are clear and support their conclusions. However, there are a few issues that should be further clarified before the manuscript is accepted for publication.1) After the HDA9 ChIP-seq and hda9∆ RNA-seq analysis, the authors found that 95% of genes bound by HDA9 did not change gene expression when HDA9 is deleted. The authors interpreted it as either HDA9 is not a primary regulator of transcription for the majority of its targets or it is insufficient to regulate transcription. I think that it is most likely that gene expressions are regulated and repressed by multiple redundant or parallel repressors and eliminating one of them is usually not enough to derepress and activate transcription. There are such examples clearly described in yeast between HDAC Rpd3 and chromatin remodeling enzyme Isw2 .We appreciate reviewer’s suggestion and have included this possible mechanism in the Discussion section, as illustrated below.“our ChIP-seq and RNA-seq analyses also reveal that the majority of HDA9 bound genes do not alter gene expression when HDA9 is deleted. Although the mechanism is unclear, several possibilities could account for this pattern. […] It is possible that other HDACs (e.g. HDA6 and HDA19) or transcriptional repressors function redundantly with HDA9 to regulate gene expression, and thus loss of HDA9 itself is insufficient to release the transcriptional repression of its targets.”2) The authors identified WRKY binding motif in HDA9 target sites. However, it is not clear whether the "target sites" simply means HDA9 ChIP-seq peak or it means those genes that both have HDA9 ChIP-seq peaks and altered gene expression in hda9. In either case, the exact numbers of genes containing the WRKY binding motif should be given with a p-value.We apologize for the confusion. We have clarified it in the text that the DNA-binding motifs were identified based on the HDA9 binding sequences. We have also added the p-value in the text as following: “1,328 HDA9 binding peaks  showed the significant enrichment of W-box motif (TTGAC/T), recognized by WRKY family transcription factors , consist3) The authors compared the up-regulated and down-regulated genes in hda9 and pwr mutants and found substantial overlaps. Fisher's exact test p-values should be given for this analysis to show whether the overlap was significantly higher than by chance.As suggested, we have added Fisher’s exact test p-value in 4) The authors showed four genes in hda9 by RNA-seq. We have clarified it in the revised manuscript.Direct targets represent the genes that are bound by HDA9 by ChIP-seq and are upregulated in 5) Since the model is PWR recruiting HDA9 to target genes, one would predict that genes with both HDA9 ChIP-seq peaks and up-regulated by hda9 mutation should show higher chance of PWR binding. This would provide further support for the model if proven true.pwr and compared the H3K27ac levels of HDA9 bound genes over non-HDA9 bound genes andfound that pwr induced H3K27 hyperacetylation is correlated with genome-wide HDA9 binding  Overlap of genome-wide and gene-specific analysesThe new logic presented in Please see our previous responses.2) Role of HDA9 at active loci. Adding the H3K27ac ChIPseq strengthens the manuscript and, in particular, helps solidify the link between PWR and HDA9. In addition, HDA9 bound genes have higher H3K27ac than nonbound genes, supporting the idea that HDA9 resides at active loci. In hda9 and pwr mutants there is perhaps a stronger increase in H3K27ac at HDA9 bound loci than at nonbound loci. Is that true? This could be tested statistically. One remaining question is how do the changes in H3K27ac in the mutant compared to the wild type link to the changes in gene expression in the same genetic backgrounds? The authors should include a Venn diagram for the overlap between genes bound by HDA9, upregulated in hda9 and genes with significantly increased H3K27ac in hda9. This is very easily done with the available data.Also, I apologize for a typo in my comment: should have read " a global increase in two active marks".hda9 and pwr (p<2.2e-16) as presented in Thanks for the suggestions. Indeed, we found that HDA9 bound genes showed a significantly stronger increase of H3K27ac relative to non-HDA9 bound genes in both hda9 RNA-seq, and hda9 H3K27ac ChIP-seq datasets. We noted that 151 out of 222 genes (~68%) that bound by HDA9 and upregulated in hda9 showed significantly increased H3K27ac in hda9 (p=1.2e-10). This new datahas been included in As suggested, we performed the overlap analysis between HDA9 ChIP-seq, 3) PWR recruits HDA9. The additional PWR ChIP data is nice. However, the authors need to rephrase their conclusions. Nuclear HDA9 levels are reduced in pwr (HDA9-FLAG hda9 pwr Arabidopsis”. We have also rephrased the conclusion as illustrated below.We appreciate this comment and have changed the title to “POWERDRESS interacts with HISTONE DEACETYLASE 9 to promote aging in “HDA9 nuclear accumulation and chromatin association are dependent on PWR”.


