Here we show that 12 hours after amputation, the chromatin accessibility of cells in the wound region changes according to the polarity of the pre-existing tissue in a Wnt/β-catenin-dependent manner. Genomic analyses suggest that homeobox transcription factors and chromatin-remodeling proteins are direct Wnt/β-catenin targets, which trigger the expression of posterior effectors. Finally, we identify FoxG as a wnt1 up-stream regulator, probably via binding to its first intron enhancer region.For successful regeneration, the identity of the missing tissue must be specified according to the pre-existing tissue. Planarians are ideal for the study of the mechanisms underlying this process; the same field of cells can regrow a head or a tail according to the missing body part. After amputation, the differential activation of the Wnt/β-catenin signal specifies anterior versus posterior identity. Initially, both  Any planarian fragment regenerates the missing head and tail in the proper end. Early activation of the Wnt/β-catenin signaling pathway changes the chromatin accessibility of the cells of the posterior-facing wound to regenerate a tail. Spemann and Mangold were the first to demonstrate that the dorsal lip of a newt’s early gastrula has the ability to generate a fully patterned secondary axis when grafted to the opposite site8. The homologous organizer is found during gastrulation of all vertebrates, receiving different names, such as the Hensen’s node in birds9 or dorsal shield in fish embryos10. The difference between organizers and organizing centers is commonly attributed to their ability to pattern a whole-body axis or just an organ or tissue, respectively. Organizing centers have been identified in several stages of development, for instance, in the limb bud of tetrapods or the isthmic organizer at the midbrain–hindbrain boundary12. Although organizers are commonly studied in embryos, the first experiment that demonstrated the existence of an organizer was performed in adult Hydra by Ethel Browne in 1909. Browne transplanted non-pigmented oral tissue into the body column of a pigmented Hydra and observed the induction of a secondary axis that was composed of the cells of the host13. More than a century later, the existence of organizing regions in adult tissues, i.e., during regeneration, which also requires re-patterning of tissues, has not been well studied. In this study we investigated the process of regeneration of planarians, flatworms that can regenerate any missing structure, even the head, in a few days. Thus, they are whole-body regenerating animals, which need to re-pattern the body axes to regenerate the proper missing structures according to the pre-existing polarity.During embryonic development, specification of the body axis is one of the earliest events, creating a coordinate system to which to refer when building all organs and tissues. Specification of the first body axis requires the formation of an organizing center or organizer, which refers to a group of cells with the ability to instruct fates and morphogenesis in surrounding cells, giving rise to specific organs and tissues15, in addition to the continuous activation of the signaling pathways that instruct the fate of these stem cells and their progeny. Several studies demonstrate that muscle cells surrounding the planarian body are the source of Positional Control Genes (PCGs), which are secreted factors that confer axial identity to the remainder of the cells20. A subset of these muscular cells located in the most anterior (tip of the head) and the most posterior (tip of the tail) ends of the planarian body act as organizers21. The anterior and the posterior tip express the PCGs notum (a Wnt/β-catenin or cWnt pathway inhibitor) and wnt1 (a cWnt pathway activator), respectively. Inhibition of these genes produces a shift in the polarity, originating two-tailed or two-headed planarians after silencing notum or wnt1, respectively24. Thus, in planarians, as described in several embryonic models, the cWnt pathway specifies the anterior–posterior axis30. Importantly, during the first hours of regeneration, both notum and wnt1 are expressed in differentiated cells of any wound, and it is not until 36–48 h of regeneration that they are restricted to their respective tip31, forming the anterior and the posterior organizing regions. It is known that this late localized expression of notum and wnt1 depends on the proliferation of stem cells, and that it requires the expression of specific transcription factors and kinases, such as foxD, zicA, prep, or pbx for anterior tips36 and islet, pitx, mob, striatin, and teashirt (tsh) for posterior tips41. However, the triggering of the early expression of notum and wnt1, which does not depend on stem cell proliferation, is not understood.The plasticity of planarians is based on the presence of a population of adult pluripotent stem cells cis-regulatory elements (CREs) of the Schmidtea mediterranea genome42 and analyzed their accessibility in wild type (WT), notum, and wnt1 (RNAi) regenerating wounds. Our results show that at 12 hours of regeneration (hR), anterior wounds of notum (RNAi) animals resemble WT posterior wounds, and posterior wounds of wnt1 (RNAi) animals resemble WT anterior wounds. Thus, during the first hours after amputation, before the expression of any anterior or posterior marker, the chromatin accessibility of the cells localized in the wound region has changed according to the polarity of the pre-existing tissue. Analyzing the DNA binding motifs upstream of genes downregulated after wnt1 (RNAi), we found an enrichment of Homeobox transcription factors (TFs), suggesting that these are the genes directly regulated by the cWnt pathway (Wnt1/β-catenin-1) and responsible for triggering the posterior program. Moreover, thanks to the annotation of CREs, we identified two putative enhancer regions located in the first intron of wnt1 containing a FoxG binding site. Silencing of foxG inhibits the early and late phases of wnt1 expression, but not notum, and phenocopies the wnt1 (RNAi) phenotype. This result suggests that FoxG directly regulates the early expression of wnt1 in any wound and is a key factor in triggering the formation of the posterior organizing center, and thus specifying posterior versus anterior identity.Since gene expression is defined by the epigenome, early changes in the chromatin accessibility in the wound region must occur, in order to reprogram the fate of the preexistent tissue. Thus, in this study, we undertook a genomic approach to analyze the formation of the posterior organizer during the early stages of planarian regeneration. Through ATAC-sequencing and ChIPmentation techniques, we uncovered https://compgen.bio.ub.edu/PlanNET/planexp43 and https://compgen.bio.ub.edu/jbrowse/). An additional web-tool has been developed to search for transcription factor binding sites and to explore the predicted regulatory elements (https://compgen.bio.ub.edu/PlanNET/tf_tools).In this study we annotate CREs (promoters and enhancers) functional during planarian regeneration and specific of anterior-vs-posterior pole identity acquisition. An open platform to query and interpret all transcriptomic and genomic results obtained has been created  specific for each pole . We found 611 anterior specific ACRs and 2484 posterior specific ACRs. Comparing these ACRs with ChIPmentation of samples also corresponding to 12 hR anterior and posterior wounds using the H3K27ac antibody, which allows the identification of active enhancers45, enabled us to identify a list of 555 anterior putative active enhancers and 1869 posterior putative active enhancers  animals48 and posterior heads after wnt1 (RNAi)49. With the aim of analyzing the chromatin changes occurring during anterior and posterior specification, we performed ATAC-seq of notum (RNAi) anterior wounds and wnt1 (RNAi) posterior wounds, both at 12 hR. We analyzed the state of the anterior and posterior putative active enhancers previously found to be specifically open in the anterior or posterior in these RNAi samples. The result shows that in notum (RNAi) anterior wounds, only 12.3% of the anterior putative active enhancers were open, whereas the remainder were closed or reduced their accessibility  anterior wounds. In wnt1 (RNAi) posterior wounds, only 24.5% of the posterior putative active enhancers were open and the remainder were closed or decreased their accessibility. Furthermore, 31.4% of the anterior putative active enhancers appeared to be open in wnt1 (RNAi) posterior wounds and 9.5% became more accessible  anterior or posterior wounds, respectively. These results indicate that (1) inhibition of the key elements of the anterior and posterior organizers, notum and wnt1, respectively, produces a very early change of the chromatin structure, suggesting that both elements trigger the specific anterior or posterior program via the regulation of chromatin remodelers; and (2) the chromatin structure of cells in the wound is remodeled according to the polarity of the pre-existing tissue, which occurs a few hours after amputation (<12 hR), before the first anterior or posterior markers appear (around 48 hR)50.In summary, we found specific CREs and potential associated TF in anterior or posterior wounds. The accessibility of these putative enhancer regions changes as soon as 12 h after amputation in wnt1 (RNAi) posterior wounds (0–72 hR) to find the genes downregulated after cWnt pathway inhibition  planarians with respect to controls . As expected, known elements involved in posterior identity specification were found among the wnt1 (RNAi) downregulated genes 53; the posterior Wnt11 (wnt11-1 and wnt11-2)31; the posterior Frizzled fzd4-154, axinB26, tsh40, and sp5, a TF recently found to mediate the evolutionary conserved role of cWnt in axial specification29.To identify CREs that could be regulated by the cWnt pathway during posterior regeneration, we performed an RNA-seq of controls and ion Fig. . We perfion Fig. . A totalnes Fig. : the poswnt1 (RNAi) downregulated genes, we first identified the CREs found in 12 hR planarian wounds using the previous ATAC-seq and ChIPmentation samples, together with ATAC-seq analysis of un-wounded planarians (0 hR) and anterior and posterior 48 hR regenerating wounds (https://compgen.bio.ub.edu/jbrowse/). We classified the CREs found in putative promoters or enhancers according to their position with respect to the Transcriptional Start Site (TSS)  Fig.  as descrwnt1 (RNAi) wounds. The result shows that the motifs found in the putative enhancer regions of a higher percentage of wnt1 (RNAi) downregulated genes were Homeobox 53, sp529, axinB26, and tsh40, indicating that they are direct targets of the Wnt1/β-catenin-1/TCF signaling. We also combined our RNA-seq data with the RNA-seq of β-catenin-1 (RNAi) animals already reported29. This strategy resulted in 42 genes  wounds showed a TCF binding site. However, the most represented motifs found in wnt1 (RNAi) downregulated genes are not TCFs but Homeobox. These results suggest that the Wnt1/β-catenin-1/TCF signaling could directly activate the expression of TFs, which in turn would activate the effectors of the posterior fate. In agreement with this hypothesis, Gene Ontology enrichment analysis of the genes downregulated after wnt1 (RNAi) with TCF binding site in their putative promoter or enhancer regions showed a significant enrichment of DNA binding proteins/regulators of transcription and specifically of Homeobox TFs  downregulated genes containing TCF motifs, we also found chromatin-remodeling proteins, such as BPTF, a nucleosome-remodeling factor56, and TOP2B57  downregulated genes containing a TCF binding motif. A new web tool was developed to search for transcription factor binding sites and to explore the predicted regulatory elements (https://compgen.bio.ub.edu/PlanNET/tf_tools).Several genes downregulated in TFs Fig. . Among tsp5, tsh), which in turn regulate the activation of the effectors of posterior specification  and enhancer 2 (E2) according to their distance to the TSS  wounds  to the first intron of Dm-wnt1 (wingless)61.To assess the biological significance of these putative enhancer regions, we looked for evidence showing their evolutionary conservation. Interestingly, we found that, although zed Fig. . Furtherzed Fig. . ImportaS. mediterranea wnt1 first intron and its possible evolutionary conservation, supports the role of FoxG as a direct wnt1 regulator.Thus, the finding of enhancer activity in wnt1 expression in planarians, we inhibited it by RNAi in regenerating animals  animals demonstrated that it was absent in both at 12 hR and 3 dR posterior wounds, indicating that foxG is required for both the early (stem cell independent) and the late (stem cell dependent) phase of wnt1 expression  in intact animals and in posterior regenerating blastemas at 72 hR63  animals should show a phenotype related to the malfunction of the posterior organizer. Accordingly, we found that 70% (15/20 and 40/56) regenerating foxG (RNAi) animals presented a rounded posterior blastema  phenotype31. Analysis of the central nervous system and the digestive system by anti-arrestin (3C11) and anti-βcatenin-2 immunohistochemistry, respectively, demonstrated that 70% (15/21) of these animals are tailless , indicated that they are downregulated in posterior foxG (RNAi) regenerating blastemas at 3 dR , 2 out of 20 regenerating animals (two independent experiments) showed a two-headed phenotype  animals do not show a decrease in foxG expression (Supplementary Data These results demonstrate that 21), a term that has been traditionally used in the field of embryonic development. The finding of adult organizers in other regenerating animals, such as Hydra, zebrafish, or Xenopus tadpoles, supports the idea that the formation of organizers could be a general mechanism that confers regenerative properties68. There are common features in the reported examples: (1) the cells that function as organizers are non-proliferative and are located in the periphery of the early blastema, and (2) the organizing activity relies on the cWnt signaling69. These properties are also accomplished by planarian organizers. A difference between planarians and other bilaterian models of regeneration is that planarians can completely regenerate a new axis from both ends, anterior and posterior, independently of the fragment amputated. The plasticity of the model, in addition to the use of genomic and transcriptomic high throughput techniques, has allowed us to compare the genomic changes occurring during anterior or posterior specification in the same field of original cells.The plasticity of planarians is providing insightful data about the mechanism underlying regeneration. Several studies have demonstrated that the anterior and posterior tips of planarians function as organizers (reviewed in ref. notum (RNAi) wounds with respect to WT are stronger than those in wnt1 (RNAi). However, we cannot conclude that notum has a more determinant or earlier effect than wnt1, because we only have analyzed one time point, 12 h after the cut. Furthermore, our wnt1 (RNAi) animals have a milder phenotype (tailless) than notum (RNAi) animals (two-tailed). (2) Remodeling of the chromatin could allow the expression of TFs, such as the Hox genes, whose transcription has shown to be dependent on extensive chromatin remodeling in other models70. These two steps appear to be directly regulated by the cWnt signaling, because among the wnt1 (RNAi) downregulated genes showing TCF binding sites in their putative enhancer/promoter regions, we found an enrichment of DNA binding proteins, including chromatin-remodeling proteins and TFs. (3) The third step consists in the activation of the Posterior Effectors , which are required for differentiation and morphogenesis of tail structures, thanks to the TFs active in step 2.Our data indicates that the establishment of the appropriate identity in a planarian wound could follow a three-step model Fig. . (1) Remwnt1 (RNAi) genes showing a TCF binding site, indicates that in planarians the Wnt/β-catenin pathway specifies cell fate via regulating chromatin structure and reprogramming as described in other contexts71. It is important to note that the early expression of notum and wnt1 is stem cell independent24, supporting the essential role that reprogramming could have at this early stage.The early change in the genomic landscape found in each regenerating tip, in addition to the finding of several chromatin-remodeling proteins downregulated in 50, we observed that changes occurring in the chromatin of cells in each wound are wound-specific and occur a few hours after the cut. These rapid changes at genomic level were visualized due to the genomic analysis restricted to the cells in the wound region and at a very early time point, significantly before the appearance of any polarity signaling. Future genomic analysis at single cell level will allow visualization of the genomic changes occurring in specific cell types of the wound region.Furthermore, our data restricts the timing when this chromatin remodeling occurs, which must be earlier than 12 h after the cut. Thus, a novelty of the proposed three-step model is that, in contrast to the results found in previous transcriptomic analysis in planarians, in which injury-specific transcriptional responses emerged 30 h after injurywnt1 leads to the deregulation of a large number of genes at late timepoints (48–72 h), corresponding to the process previously known as injury-specific transcriptional response50. However, the second novelty of our three-step model is that through the identification of CREs in the S. mediterranea genome, we observed that the motif present in a higher percentage of wnt1 (RNAi) downregulated genes was the Homeobox binding site and that a small number of them, mainly corresponding to DNA binding proteins, contained TCF motifs. This result suggests that TFs and mainly Homeobox genes are direct targets of WNT1 that afterwards will activate the transcription of the posterior effectors. The Hox genes post2c, lox5a/b, and hox4b are specifically expressed in posterior, although regenerative and segmentation defects have only been seen after lox5a and lox5b (RNAi)72, respectively. Not only in planarians, but also in other whole-body regenerating animals, such as acoels and Hydra, Hox genes and sp5, which also shows a TCF motif in its CRE, have a role in axis establishment, suggesting that a conserved set of cWnt targets mediate the patterning of the primary body axis69.Our RNA-seq analysis agrees with previous transcriptomic studies, because we found that inhibition of wnt11-1 and wnt11-2, which are required to regenerate a proper tail but whose inhibition does not produce a shift in polarity27, are downregulated at a late stage in wnt1 (RNAi) animals, and do not show a TCF binding motif, suggesting that they could be part of the posterior effectors. Supporting the late role of wnt11-1 and wnt11-2, their silencing inhibits the late wnt1 expression but not the early expression49. The same situation occurs with the posterior WNT receptor, fzd4-1. In this case, it could be that the expression of fzd4-1 is mediated by the early wnt1+ cells, as recently proposed55, forming the posterior organizer, in accordance with the idea that organizers evocate the surrounding tissue; a first organizer action would be to prepare the tissue to make it competent to itself2.According to our data, 74. The proposed three-step model assumes this antagonism and presupposes that remodeling of the chromatin is different in anterior and posterior wounds because notum is expressed at higher levels in anterior and wnt1 is expressed at higher levels in posterior. Genes required for the late expression of notum and wnt1, localized in the midline, have been identified. foxD and zicA (RNAi) animals do not show the late expression of notum and do not regenerate a proper head34; islet and pitx (RNAi) animals do not show the late expression of wnt1 and are tailless46. Little was known about the regulation of the expression of notum and wnt1 in disperse cells of early wounds. Equinox, an extracellular protein expressed in the wound epidermis, has been shown to be required for the expression of wound response genes, including notum and wnt175, and a role of activin-2 in restricting the early expression of notum in anterior wounds has been reported76. However, the regulation of the expression of wnt1 in a salt-and-pepper manner in early wounds, and its final restriction to the posterior pole remained unsolved.The fundamental role of the Notum-Wnt1 antagonism in establishing the identity of a wound has been widely demonstrated through functional and expression analyseswnt1 gene which showed FoxG binding motifs. We propose that these putative enhancer regions are required for wnt1 expression in planarians. First, they are localized in the first intron, which is a region frequently enriched in regulatory elements80. Second, we found that foxG is necessary for wnt1 expression in any context. foxG inhibition suppresses the early and the late phase of wnt1 expression during regeneration, in addition to its expression during homeostasis. The different accessibility of E1 and E2 could account for it, since E1 is specifically accessible at 12 hR and E2 is accessible at any time point analyzed. Third, the presence and activity of this enhancer region could be evolutionary conserved, which further supports its relevance. We found that the position of intron 1 in all wnt1 genes studied in different metazoan species is conserved. Furthermore, there are several genomic studies that demonstrate the existence of open regions in this intron, and a ChIP-sequencing analysis with the FoxG antibody in Drosophila demonstrates that FoxG binds to Dm-wnt1 (wingless) intron 1. We hypothesize that the binding of FoxG to the intron 1 of wnt1 to regulate its expression is ancestral and conserved through evolution. Genomic studies in different regenerative species have identified different sets of TFs as regulators of cWnt genes during regeneration. In Drosophila, injured imaginal discs required “regenerative enhancers” to trigger wingless expression and the regeneration process83. During Hydra head regeneration, an enhancer collection becomes accessible, inducing the expression of cWnt genes in head organizing cells86. In acoels, egr is expressed after amputation triggering the expression of wnt3, which participates in posterior specification87. As recently proposed, it could be that enhancers are maintained as part of conserved gene regulatory network modules during evolution88. In this respect, further studies are required to analyze the evolutionary conservation of the enhancers found in the first intron of wnt1.Due to the annotation of the CREs in the planarian genome, we identified two putative enhancer regions (E1 and E2) in the first intron of the foxG suppresses both early and late wnt1 expression after amputation, and, consequently, animals became tailless. Importantly, a low percentage of foxG (RNAi) animals regenerated as two-headed. A shift in polarity is a phenotype only found after β-catenin-1 or wnt1 (RNAi)30, but never after islet or pitx (RNAi)46. Thus, the finding of two-headed foxG (RNAi) animals suggests that inhibition of the late phase of wnt1 prevents the regeneration of a tail, but that inhibition of the early phase is required to shift polarity. This idea is supported by reports on the role of Hedgehog (Hh) signaling in planarians. Activation of the Hh signaling is also required for the early phase of wnt1 expression and a low percentage of animals become two-headed90. According to these data, Hh could mediate its early role in polarity establishment by regulating wnt1 expression through foxG activation, as has been reported in zebrafish, mice and amphioxus, where Hedgehog signaling contributes to Foxg1 induction and integration of telencephalic signaling centers93.RNAi inhibition of wnt1 in differentiated muscular cells. However, the cells in the organizer must integrate a signaling network that includes several genes that are not cell specific, and simultaneously they must be integrated in a diverse and dynamic cellular context. Our study has shed some light on this genetic and cellular context of the planarian posterior organizer. We found foxG to be a gene essential for wnt1 muscle-specific expression, and its inhibition phenocopies wnt1 (RNAi). Of note, it has recently been shown that foxG may play a role in muscle cell specification in many invertebrate organisms, such as planarians94. However, foxG is not specifically expressed in wnt1+ muscular cells but is also expressed in neurons and in progenitor cells. Interestingly, the binding site for FoxG (SLP1) was also notably enriched in the putative enhancer regions of wnt1 (RNAi) downregulated genes and it is present in the CREs of genes associated with. Thus, FoxG can regulate not only wnt1 expression in muscular cells but, additionally, wnt1-regulated posterior genes in other cell types, such as neurons. Further studies are necessary to analyze whether FoxG binds to E1 and/or E2 of wnt1, in addition to the existence of specific co-factors that confer it a cell-dependent activity.The planarian posterior organizer is defined by the expression of Drosophila imaginal discs98. The plasticity of planarians, which allows the comparative study of anterior and posterior regenerating wounds originating from the same field of cells, has allowed the identification of regenerative enhancers specifically associated with posterior specification. The data presented in this study suggests that the formation of the posterior organizer could work as a chain reaction. A first differential signal in the wound according to the polarity of the pre-existing tissue 90 leads to the rapid resolution of the Notum-Wnt1 antagonism, which in posterior wounds will maintain wnt1 and suppress notum. At this point, which must occur during the first 12 h, the program to become posterior has already started, setting up chromatin changes specific to the posterior pole and dependent on cWnt activation. Chromatin accessibility changes allow the subsequent expression of a specific set of TFs that turn on the tail effectors. The finding of several Forkhead binding site motifs in a high percentage of wnt1 (RNAi) downregulated genes enhancers, as well as in the specific anterior and posterior CREs, aligns with pioneer factors acting at the top of gene regulatory networks to control developmental transitions99 and prompts to investigate the role of pioneer factors during regeneration and polarity acquisition.The existence of “regenerative enhancers”, groups of enhancers that become accessible during regeneration, has been demonstrated in regenerating species, such as zebrafish and Hydra. Notably, they can be identified both in regenerating and in intact contexts. Muscular wnt1+ cells are found in the midline of posterior wounds and in the tail of planarians during homeostasis30, and we found that in both situations wnt1 expression depends on foxG. However, homeostatic and regenerating wnt1+ cells have different properties, because inhibition of wnt1 or foxG during homeostasis does not produce a shift in polarity. After an amputation, when new tissue must be regenerated, there must be a time window when everything is possible. According to the signal received by the cells in the wound, the identity of the organizer is decided. Importantly, not only the identity but the presence of an organizer, which indicates the possibility of regenerating, is determined. As shown by Liu et al., modulating the cWnt provided regenerative capacity to planarian species that are not able to regenerate a head in nature100. These results indicate that the ability to form an organizer is linked to the ability to regenerate. Thus, understanding the formation and function of organizers is key to understanding adult regeneration, and it must be a subject of study not only in whole-body regenerating animals.Organizers or organizing centers required for growth and the pattern of a new structure are well studied during embryonic development. Adult organizers are found in whole-body regenerating animals, such as planarians or https://compgen.bio.ub.edu/PlanNET/planexp)43. Furthermore, an additional web tool was developed to enable searching for transcription factor binding sites and exploring the predicted regulatory elements (https://compgen.bio.ub.edu/PlanNET/tf_tools).Our results demonstrate the power of genome-wide approaches to further understand the genetics of regeneration. With the aim of sharing the results obtained in this study and facilitating their further analysis by the scientific community, we integrated all transcriptomic and genomic analysis results into the PlanExp open platform  water at 20 °C in the dark. PAM solution contains101: 0,016 mM NaCl , 0,01 mM MgSO4·7H2O , 0,012 mM NaHCO3 , 0,001 mM KCl , 0,001 mM MgCl22·6H2O  and 0,01 mM CaCl2·2H2O  diluted in MiliQ water. Animals were regularly fed twice per week with organic cow liver102. Animals with a 5 mm length average were randomly selected for most of the experiments. In the RNA-seq/ATAC-seq and ChIPmentation experiments, animals with 8 mm length average were used.103. dsRNA (3 × 32.2 nl) was injected into the digestive system of each animal on 3 consecutive days (1 round). For wnt1 RNA-seq samples, inhibited and control animals were injected for one round at 1500 ng/µl and amputated at the post-pharyngeal level. Then, studied pieces were soaked in dsRNA diluted (1000 ng/µl) in PAM water for 3 h in the dark. For wnt1 and notum ATAC-seq samples, inhibited and control animals were injected for two rounds at 1000 ng/µl and amputated at pre- and post-pharyngeal levels. foxG (RNAi) regenerating animals were inhibited (1500 ng/µl) for two rounds; and high dsRNA concentration (2000 ng/µl) for 5 consecutive days for two weeks was used to increase the RNAi depletion. Animals were amputated pre- and post-pharyngeal at the end of the injection period. Intact