Higher-order chromatin organization controls transcriptional programs that govern cell properties and functions. In order for pluripotent stem cells (PSCs) to appropriately respond to differentiation signals, developmental gene loci should be structurally and spatially regulated to be readily available for immediate transcription, even though these genes are hardly expressed in PSCs. Here, we show that both chromatin interaction profiles and nuclear positions at developmental gene loci differ between human somatic cells and hPSCs, and that changes in the chromatin interactions are closely related to the nuclear repositioning. Moreover, we also demonstrate that developmental gene loci, which have bivalent histone modifications, tend to colocalize in PSCs. Furthermore, this colocalization requires PRC1, PRC2, and TrxG complexes, which are essential regulatory factors for the maintenance of transcriptionally poised developmental genes. Our results indicate that higher-order chromatin regulation may be an integral part of the differentiation capacity that defines pluripotency. Higher-order chromatin organization regulates the expression of transcriptional programs that control cell function. Here, the authors show that chromatin interaction profiles and nuclear positions at developmental gene loci differ between human somatic and pluripotent stem cells. One prominent aspect of stem cells is their ability to differentiate into other cell types. Specifically, pluripotent stem cells (PSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), can give rise to almost all cell types within an animal’s body. In the pluripotent state, developmental genes are rarely expressed in PSCs, but should be properly transcribed in response to extracellular differentiation cues. Therefore, in order to understand the differentiation ability of PSCs, it is important to know how developmental genes are regulated in order to promptly undergo transcription upon stimulation.5. Bivalent domains have both transcriptionally active (H3K4me3) and repressive (H3K27me3) histone marks, which are independently catalyzed by the trithorax group (TrxG) and polycomb repressive complex 2 (PRC2) complexes, respectively8. Moreover, polycomb repressive complex 1 (PRC1), which has ubiquitin ligase activity, binds to bivalent domains by recognizing H3K27me3 and maintains the inactivation state of developmental genes9. Notably, bivalent domains are frequently occupied by paused RNA polymerase II11, suggesting that bivalency is a mark of developmental genes that are in transcriptionally silent but poised states in PSCs. Most of the bivalent gene loci in PSCs lose either active (H3K4me3) or repressive (H3K27me3) marks upon PSC differentiation1. Conversely, during somatic cell reprogramming, bivalency at developmental gene loci is reestablished in their promoters12. Furthermore, knockout experiments have implied that epigenetic modifiers that establish bivalency might be required for developmental plasticity15. Thus, the regulation of bivalent modification is closely related to the cellular differentiation of PSCs.Epigenetic regulation by histone modification plays critical roles in transcriptional programs that govern various biological processes. In PSCs, distinct histone modification regions, termed as bivalent domains, have been observed in the promoters of many developmental genesNanog, are repositioned from the nuclear periphery to the nuclear interior16, and that the promoter–enhancer looping structure of the pluripotency genes is reorganized before transcriptional activation17, suggesting a crucial role of chromatin interaction during the induction. However, it remains unclear whether higher-order chromatin structures at developmental gene loci are altered during somatic cell reprogramming and how these structures are regulated in PSCs.In addition to histone modifications, higher-order chromatin arrangements through three-dimensional (3D) architecture and subnuclear localization are also key factors for the control of transcription. Previous studies have shown that upon the induction of PSCs, pluripotency gene loci, including 18. These methods quantify chimeric DNA fragments that are derived from proximity ligation events. Among them, circular chromosome conformation capture sequencing (4C or 4C-seq) can identify spatial interactions of a single genomic locus on a genome-wide scale21. Since 4C-seq focuses on one genomic locus as the