animals were inhibited for three consecutive rounds. All control animals were injected and/or soaked with dsRNA of gfp.For RNAi, double strand RNA (dsRNA) was synthesized by in vitro transcription (Roche) using PCR-generated templates with T7 and SP6 flanking promoters. The precipitation step was conducted using ethanol, followed by annealing and resuspension in waternotum (RNAi), wnt1 (RNAi), or gfp (RNAi) samples. Twenty animals were used per biological replicate. ATAC-sequencing was carried out as first described in104 and then adapted by105. The ATAC-seq protocol has three main steps: (1) Nuclei preparation. Planarian mucous was removed by washing in 2%L-Cystein (pH 7) for 2 min. Then, animals were transferred to a Petri dish with CMFH . Planarians were placed in Peltier Cells at 8 °C to amputate the wound region (the blastema and post-blastema region posterior to the mouth). Then, they were transferred to a 1.5 ml Eppendorf tube to be dissociated using a solution of liberase/CMFH (1:10) at RT for 10 min, pipetting until obtaining an homogenized solution. Cell suspension was passed through a 40 µm strainer washed with cold lysis buffer , and cells were quantified using the Neubauer chamber. (2) Transposition reaction. Fifty thousand cells were transferred to a new 1.5 ml tube and resuspended in a transposition reaction  for 30 min at 37 °C. Then, the samples were transferred to ice. 2.4 µl of EDTA 0.5 M were added per sample, and incubated for 30 min at 55 °C. After that, 1.2 µl of MgCl2 1 M were added per sample. Following the transposition, the DNA lysate was purified using MinElute Reaction Cleanup Kit  and eluted in 10 µl. (3) DNA purification and library preparation. Following the purification, the DNA fragments were amplified using 25 µl of NEBNext High Fidelity 2X PCR Master Mix , 10 µl of Transposase DNA, 10 µl of nuclease free water and 2.5 µl of 25 µM adapter 1 and 2.X  Tissue crosslinking. Planarians were placed in Peltier Cells at 8 °C to amputate the wound region (the blastema and post-blastema region posterior to the mouth). Then, wounds were transferred to a Petri dish containing 1 M MgCl2 solution, for 15–30 rocking at room temperature (RT). PBS 1× was added to remove salts. Blastemas were fixed with formaldehyde 1.85% for 15′ rocking, at RT. Glycine was added to obtain a final concentration of 0.125 M to quench formaldehyde, for 5′ at RT, rocking. Then, blastemas were washed 3× with cold PBS 1×. Finally, PBS excess was removed, and samples were stored at −80 °C. (2) Tissue homogenization, sonication and immunoprecipitation. Samples were homogenized in a lysis buffer . After centrifuging the samples, the pellet was resuspended in 660 µl Nuclear lysis buffer  and 1.34 ml of ChIP Dilution buffer . Then, samples were sonicated in a M220 Focused-ultrasonicator  with the following settings: duty factor = 10%, PIP = 75 W, cycles = 100, time = 10 min. The sonicated chromatin was incubated with H3K27ac polyclonal antibody  overnight at 4 °C. (3) Bead incubation and TAGmentation. The samples were incubated with Dynabeads protein G resuspended in ChIP Dilution Buffer for 1 h at 4 °C. Then, beads were washed twice with Wash Buffer 1 , twice in Wash Buffer 2 , twice in Wash Buffer 3 , and twice in 10 mM TrisHCl pH 8. Beads were resuspended in TAGmentation reaction mix  and 1 µl of Tn5 and incubated for 1 min. Subsequently, two washes with Wash Buffer 1 were performed and once with TE 1×. The samples were eluted 15 min with 100 µl of Elution Buffer  and finally with 180 µl of Elution Buffer Per sample, 10 µl of 4 M NaCl and 0.5 µl of 10 mg/ml ProteinaseK were added, being incubated between 4/6 h at 65 °C. (4) DNA purification and library preparation. DNA was purified using Minelute columns . The libraries ware prepared by PCR reaction: 19 µl of DNA, 1 µl of 25 µM of adapter 1 and 2X 108. BAM were converted to BED; for the ATAC-seq replicates then the coordinates on the BED files were shifted +4 and −5 positions to overcome the Tn5 cut position. MACS2109 was used for peak calling and HOMER110 for motif discovery. Differential binding analysis was carried out using DiffBind111 R functions (see CSM sections 4 and 5).Reads were aligned by bowtienotum and wnt1 (RNAi) ATAC-seq samples (DiffBind “second round” from now on). All anterior and posterior ATAC-ChIP peaks found non-significant on the “second round” that had positive counts when compared with the two replicates of the notum or wnt1 (RNAi) ATAC-Seq peaks were considered “accessible”. If an ATAC-ChIP peak was significant on the “second round” and both replicates of ATAC-ChIP and both of notum (RNAi) ATAC-Seq had positive counts, then those peaks were annotated as “slightly” for posterior regenerating blastemas or “less” accessible for anterior regenerating blastemas. If an ATAC-ChIP peak was significant on the “second round” and both replicates of ATAC-ChIP and wnt (RNAi) ATAC-Seq samples had positive counts, then those peaks were annotated as “slightly” for anterior regenerating blastemas or “less” accessible for posterior regenerating blastemas. Finally, all those peaks found significant on the “second round” that had two positive ATAC-ChIP replicates and less than two of notum or wnt1 (RNAi) ATAC-Seq sample replicates, were annotated as “non-accessible” , were assumed to be promoter elements; on the other hand, such procedure returned 555 and 1869 non-significant sites that were marked as putative enhancers for anterior and posterior respectively. Those enhancer regions will be referred to as ATAC-ChIP peaks. Enhancer dynamics was derived after crossing with DiffBind the data of anterior and posterior ATAC-ChIP peaks over cis-regulatory elements (CRE) were annotated over the S. mediterranea genome version S2F2. For this purpose, both ChIP-seq and ATAC-seq data from all collected samples were used. Narrowpeaks over the genome were identified using MACS2 . These peaks were merged using the mergePeaks command of the HOMER software suite. Finally, regions over the genome were classified as either putative promoters, or putative enhancers, according to their evidence regarding ATAC-seq and ChIP-seq peak coverage. Only the regions known as peaks on at least two samples were considered, and the remainder were discarded for the CRE annotation .Putative Peak regions with only ATAC-seq evidence were classified as core promoters (<100 bp upstream of an annotated TSS) or proximal promoters (between 500 and 100 bp upstream of a TSS). Finally, peaks with CHIP-seq evidence were classified as either proximal enhancers (within 2000 bp of an annotated TSS) or distal enhancers .Drosophila melanogaster (MA0458.1) and FOXG from Homo sapiens (MA0613.1). Weight matrices were obtained from the JASPAR CORE 2022 database112.Putative transcription factor binding sites were identified and annotated on all of these enhancer and promoter regions using the HOMER’s findMotifsGenome command, scanning these regions using the motifs provided by the software suite (known motifs). Two further motifs were manually appended to the set of known motifs: slp1 from HOMER findMotifsGenome command computed motifs overrepresentation within those enhancer and promoter regions with respect to random sampled regions scattered through genome. All motifs considered from that output had an adjusted p-value smaller than 0.05. Then, enhancer and promoter regions were assigned to the closest gene, which facilitated the calculation of ratios of FoxG motif matches with respect to the total number of motifs found on each region for each gene . At 12 h anterior/posterior comparison 4035 regions were assigned to genes; of those, 3290 had no FoxG motif annotated in either promoter or enhancer regions , 304 were found to have FoxG motif only on anterior samples (“A to 0”), whilst 433 only on posterior samples (“0 to P”), and the remaining 8 genes had similar anterior/posterior FoxG ratios. See CSM sections 7.4.5 for further details on the gene selection related to the anterior/posterior FoxG enrichment ratios calculation, and 7.5.3 for the gene ontology functional analysis over those genes 113 using the default parameters. FASTA files containing DNA sequences corresponding to the wnt1 first intron from different species were obtained from different sources, mostly using UCSC browser ; libraries were sequenced on HiSeq 4000 (Illumina) with a read length of 2 × 76 bp.RNA-sequencing samples were obtained following the soaking protocol. At the corresponding time point , animals were placed in a Petri dish with cold 1% HCl (diluted in water) for 2′ and then transferred to a new Petri dish with cold PBS 1×. Two washes were performed with cold PBS 1× and animals were transferred to cold RNAlater for 20′ placed in ice. Then, planarians were amputated in a Peltier Cell with a clean blade, to obtain the blastemas and post-blastemas. Fragments were washed with RNAlater (Invitrogen) and 50% RNAlater/Trizol. Finally, liquids were removed and 100 μl of Trizol reagent (Invitrogen) was added. Total mRNA extraction was performed as described in ref. 42 using the STAR software tool116. Genes with low expression were filtered by removing genes with less than 1 count-per-million (CPM). Two biological replicates were removed due to ineffective wnt1 inhibition . Differentially expressed genes were identified using the lima-voom pipeline117, using an FDR cut-off of 0.05 and a log fold change cut-off of ±0.5. Interactive expression analyses are also available from PlanEXP as “2019 Adell Time-course” dataset.RNA reads were mapped against the planarian genome version S2F2β-catenin-1 (RNAi)29 were used to combine with the downregulated genes wnt1 (RNAi) wounds. The transcriptome IDs were converted to genome IDs, using the “ID Converter” tool from PlanNET, and used to determine their presence in our dataset.The day 1 (42), day 2 (95) and cluster (52) of downregulated genes from RNA-seq of 2O and adjusted to a final concentration of 250 ng/µl. All primers used are displayed in Supplementary Data 53: animals were killed in 5% N-acetyl-L-cysteine (NAC), fixed