analysis target, the required total read number for analyzing chromatin interactions with 4C-seq is much smaller than that with the Hi-C method, which detects all combinations of genomic interactions22. However, conventional 4C-seq has some disadvantages in the library preparation, which requires inverse PCR using a circularized 3C library as a template, prior to quantification by massively parallel sequencing. This inverse PCR results in the amplification of DNA fragments that have the same 5′ and 3′ sequences derived from the primers, and the artificial PCR duplicates prevent quantitative analysis of the 4C-seq data. Furthermore, the circular 3C library construction process contains DNA that has been digested with a restriction enzyme ; therefore, it has a potential bias associated with the uneven distribution of the enzyme recognition sequence. In addition, conventional 4C-seq is restricted to one genomic locus and cannot reveal the interaction profiles at multiple regions in parallel.Generally, chromosome conformation capture (3C)-based methods are widely used to determine the physical interactions of distant DNA loci23 chromosome conformation capture combined with high-throughput sequencing (ms4C-seq) by improving upon previously reported 4 C methods25. The ms4C-seq allows simultaneous analysis of chromatin interactions from multiple viewpoints while limiting the effects of PCR and sequence bias. Using ms4C-seq, we examine the genome-wide chromatin interaction profiles of multiple developmental gene loci before and after human somatic cellular reprogramming. Our results demonstrate that the global interaction profiles of developmental genes dynamically change during the reprogramming process. Furthermore, we find that the position of pluripotency gene loci and also developmental gene loci change from the nuclear periphery in somatic cells to the nuclear interior in human PSCs (hPSCs), and these changes are accompanied by changes in the nuclear positions of their interaction target loci. Finally, we show that bivalent promoters have a tendency to colocalize with one another in hPSCs, and that the knockdown of components of PRC1, PRC2, or TrxG complexes disrupts bivalent gene colocalization, thereby suggesting that the histone modification machinery plays an instructive role in higher-order chromatin organization. Thus, our findings illuminate the regulatory mechanisms of developmental genes that are crucial for the cellular differentiation of hPSCs.In this study, to investigate the global chromatin interaction profiles around dozens of developmental gene loci in detail, we develop a multiplexed Splinkerette26. Here, we focused our attention on developmental genes, which are frequently marked in PSCs by both active (H3K4me3) and repressive (H3K27me3) histone modifications, called bivalent domains5. To examine the chromatin interaction profiles of the developmental genes  at high resolution, we tried to perform a 4C- (circularized chromosome conformation capture) based massively paralleled sequenced method (4C-seq). Many versions of 4C-seq have been reported to overcome the disadvantages of 4C-seq described above by introducing several modifications, such as sonication-based fragmentation, adaptor ligation, and multiplexed PCR25. Thus, we combined the beneficial features of those modified methods and developed a version of 4C-seq, termed Multiplexed Splinkerette23 chromosome conformation capture combined with high-throughput sequencing (ms4C-seq)  to characterize chromatin states. In a previous report that applied ChromHMM to nine ChIP-seq plus input ENCODE data across nine cell types28, all human genomic regions  were assigned to 15 chromatin states including a “Poised Promoter” state. Comparison with ChIP-seq data sets29 showed that virtually all the genes whose promoter regions (±250 bp from transcription start sites (TSS)) are categorized into a “Poised_Promoter” state by ChromHmm have both H3K4me3 and H3K27me3 modifications in their promoters. Therefore, hereafter, we designate these genes as “bivalent genes” in PSCs and human fibroblasts (HFs)  because the gene number of the bivalency lost is greater than that of the bivalency reformation during PSC differentiation.To select the baits for our analysis with ms4C-seq systematically, we used publicly available data sets for chromatin-state segmentation determined by ChromHmm35. We performed ms4C-seq for all 89 bait loci on human iPSCs , and for 42 bait loci out of 89 bait loci on their original HFs. Using the data from each bait that met our strict criteria for quality control , lower (category 2), and similar (category 3) expression in hiPSCs than HFs 43, we observed that active and repressive genes were biased to