in 4% formaldehyde (FA), permeabilized with reduction solution for 5′ at 37 °C and stored in methanol at −20 °C. Following overnight hybridization, samples were washed twice with 2x SSC with Triton-X (SSCTx), 0.2x SSCTx, and 0.02x SSCTx and MABTween. Subsequently, blocking was in 5% Horse Serum, and 0.5% Western blocking reagent (Roche) MABTween solution and anti-DIG-AP  was used. The antibody was washed for 2 h followed by NBT/BCIP development.RNA probes were synthesized in vitro (Roche) using T7 or SP6 polymerases and DIG-modified, purified with ethanol and 7.5 M of ammonium acetate, diluted in 25 µl ddH118: animals were killed with cold 2% HCl and fixed with 4% FA at RT. After 4 h in blocking solution (1% BSA in PBS Triton-X 0.3%), animals were stained overnight at 4 °C. Animals were washed extensively with PBSTx, blocked for 2 h, and stained overnight at 4 °C. The following antibodies were used in these experiments: mouse anti-synapsin  and anti-Smed-β-catenin-2 . The secondary antibodies used were Alexa 488-conjugated goat anti-mouse  and Alexa 568-conjugated goat anti-rabbit . Nuclei were stained with DAPI (1:5000).Whole-mount immunohistochemistry (IF) was performed as in ref. ura4 was used to normalize the expression levels, all primers used are displayed in Supplementary Data Total mRNA was extracted from a pool of 5 control and RNAi planarians at 7 days of regeneration, using TRIzol reagent (Invitrogen). RNA samples were treated with DNase I  and cDNA was synthesized using First-Strand Synthesis System Kit . Experiments were conducted on 7500 Fast PCR System (Applied Biosystems), using 3 biological and 3 technical replicates for each condition. The housekeeping 120 was used to show representative confocal stacks for each experimental condition.In vivo images were acquired with Scmex 3.0 camera  in a Zeiss Stemi SV 6 binocular loupe. Brightfield colorimetric ISH images obtained with a ProgRes C3 camera from Jenoptik . A Zeiss LSM 880 confocal microscope  was used to obtain confocal images of whole-mount immunostainings. Fiji/ImageJt-tests (α = 0.05) were performed to compare the means of two populations (qRT-PCR experiment). P values of <0.05 (*), <0.01 (**), <0.001 (***) were annotated with asterisks in figures. Statistical analyses were performed using GraphPad Prism 8 . For in vivo, ISH and IF experiments, values indicate exactly the animals used in each experiment. The experiment reproducibility is indicated either in the figure legend or the CSM.Information regarding statistical tests, n values, and replicates are detailed in figure legends, Computational Supplementary Methods (CSM), Source Data and Reporting Summary. Two-sided Student’s wnt1-RNAi 0 hR and 12 hR, see Figure CSM.10), because their wnt1 expression level was overlapping the one of the control, which indicates ineffective wnt1 inhibition on those samples. Therefore, all RNA-Seq timepoints consisted of three replicate libraries for both controls and wnt1 (RNAi) samples, except for wnt1 (RNAi) 0 hR and 12 hR that had only two. ATAC-Seq single replicate timepoints at control 0 hR, anterior 48 hR, and posterior 48 hR, were not considered to analyze the dynamics of regulatory elements. Three library replicates per ATAC-Seq condition at 12 hR were obtained; however, one replicate of each condition was discarded after PCA analysis . All the downstream analyses were made using two replicates per condition of the ATAC-Seq at 12 hR and for the ChIPmentation anterior/posterior conditions; on all those replicates FRiP score was greater than 0.3 , and irreproducible discovery rate (IDR) rank plots showed good correlation between peaks annotated on replicate pairs . Replicate and statistical information for RNA-seq, ATAC-seq, Chipmentation data and other bioinformatic analysis are detailed in the CSM.Four RNA-Seq replicates were discarded: two sequencing libraries due to low sequencing yield , which were compensated by an extra replicate at those timepoints; and two further replicates later on (Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Reporting Summary


Epigenetic mechanisms regulate gene expression in each cell type without modifying the underlying genetic sequence. These mechanisms are crucial for normal blood cell function. When they are disrupted, they give rise to diseases such as acute myeloid leukemia, an aggressive type of blood cancer. In this review, we outline the most recent technological advances that enable the study of the epigenetic mechanisms of blood cells with greater precision and a higher resolution. From the technologies that can introduce specific types of epigenetic changes ((epi)-genomic editing) to those that allow us to study the epigenetic mechanisms of individual cells, we summarize the advances which provide a new lens through which to study epigenetic regulation. Given the essential role of epigenetic mechanisms in healthy tissue function and disease, this can provide a comprehensive resource for researchers in the gene regulation field and beyond.Epigenetic modifications, such as histone modifications and DNA methylation, are essential for ensuring the dynamic control of gene regulation in every cell type. These modifications are associated with gene activation or repression, depending on the genomic context and specific type of modification. In both cases, they are deposited and removed by epigenetic modifier proteins. In acute myeloid leukemia (AML), the function of these proteins is perturbed through genetic mutations  or translocations  arising during leukemogenesis. This can lead to an imbalance in the epigenomic landscape, which drives aberrant gene expression patterns. New technological advances, such as CRISPR editing, are now being used to precisely model genetic mutations and chromosomal translocations. In addition, high-precision epigenomic editing using dCas9 or CRISPR base editing are being used to investigate the function of epigenetic mechanisms in gene regulation. To interrogate these mechanisms at higher resolution, advances in single-cell techniques have begun to highlight the heterogeneity of epigenomic landscapes and how these impact on gene expression within different AML populations in individual cells. Combined, these technologies provide a new lens through which to study the role of epigenetic modifications in normal hematopoiesis and how the underlying mechanisms can be hijacked in the context of malignancies such as AML. The mammalian genome is finely regulated to ensure precise gene expression in each cell type. This is achieved through epigenetic mechanisms which dynamically control gene expression without perturbing the underlying genetic code. Two well-characterized types of epigenetic marks are histone modifications and DNA methylation. Epigenetic modifier proteins are responsible for either ‘writing’, ‘erasing’, or ‘reading’ these modifications, which can contribute to gene activation or repression.The epigenetic regulation of gene expression controls differentiation throughout all the stages of hematopoiesis, and its disruption can result in disease. In the context of acute myeloid leukemia (AML), epigenetic dysregulation promotes aberrant gene expression in the hematopoietic stem and progenitor cells, resulting in defective differentiation and leukemic transformation. The disruption of the epigenetic code can occur through the acquisition of genetic mutations in the genes encoding epigenetic regulators or chromosomal translocations that cause epigenetic defects.In this review, we outline new biological models and technological advances that are instrumental in understanding how histone modifications and DNA methylation regulate transcription in normal cells and how these mechanisms are hijacked in the context of hematologic malignancies such as AML.Histones can be post-translationally modified with chemical tags such as methylation and acetylation, which are associated with either gene activation or repression. Histone modifications can be used to denote active or repressed cis-regulatory elements, such as enhancers, promoters, and gene bodies ,2. ActivDot1l-deficient mice displaying severe anemia and death at E10.5-13.5 ,1110,11]and Spi1 . DOT1L cand Spi1 . In a noand Spi1 ,17,18. Iand Spi1 . In addiand Spi1 .DNA methylation takes place through the deposition of a methyl group on the 5′ carbon of the cytosine bases (5mC) at CpG dinucleotides a. DNA mePOU2AF1, implicated in B-cell differentiation), whereas the genes required for hematopoietic stem cell self-renewal, such as MEIS1, are methylated and silenced . To. To76]. When dCas9 is fused to an enzyme with DNA methyltransferase activity, this technology enables high-precision CpG editing by using guide RNAs to recruit methylation enzymes to specific sites in the genome. For example, dCas9 fused to DNMT3A or MQ1 (a prokaryotic methyltransferase) were used in primary T lymphocytes and mouse embryos to methylate specific loci in the human genome, such as the RUNX1 gene ,83. UponA major limitation of the current dCas9-based epigenomic editors is the size of dCas9 (encoded by over 4 kilobases) and its fusion proteins of interest. This makes it difficult to deliver such constructs to hematopoietic cells using retroviral or lentiviral vectors due to limitations on efficient viral packaging. To avoid this limitation, the co-transduction of two lentiviral vectors encoding dCas9-p300 and an sgRNA fused to two different fluorescent proteins was used in mouse primary T-cells . HoweverOther strategies that may be used to address this size limitation include the development of new transgenic lines for epigenomic editing: Rosa26:LSL-dCas9-p300 for gene activation and Rosa26:LSL-dCas9-KRAB for gene repression . These mGenome-wide epigenomic approaches, such as chromatin immunoprecipitation (ChIP-seq), assays for transposase-accessible chromatin (ATAC-seq), and bisulfite sequencing (BS-seq), have been instrumental for the interrogation of histone modification, DNA accessibility, and methylation patterns in bulk populations, respectively. Clear disadvantages of these technologies include the requirement of a large numbers of cells and, importantly, that fact that they mask epigenetic heterogeneity between cells within a population. Some of these technologies have been further developed and adapted for low cell numbers and single-cell inputs, making significant contributions to our understanding of the hematopoietic system and hematopoietic malignancies such as AML.One of the pioneering single-cell epigenomic technologies is single-cell ATAC-seq (scATAC-seq), now established in widely used droplet microfluidic platforms ,88. In fThe study of histone modifications by ChIP-seq in cases of low cell numbers poses clear challenges related to background signal and cellular crosslinking requirements, although pioneering studies have adapted this technology to droplet microfluidic platforms so as to achieve single-cell readouts ,92,93. NHOXA9 and TAPT1 expression displayed high H3K4me3 and low H3K27me3 levels at their promoters. Inversely, low H3K4me3 and high H3K27me3 were associated with low HOXA9 and TAPT1 expression. This bivalency could reflect the MLL::FP binding dynamics at its gene targets in individual cells within a leukemic population.Recent advances in single-cell CUT&RUN and CUT&Tag provide a higher-resolution view of the histone modification landscape of individual cells  96,97].,97.96,97Mll::Af9 leukemia cells. The sgRNAs targeting the N-terminus of DOT1L, which contains the methyltransferase domain responsible for H3K79me deposition, showed deregulation of DOT1L-inhibitor-sensitive genes, such as Meis1, Hoxa9, and Myc, as well as myeloid differentiation genes, including Cd11b and Gr1. Single-cell techniques coupled with gene editing approaches can be used to distinguish precisely which individual epigenetic modifier domains are important drivers of leukemogenesis.CRISPR tiling is another technology used to explore chromatin modifier functions by coupling single-cell gene expression data with CRISPR editing. This approach has been used to examine the importance of individual DOT1L domains in MLL-r leukemia . In thisDNMT3A mutations on clonal hematopoiesis . P. P100]. opoiesis ,102. In In summary, the development of single-cell technologies to study epigenetic regulation in healthy and malignant hematopoiesis has provided critical insights into the cellular hierarchies that construct each state. The wider adoption of these technologies by the hematopoietic community will hopefully lead to a high-resolution picture of the epigenetic mechanisms driving leukemogenesis.Molecular tools that can be used to interrogate the functional role of epigenetic modifications are rapidly being developed. These technologies, including CRISPR-Cas9 editing and single-cell approaches, represent a new era of research, aiming to study epigenomics from a new perspective at a high resolution . ApplyinCRISPR-Cas9 technologies have been shown to be instrumental for the investigation of AML disease models and our understanding of the underlying epigenetic mechanisms which drive them. Despite their wide application, thus far, there are questions remaining in the MLL-r AML field that CRISPR approaches could be used to explore further. Even though the same fusion proteins, such as MLL::AF9, can be responsible for leukemogenesis, chromosomal translocations can occur at different breakpoints, meaning that not all MLL::AF9 fusion proteins are identical ,104. As EZH2 mutations. This technology could also be particularly useful as a means to model mutations in the proteins of the DNA methylation machinery. Many of these mutations are hotspot (DNMT3A-R882) or gain-of-function mutations (IDH1-R132 and IDH2-R140). Therefore, base editing could be used to specifically introduce these mutations in an endogenous context without completely knocking out or overexpressing the mutant versions of these genes, more faithfully replicating the context in which they occur in leukemia, as recently shown in IDH mutant TF1 cells [Another variant of CRISPR-Cas9 editing which has not yet been widely applied to study the role of epigenetic modifications in AML is CRISPR base editing. Given that MLL-r AML is dependent on H3K79me, base editing could be used to create H3K79 mutant MLL::AF9 cells in order to directly investigate how H3K79me impacts transcriptional regulation in this setting. Base editing could be similarly used to study the function of mutant histones, such as H3K27M, in AML settings, as well as wildtype H3K27me3, which is potentially perturbed in AML models carrying F1 cells .The next generation of CRISPR-based tools is epigenomic editors. Overall, epigenomic CRISPR-Cas9 editors are a promising system to perform functional perturbations of a cell’s epigenetic state. However, some of their current limitations include the potential off-target effects of delivering endogenous enzymes (such de novo Dnmts) into the nucleus in large quantities. Studies addressing this issue have found non-specific, widespread methylation independent of sgRNA expression in multiple cell types, indicating that the further refinement of these tools will be necessary to achieve truly targeted epigenomic editing . FurtherIn addition to CRISPR-Cas9-based editing, other technologies, such as targeted protein degradation, offer a promising method for studying the functions of histone modifications and, potentially, DNA methylation in AML. Proteolysis-targeting chimeric (PROTAC) technology enables the rapid degradation of endogenously tagged proteins. Recently, this was used in the context of MLL-r leukemias to rapidly degrade MLL::AF9 . Using tCRISPR-Cas9 or PROTAC technologies perturb epigenetic protein function by genetic deletion or rapid protein degradation, respectively. In contrast to these approaches, another way to specifically perturb histone modifications and DNA methylation without genetic manipulation is the use of small molecule inhibitors. These are important tools due to the relative ease of their delivery into patients. Indeed, some epigenetic inhibitors are currently being used in the clinic to treat AML patients.The classical hypomethylating agents used in AML treatment (decitabine and azacytidine) are cytidine analogs irreversibly incorporated into the DNA during replication, which target DNMTs for proteasomal degradation . HoweverNPM1-mutated AML [DOT1L inhibitors (Pinometostat/EPZ-5676), along with SNDX-5613 and KO-539 , are being used in clinical trials on MLL-r AML, as well as other subtypes, including ated AML ,110,111.ated AML ,113,114.ated AML . These mDnmt3a-/- murine HSCs [DNMT3A mutant AML cell lines, xenograft models, and leukemic stem cells with DOT1L inhibitors led to reduced proliferation, cell cycle arrest, and differentiation [Despite the fact that both histone modifications and DNA methylation play important roles in gene regulation in AML, the functional interplay between these two types of epigenetic marks remains relatively under-studied. An example of this interplay is the DNA hypermethylation of bivalent domains at the promoters of genes implicated in AML . Anotherine HSCs . DOTL1 ontiation ,118. ThiHistone modifications and DNA methylation play integral roles in maintaining normal hematopoietic development, and their disruption leads to aberrant gene expression patterns which ultimately drive disease. New technological advances such as (epi)genomic editing and single-cell methods will continue to unlock important insights into how epigenetic modifications impact gene regulation in healthy tissues and in the context of disease.


The Notch signalling pathway is a master regulator of cell fate transitions in development and disease. In the brain, Notch promotes neural stem cell (NSC) proliferation, regulates neuronal migration and maturation and can act as an oncogene or tumour suppressor. How NOTCH and its transcription factor RBPJ activate distinct gene regulatory networks in closely related cell types in vivo remains to be determined. Here we use Targeted DamID (TaDa), requiring only thousands of cells, to identify NOTCH and RBPJ binding in NSCs and their progeny in the mouse embryonic cerebral cortex in vivo. We find that NOTCH and RBPJ associate with a broad network of NSC genes. Repression of NSC-specific Notch target genes in intermediate progenitors and neurons correlates with decreased chromatin accessibility, suggesting that chromatin compaction may contribute to restricting NOTCH-mediated transactivation. Notch signalling plays a key role in cell fate transitions, but how Notch activates distinct regulatory networks in closely related cell types is not well understood. Here the authors profile Notch and RBPJ targets in the developing mouse cortex and reveal how transcription factor occupancy and chromatin remodelling interact to direct differential gene expression during differentiation. Upon ligand binding, the NOTCH receptor is cleaved and the intracellular domain (NICD) translocates to the nucleus where it associates with its cofactor, RBPJ, to activate target gene expression2  to postmitotic neuronson2 Fig. . The out18 to perform cell-type specific genome-wide profiling of NOTCH and RBPJ binding in vivo in the developing mouse brain. This reveals dynamic binding patterns in two directly related cell types, RGCs and IPCs, and enables us to compare binding, chromatin accessibility and gene expression during differentiation.Here, we use Targeted DamID (TaDa)4. However, despite their remarkable context-dependent function, cell-type specific binding profiles of NOTCH and RBPJ during mammalian nervous system development have not been determined. This is largely due to the difficulty of capturing NICD in the nucleus21, the short half-lives of both NICD and its canonical target genes22 and the dependence of Notch-signalling on cell-cell contact, which is disrupted by cell sorting. Insights into cell-type specificity of Notch pathway output have come from studying transcriptional regulation of NOTCH-target genes in model organisms27. A simple approach for assessing cell type specific