the nuclear interior and periphery, respectively, in both HFs and PSCs  interact with genomic regions with the H3K4me3 modification  genes11. To obtain mechanistic insights into the colocalization of bivalent gene loci, we focused on PRC1, PRC2, and TrxG protein complexes. We introduced small hairpin RNAs (shRNAs) that target RING1B, EED, and WDR5, which are components of the PRC1, PRC2, and TrxG complexes, respectively, into hiPSCs and performed ms4C-seq for eight selected bivalent bait loci to examine the effects of the shRNAs on the interaction profiles  also play a role in recruiting WDR5 to target loci for the methylation of H3K460. Therefore, in addition to histone modifiers, lncRNAs may also mediate the colocalization of bivalent genes.We also showed that histone modifiers contribute to the colocalization of bivalent genes in hPSCs. RING1B and EED, which are components of PRC1 and PRC2, respectively, are essential for the chromatin organization of polycomb-regulated gene loci in mouse PSCsSCs Fig. . Recent 61, and WDR5 is required for ESC self-renewal62. Therefore, the colocalization of bivalent genes that are mediated by histone modifiers may be a critical regulatory event underlying the differentiation and self-renewal capabilities of PSCs.Our knockdown experiments showed that the contribution of RING1B, EED, and WDR5 to the colocalization of bivalent genes varies among baits. These different effects on the colocalization of bivalent gene loci may have several causes, including different cofactors, binding strengths, frequencies, and stabilities of the histone modifiers. Knockout of RING1B and EED derepresses developmental genes in ESCs63, the detailed regulatory mechanisms of higher-order chromatin structures and subnuclear localization at bivalent gene loci should provide insights on early embryogenesis.In conclusion, our present study shows that bivalent gene loci colocalize to the nuclear interior of hPSCs, and that the organization of chromatin 3D structures around bivalent genes is mediated by histone modifiers related not only to inactive but also to active marks Fig. . Because65 were cultured in DMEM/F12 (Thermo Fisher 10565-018) supplemented with 20% knockout serum replacement (Thermo Fisher 10828-028), 2 mM l-glutamine (Thermo Fisher 25030-081), 1× nonessential amino acids (Thermo Fisher 11140-050), 110 mM 2-mercaptoethanol (Thermo Fisher 21985-023), penicillin/streptomycin  (Thermo Fisher 15140-122), and 4 ng per ml of hbFGF (Wako 064-054541) on feeder layers of mitomycin-C-treated SNL-STO cells stably expressing the puromycin resistance gene. HFs (1388 and TIG120) were cultured in DMEM  supplemented with 10% FBS (Japan Bio Serum S1560-500). The mouse SNL-STO cells used as feeder cells were cultured in DMEM  supplemented with 10% FBS (Thermo Fisher 10437-028), 0.05 U per ml of penicillin, and 50 µg per ml of penicillin/streptomycin  (Thermo Fisher 15140-122). All cells were cultured at 37 °C in a 5% CO2 incubator. KhES3 was obtained from Kyoto University. H9 was from WiCell Research Institute. TIG120 was obtained from the Japanese Collection of Research Bioresources. HDF 1388 was purchased from Cell Applications.hESC lines (H9 and KhES3) and hiPSC lines (428C2 and 409B2)66. Target sequences of shRNAs for EED, RING1B, and WDR5 were designed using siDirect (http://sidirect2.rnai.jp/) and cloned downstream of the hU6 promoter of the modified vector  in the presence of 10 μM Y-27632 (Wako 257-00511) on Matrigel (CORNING 356231)-coated 10-cm dishes. Selection with 2 μg per ml puromycin was performed 2 days after transfection. The cells were harvested 4 days after transfection for ms4C-seq analysis, immunoblotting, and quantitative PCR (qPCR) analysis.428C2 cells were washed with 1× PBS, and feeder cells were removed by 3–5 min of incubation in dissociation solution (Repro Cell RCHETP002). The hiPSC colonies were dissociated into single cells by incubation in ACCUMAX (Innova Cell Technologies AM105) at 37 °C for 10 min. To prepare the transfection mix, 6 μg of shRNA expression vector and 6 μg of CAG promoter-driven expression vector of piggyBac transposase were mixed with 540 μl of Opti-MEM (Thermo Fisher 31985-062) and 46 μl of FuGENE HD (Promega E2311). After incubation of the transfection mix at RT for 15 min, 5 × 10RNA was extracted from each cell line with RNeasy Mini Kit QIAGEN 74104). Complementary DNA was synthesized from 100 ng of total RNAs with QuantiTect Reverse Transcription Kit (Qiagen). qPCR analysis was performed with SYBR premix Ex TaqII (Takara) and primer sets (Supplementary Table 04. ComplRNA was extracted from hiPSCs (409B2) and the original HFs (1388) with TRIzol and QIAGEN RNeasy Kit. The total RNA was subjected to cRNA synthesis