Notch and RBPJ binding patterns, in vivo and genome-wide, would help to reveal how cell-type specific target gene expression is achieved.Downregulation of Notch target genes during neurogenesis has been proposed to result from differential chromatin binding of Notch and RBPJ in RGCs and IPCsin utero electroporation (IUE)18 to map NOTCH and RBPJ binding in the developing mouse brain . IUE of intronDam-plasmids generated reproducible methylation patterns in single brain hemispheres at E17.5  without seemingly affecting neurogenesis . The N-terminal half of the Dam methylase sequence was inverted and flanked by loxP sites  led to a strong reduction in differentiation  of cells were able to differentiate into postmitotic neurons of the cortical plate (CP) after 3 days  fused to intronDam, under the control of RGC-specific (Hes5)38 or IPC-specific promoters  were associated with RGCRBPJ peaks, as compared to 455/1910 (23.8%) found previously by RBPJ ChIP-seq of cortical NSCs37  and Gli2/3, and many upstream genes involved in signal transduction  were clustered using an optimisation approach based on k-means , or in both RGCs and IPCs   Fig. . The maj 7) Fig. . To conf Fig. . T30; Fig. 32. Clusters where NOTCH and RBPJ co-localized , were more accessible than those where only one of the two factors were bound     Fig. . Comparaion Fig. .34 .When NOTCH/RBPJ were bound together in RGCs, they could also be detected after ectopic expression in IPCs, where they mostly co-localized  Fig. . Genes n34 Fig. , and wit4.5 Fig. . Peaks w4.5 Fig. . The RGCsee Fig.  were allsee Fig.  and 5c. see Fig.  or neurosee Fig.  were mos51. 131 genes that were shown to be expressed specifically in RGCs37 (FDR < 10−5) were associated with cluster 6 peaks  showed significantly increased expression upon ectopic NICD expression in the embryonic cortex, as documented previously by RNAseq37 (p < 0.05 and fold-change >1.5); Supplementary Data Sox9, Gli3 and Prdm16  decreased between RGCs and IPCs Fig. , as did 18. Using vectors that overcome background plasmid methylation that can interfere with transient transfection experiments, we were able to achieve genome-wide profiling in limiting cell numbers in vivo, without disruption of the native tissue environment. We profiled NOTCH and RBPJ binding in RGCs and IPCs in the developing mouse cerebral cortex after IUE. We found that NOTCH/RBPJ binding patterns in specific cell types correlate with chromatin accessibility although we also found many putative binding sites of NOTCH or RBPJ in relatively inaccessible chromatin regions. Enrichment of homeobox transcription factor binding motifs at NOTCH/RBPJ sites suggests a role for transcription factors like LHX244 in establishing a permissive chromatin environment to enable a tissue specific response to Notch, in a manner similar to that shown for Runx transcription factors in Drosophila49 and T-cell leukemia48.Intercellular signalling is mediated by signalling pathways that are used iteratively throughout development and disease. How the same signal is interpreted differently depending on cellular context remains largely unanswered. This has been due, in part, to the need for sensitive tools for cell type specific genome-wide chromatin profiling in vivo. Targeted DamID enables genome-wide profiling of DNA- or chromatin-binding without cell isolation, fixation or affinity purification50 and found that ectopically expressed NOTCH and RBPJ could bind, perhaps only transiently, to RGC-specific genes in IPCs. Therefore, additional mechanisms may ensure that RGC-specific NOTCH target genes are inactivated to enable neurogenesis if NOTCH were to remain present during or after the transition of RGC to IPC. One such mechanism could be a reduction in chromatin accessibility at the regulatory regions of Notch target genes which, when paired with a decrease in NOTCH/RBPJ expression, could facilitate efficient repression of RGC-specific genes. Nevertheless, given that NOTCH/RBPJ can bind their target genes in IPCs, we hypothesize that the binding events occurring in RGCs could be maintained in IPCs, making chromatin accessibility changes essential for blocking the activation of RGC-specific NOTCH target genes.To assess the transcriptional activity of the putatively bound loci, we screened publicly available cell-type specific transcriptional data sets55, may influence the progression of specific brain tumour subtypes12.Our data represent a population level view of NOTCH activity and it remains to be determined whether there is heterogeneity of NOTCH/RBPJ binding within cell types at the single cell level. With recent advances in single-cell technology, future experiments may be able to better characterize variability in NOTCH activity within cell populations in the developing cortex. The factors that determine the competence of cells to respond to Notch pathway activation have broad relevance, not only to the multitude of developmental processes in which Notch is involved, but also to pathologies such as cancers. Chromatin accessibility and the tumour cell of origin within the NSC lineage56 was inserted between helix 3 and 4 of the DNA-binding domain of the Dam methylase57 in pPB-PGK-mcherry-Dam17. mCherry-intron1Dam-SV40polyA was cloned into pCAG-IRES-GFP  to give pCAG-mcherry-intron 1Dam. For intron2Dam a modified version of the Promega chimeric intron sequence60 was subcloned into pCAG-mcherry- intron1Dam, replacing intron 1 and modifying the exon junctions. intron2Dam was more efficient, as assessed by RT-PCR, and was used for most experiments.For intron1Dam, the sequence of intron 3 of mouse IghE61 were inserted into the NheI site upstream of mCherry and the XmaI site inside intron2, respectively. The two Lox-sites and intervening sequence were then inverted to give pCAG-flox2Dam.Lox71 and Lox61 sites38, and a 1097 bp fragment of the mouse Tuba1a promoter, Tα140, were amplified from genomic DNA and cloned into SpeI-HindIII cut pCAG-mcherry-intron2Dam. pHes5-d2eGFP was a gift from R. Kageyama. IRES-GFP was removed from pND1-IRES-GFP (gift from F. Polleux) and replaced with Cre to generate pNeurod1-Cre. pTα1-mcherry-NLS-DR was cloned by Gibson assembly from Addgene plasmid 8460362. pCAG-Venus was generated by removing the U6-shRNA cassette from pSCV2 (gift from F. Polleux).A 764 bp fragment of the mouse Hes5-promoter and 5’UTR63. As a control, an empty pCAG-IRES-GFP plasmid was used .For the IUE experiments with constitutively active Notch the plasmid pCIG-NΔECD was used, which consists of pCAG-NΔECD-IRES-GFP and was a gift from G. Del Sal63). Mouse full-length NOTCH was from Addgene 4172864. hRBPJ1 was amplified from cDNA of human ESC-derived NSCs. mCherry(2), mammalian codon-optimized version of mCherry, was from Addgene 8460362. Plasmids for IUE were prepared from Dam-negative bacteria with Endofree Plasmid Maxi kit (Qiagen 12362). Molecular weight ladder is Hyperladder 1 kb (Bioline BIO-33026).The mouse Notch1 intracellular domain with the transmembrane domain (NΔECD) or without the transmembrane domain (NICD) was amplified from pCIG-NΔECD  using CUY650P5 electrodes (Sonidel). DamID plasmids were injected at 1 µg/µl together with pCAG-Venus at 0.25 µg/µl. All other plasmids were injected at 1 µg/µl. Embryos were harvested after 24 hours (E14.5) for TaDa with pHes5 and pTα1, after 72 hours (E16.5) for TaDa with pND1-Cre and after 96 hours (E17.5) for TaDa with pCAG-intronDam. For RGCNotch data, we combined samples from pHes5-mCherry-NICD-intron2Dam, pHes5-mCherry(2)- intron2Dam and pHes5-mCherry-NdE-intron2Dam. IUE of pHes5-NΔECD-intron2Dam did not prevent differentiation, consistent with the very low levels of translation of the Dam-fusion protein28.All mouse husbandry and experiments were carried out in a Home Office-designated facility, according to the UK Home Office guidelines upon approval by the local ethics committee (project licence PPL70/8727). Experiments were done in wild-type MF1 mice. Timed natural matings were used, where noon of the day of plug-identification was E0.5. IUE was performed as previously described24 and staining was performed on 100 µm thick vibratome sections in PBS with 0.3% Triton (PBST) and 3% BSA (Sigma A3608). Antisera were as follows: chicken anti-GFP 1/1000 (Abcam ab13970), rabbit anti-RFP 1/500 (Abcam ab62341), goat anti-Sox2 1/500 (R&D AF2018), rabbit anti-Sox9 (Millipore AB5535), rabbit anti-Prdm16 1/200 , rabbit anti-Pax6 1/500 (Covance PRB-278P), rabbit anti-Hes1 1/100 , goat anti-Gli3 1/500 (R&D AF3690). DNA was stained with DAPI. Fluorescent images were acquired using a Leica SP8 confocal microscope and analysed using ImageJ.For immunostaining, embryos and tissue were processed as previously described15. DamID fragments were prepared for Illumina sequencing according to a modified TruSeq protocol15. All sequencing was performed as single end 50 bp reads generated by the Gurdon Institute NGS Core using an Illumina HiSeq 1500.For DamID after IUE, embryos were cooled on ice, and the electroporated cortex was identified with a fluorescent binocular microscope. Meninges were removed and the electroporated region microdissected. Tissue was then processed for DamID as described previously14  and all resulting binding profiles for one Dam-fusion construct were quantile normalized to each other14. The resulting logarithmic profiles in bedgraph format were averaged for all GATC-bins across the genome and subsequently backtransformed (“unlog”). In parallel, non-normalized Dam-only scores for all GATC-bins were provided separately by the modified damidseq_pipeline as a means to assay chromatin accessibility30. Files were converted to the bigwig file format with bedGraphToBigWig (v4) for visualization with the Integrative Genomics Viewer IGV (v2.4.19).Quality check of *.fastq-files was performed with FastQC (v0.11.5), reads were trimmed with TrimGalore (v0.4.5) and if necessary deduplicated with the Clumpify tool of the BBmap suite . Data processing was automated and parallelized by using workflow scripts interacting with the slurm workload