with 3′ IVT Express Kit (Affymetrix), and the resultant cRNA was fragmented and hybridized to the HG-U133 Plus 2 platform (Affymetrix). After hybridization, GeneChip arrays were washed, stained with GeneChip Fluidics Station 450 (Affymetrix), and detected with Scanner 3000 TG System (Affymetrix) following the manufacturer’s standard protocols. Data analyses were performed with GeneSpringGX 13.0 software (Agilent Technologies).6 cells), which were suspended in 100 μl of CytoBuster Protein Extraction Reagent (BIO RAD 71009-50ML) supplemented with 1× protease inhibitor cocktail (Roche 04 693 159 001) followed by the addition of 100 μl of Laemmli sample buffer (Bio-rad 161-0737) in the presence of 5% 2-mercaptoethanol . SDS–PAGE was performed with 10% gels (Bio-rad 456-1036) or gradient gels (Bio-rad 456-9036) in 1× Tris/Glycine/SDS buffer (Bio-rad 161-0732). The separated proteins were transferred to a PVDF membrane (Bio-rad 162-0174). Target proteins were detected with the following antibodies: anti-EED , anti-WDR5 , anti-RING1B , and anti-GAPDH . Secondary antibodies were Anti-Rabbit IgG, HRP-Linked F(ab′)2 Fragment Donkey , or Anti-Mouse IgG, HRP-Linked F(ab′)2 Fragment Sheep .Cell lysates were prepared from an equal number of cells (0.5–1 × 10GATA4), RP11-102O8 (LGI3), RP11-383B10 (MTUS1), RP11-1083M23 (TWIST1), RP11-815K24 (EGFR), and RP11-614D15 (INHBA). Distances between the bait probe and the positive or negative probes were measured in 180–456 signal pairs from three to five visual fields in a single experiment and the number of colocalized signals was counted. The statistical significance was calculated by Fisher’s exact test.Probes were prepared from BAC clones (BACPAC Resources) by using a Nick Translation Reagent Kit (Abbott Molecular Inc. 32-801300) and labeled with Red 650 dUTP (ENZO ENZ-42522), Red 580 dUTP (ENZO ENZ-42844), or Green 496 dUTP (ENZO ENZ-42837). Nick-translated probes were precipitated with 70% EtOH . The probes were dissolved in 4 µl of formamide that was preheated at 42 °C, denatured at 75 °C for 10 min, and then placed on ice for 3 min. The denatured probes were dissolved in 1× hybridization buffer (2 mg per ml of BSA (Roche 711454), 2× SSC, and 10% dextran sulfate sodium salt (Sigma D8906)). Cells cultured on gelatin-coated chamber slides (Iwaki) were fixed with 4% PFA in PBS at room temperature for 10 min and permeabilized with 0.5% Triton X-100 in PBS at RT for 5–15 min. Permeabilized cells were washed two times with 70% EtOH that was prechilled at −20 °C and dehydrated in 70, 90, and 100% EtOH (v per v) at RT for 5 min each. DNA in the nuclei was denatured in buffer (70% formamide (pH 7.0), 2× SSC) at 80 °C for 5 min. The denatured samples were washed and dehydrated with a gradient of ice-cold ethanol ) for 5 min each. The dissolved probes were hybridized to the samples in a 37 °C wet box for 1–2 days. The samples were then washed three times with 50% formamide/2× SSC solution at 42 °C for 10 min and then washed two more times with 2× SSC solution at 42 °C for 5 min. The nuclei were counterstained with 2 µg per ml of Hoechst at RT for 10 min. FISH signals were detected by using Zeiss LSM710. Z sections that were captured at 0.2-µm intervals. The following BACs were used in these studies: RP11-235I5  at RT for 10 min. The formaldehyde was quenched with 500 μl of 2.5 M glycine and washed twice with 5 ml of ice-cold 1× PBS. Cross-linked nuclei were isolated by incubation in 550 μl of lysis buffer ) on ice for 20 min and homogenization with 10 strokes × 2 by a tight pestle in a dounce homogenizer (Wheaton) on ice. The isolated nuclei were washed twice with 500 μl of 1× cutsmart buffer (NEB B7200S). The formaldehyde was quenched with 500 μl of 2.5 M glycine and washed twice with 5 ml of ice-cold 1× PBS. Cross-linked nuclei were isolated by incubation in 550 μl of lysis buffer ) on ice for 20 min and homogenization with 10 strokes × 2 by a tight pestle in a dounce homogenizer (Wheaton) on ice. The isolated nuclei were washed twice with 500 μl of 1× cutsmart buffer (NEB B7200S). Proximity ligation of the HindIII-digested DNA ends was conducted with 10 U (Weiss unit) of T4 DNA ligase (TAKARA 2011A). 3C DNA libraries were purified by phenol–chloroform extractions  and ethanol precipitation. Precipitated 3C libraries were purified again by using an Invitrogen PureLink Genomic DNA Mini Kit (Thermo Fisher K1820-00). The 3C-qPCR experiments were performed by using a SYBR premix Ex TaqII (Takara) and primer sets  to the A-tailed 3C libraries was performed with Ligation high Ver.2 (TOYOBO LGK-201) at 16 °C for 30 min and 10:1 adapter:library molar ratio. The adaptor-ligated 3C libraries were purified with 1.8× AMPureXP beads. A total of 3.7 μg (230 ng/reaction × 16) of adaptor-ligated 3C libraries served as the template to amplify target loci by PCR amplification. Each PCR was performed in a 50-μl reaction mix (1× Phusion High-Fidelity PCR Master Mix with HF Buffer (NEB M0531S), 50 nM each universal and target primers  with Covaris E210 under the following conditions: duty cycle 5%, intensity 3, cycles per burst 200, and time 150 s. End-repairing and A-tailing were performed by using NEBNext Ultra End Repair/dA-Tailing Module (NEB E7442S) according to the manufacturer’s instructions. Ligation of the Splinkerette adaptor68. Read pairs with the HindIII site “AAGCTT” in the read1 (R1) sequence were used for the following analysis. The R1 sequences were separated into bait sequences and target sequences. To divide the reads into each bait, the former parts from HindIII of R1 were excised as bait sequence and mapped to 47 bait sequences by BWA (bwa-0.6.2)69 by using the default setting. The NANOG pseudogene gene loci were discriminated from NANOG bait loci on the basis of an SNP in the NANOG region. The latter parts from HindIII of the R1 and R2 read pairs were used for the subsequent mapping. These read pair sequences were mapped to the human reference genome (hg19) by BWA (bwa-0.6.2). The read pairs, which were derived from self-ligation and no-digestion events, were removed. PCR duplicates were removed by Picard (Picard-tools-1.97). The total read numbers within 1000 bp from each HindIII site were counted, and the counted numbers in the HindIII sites were collected as wiggle (.wig) format files. The total read numbers and the ratio of cis:trans reads were used for quality control , we analyzed the contact probabilities of the HindIII site by the following method53. In our analysis, instead of running windows for the number of HindIII sites, running windows for distances from each HindIII site were used to obtain contact probabilities. The enrichment level of reads in small windows (within 100 Kb from the HindIII) for reads in large windows (within 3 Mb from the HindIII) was statistically calculated as contact probabilities in each HindIII. Two statistical methods, the U-test and the binomial test, were used to calculate contact probabilities in proximal regions (within 8-Mb regions) and the distal region (distance >8 Mb) from the baits, respectively. The contact probabilities in each HindIII site are presented in domainograms by using previously published programs37. Gene-to-gene contact probabilities were calculated around the TSS of each gene through the same method described above with the one-sided binomial test, and adjusted by FDR.Using the read count data at each 53. Briefly, wiggle-formatted ms4C-seq data in each HindIII were binarized to 1 (reads >0) and 0 (read = 0), and cis-hit coverages were calculated by averaging these binarized values in a sliding window (100 kb from each HindIII site). Spearman correlation coefficients were calculated by comparing the cis-hit coverages between cell types or biological duplicates.To compare chromatin interaction profiles between biological duplicates or cell types, the following analysis was performedhttp://hgdownload.cse.ucsc.edu/goldenpath/hg19/encodeDCC/wgEncodeBroadHmm/wgEncodeBroadHmmH1hescHMM.CNV.bed, http://hgdownload.cse.ucsc.edu/goldenpath/hg19/encodeDCC/wgEncodeBroadHmm/wgEncodeBroadHmmNhlfHMM.bed.gz)29 and used for the gene definitions. We defined the refseq genes that are mainly occupied by “poised promoter”, “Active/Weak Promoter”, and “Repressed/Heterochrom” chromatin states as “bivalent genes”, “active genes”, and “repressive genes”, respectively.Chromatin states data of hESCs and NHLFs were obtained from the ENCODE project data sets of UCSC (2(Dam-LMNB1/Dam) signal data of Tig3 HFs41 (GSE8854) as HFs and of SHEF-2 human ESCs40 (GSE22428) as PSCs, and define the lamina-associated domains (LADs) according to a previously reported method41. Briefly, for the identification of LADs, the log2(Dam-LMNB1/Dam) signal was binarized with positive values to 1 and negative values to −1. Transition sites of these signals were identified as left and right side edges of LADs by the sliding filter, which compared the average binary values between the right and left 99-probe windows of the probe41. Cumulative fraction analysis for log2(Dam-LMNB1/Dam) signals in each gene was performed using the average log2(Dam-LMNB1/Dam) values for each probe in the gene bodies.For nuclear localization analysis of gene loci, we used publically available logAll DNA microarray data are deposited in Gene Expression Omnibus under the accession number for GSE90141.All ms4C-seq data are deposited in Gene Expression Omnibus under the accession number for GSE90782.Supplementary Information