manager (v15.08.13). Preprocessed *.fastq-files were mapped to the mm10 (GRCm38.p6) genome assembly. Reads were binned into fragments delineated by 5’-GATC-3’ motifs (GATC-bins). Individual replicates for the Dam-fusion constructs  were normalized against separate Dam-only replicates  with a modified version of the damidseq pipeline68 was used to call broad peaks for every dam-fusion/dam-only pair on the set of *.bam-files generated by the damidseq_pipeline, using Dam-only as control. Peaks were filtered stringently for FDR < 10−5 and were only considered if present in all pairwise comparisons for a particular experimental condition . Relevant Ensembl gene and genomic feature annotations for mm10 were acquired via biomaRt (v2.38.0). Peaks were annotated to genes with bedtools (v2.26.0) by identifying the closest TSS of a protein coding gene along the linear genome. Upstream sequences were defined as regions covering 5 kb upstream of TSS of all annotated transcripts from protein coding genes. Intergenic regions are the areas outside protein coding genes . To avoid artificial inflation of associations, overlapping regions were collapsed in a feature-wise manner via the bedr R package (v1.0.7) and bedtools (v2.26.0). Given the inherent ambiguity of genomic features, particular genomic areas can be part of two features. Associating peaks with the defined genomic features was performed using gat (v1.3.2) with entire chromosomes specified as workspace and 1 mio computed samples. The relative overlap of peaks with genomic features normalized for the combined length of all included peaks (percent_overlap_size_track) was visualized. Peaks from ATAC-seq in E13.5 forebrain (ENCFF798QON.bam31) were called with Macs2 (v2.1.2) using the same broad peaks settings as above but without control. Raw data from RBPJ ChIP-seq in mouse cortex37 was not publicly available, but peaks were extracted from the Supplementary Information, coordinates converted to mm10 and genes called as described above.Macs2 (v2.1.2)Overlapping peaks derived from different Dam-fusion constructs were merged into consensus peaks via bedtools (v2.26.0). Averaged binding intensities were normalized for length of the consensus peak region, converted to z-scores and subjected to unsupervised clustering to identify stable binding patterns. The optimal cluster number was determined with the help of the R packages factoextra (v1.0.5), clValid (v0.6-6) and mclust (v5.4.5). k-means as the clustering approach was chosen and its parameters optimised by calculating silhouettes with the R cluster package (v2.0.7-1). Dimensionality reduction for visualizing the distribution of clustered peaks was conducted with the Rtsne package .47. Enriched features were detected by uploading coordinates for all peaks of individual Notch/RBPJ k-means clusters to the i-cisTarget online platform  after conversion to mm9 with the liftOver function of rtracklayer (v1.42.2). Normalized enrichment scores across all features and all k-means clusters were converted to z-scores, subjected to hierarchical clustering by calculating a matrix of euclidean distances with the hclust (method = complete) and dist commands of the R stats package (v3.6.1) and visualized by using the ggdendro package (v0.1.20). The branch depth was reduced to 4 for simplicity with the cut function of the stats package and the R dendextend package (v1.10.0). De novo motif analysis on binding sites was performed with Homer69 (findMotifsGenome.pl) and motifs consisting of 5’-GATC-3’ were manually removed from the results. Known motif enrichment was analysed with AME of the MEME suite with the following scoring method: Average odds score; Fisher’s exact test, E-value ≤ 1808; Motif databases: Jaspar Core Vertebrates non-redundant, UniProbe Mouse, Jolma2013 Human and Mouse. Sequences corresponding to all peaks were first retrieved from the Biostrings genome object for the UCSC mm10 genome  with the getSeq command of the Biostrings R package (v2.50.2).Comparative motif analysis was performed with i-cisTargetGene Ontology term enrichment of genes associated with peaks was done using the broadenrich command of chipenrich (v2.10.0) for all available mm10 genesets in chipenrich.data (v2.10.0) (locusdef = nearest_tss). Gene identifiers were converted with AnnotationDbi (v1.48.0) based on the org.Mm.eg.db (v3.10.0) database. Enrichment of GO terms annotated to biological processes (GO_BP) was visualized by plotting -log10-transformed p-values, if the calculated p-value was <0.01 in at least one of the compared conditions or clusters. GO terms belonging to manually curated lists of keywords associated with indicated signalling pathways or biological processes were highlighted in the same colors in bar- and violin/dot-plots.Mapped reads (see DamID-seq data processing) were extended to 150 bp with bamCoverage from the deepTools suite (v3.1.3). The resulting *.bedgraph files were read into R, reads binned into 500 bp bins or into the regions covered by all NOTCH/RBPJ peaks and Pearson Correlation Coefficients were calculated with the cor command of the R stats package (v3.6.1). Coefficients for all pairwise comparisons were plotted as tiled heatmap.34 were acquired from GEO (GSE65000) and trimmed with TrimGalore (v0.4.5). *.fastq.gz files were pseudoaligned with kallisto  and statistical analysis was performed with sleuth (v0.30.0) by specifying full models for pairwise combinations of cell types. Reads were aggregated per gene rather than transcript while preparing the sleuth object with the sleuth_prep command . Significance of differential expression was determined via q-values derived from wald tests (sleuth_wt) based on the full model. Raw data from bulk RNAseq upon NICD overexpression37 was not publicly available, but genes with a p-value for differential expression <0.05 were extracted from the Supplementary Information.Bulk RNAseq datasets for mouse cortex cell types35 and E14.550 were sourced from GEO as raw count matrices with the accession number . GSE107122 (E13.5) was read into R as a Seurat Object via the corresponding R package Seurat . Cells were filtered for maximal 4800 genes per cell and an upper threshold of 8% reads allocated to mitochondrial genes, the data log-normalized , scaled and centred dependent on nUMI and percent of reads aggregated on mitochondrial genes. Dimensionality reduction via PCA preceded clustering of cells using 5 dimensions as evaluated by JackStraw analysis. The Wilcoxon rank sum test was used to identify significantly differentially expressed genes for every cluster compared to all other clusters or for sets of clusters annotated to their respective cell types  via the FindAllMarkers command . GSE123335 (E14.5) was read into R as a dgCMatrix via the methods package (v3.6.1) and processed by creating a Seurat Object with Seurat . To properly integrate all 6 replicates combined in the matrix, they were first separated via SplitObject, subsequently normalized via NormalizeData and further prepared for integration via Canonical Correlation Analysis with FindVariableFeatures and FindIntegrationAnchors71. To avoid detection of differentially expressed genes, nfeatures was set to 18361 corresponding to the number of genes detected across all 6 scRNAseq replicates. Dimensionality reduction was performed with the RunPCA and RunTSNE commands based on 90 dimensions. Differential expression analysis was performed cluster-wise as indicated for GSE107122 data with the FindMarkers command.Single cell RNAseq datasets derived from mouse cortices at E13.5Associations between sets of peaks and significantly differentially expressed genes from bulk RNAseq or scRNAseq data were modelled as binomial distributed, since multiple peaks can be linked to the same gene. Based on the assumption that individual peaks have the highest likelihood to associate with the gene whose TSS is closest, associations of significantly and non-significantly differentially expressed genes with peaks as well as the total number of significantly and non-significantly differentially expressed genes were summed at a particular significance threshold . To test for enrichment of peak-to-gene associations, the binom.test command of the R stats package (v3.6.1) was used . This test was repeated across multiple gene expression significance thresholds and peak sets . The resulting p-values were adjusted due to multiple testing with the Bonferroni correction as implemented in the p.adjust command of the R stats package . Adjusted p-values and the number of peaks associated with expressed genes (peaksAtGenes) were visualized as a function of the significance threshold of differentially expressed genes (-log10 transformed).37 and genes associated with RPBJ-peaks from either DamID-seq or RBPJ ChIP-seq (upon NICD overexpression)37 was modelled as hypergeometrically distributed. To assess the background overlap level between peaks and differentially expressed genes, the same number of randomly chosen genes as associated with the corresponding peaks were sampled from the mm10 genome (GRCm38.p6). Sampling was repeated 1000 times for both sets of peaks in the same manner and p-values were calculated with the phyper function of the R stats package .The overlap between bulk RNAseq data derived from mouse cortices with NICD-overexpression72 with the midline for TaDa ratio tracks set at 1 and for ATAC-seq set at 0. Peak or gene coordinates were saved in *.bed format and supplied as features to the getPlotSetArray command of Seqplots (v1.12.1)73. Quantile normalized, averaged and backtransformed TaDa profiles or quantile normalized chromatin accessibility profiles were provided in bigwig format. plotAverage and plotHeatmap were used to visualize and average the binding intensities across all supplied coordinates. Signal from the mitochondrial genome, the IghE-intron, the Hes5-, Tuba1a- and NeuroD1-promoters were removed for average plots of chromatin accessibility TaDa. Statistical analysis of chromatin accessibility in RGCs and IPCs was done with a Kruskal Wallis test and a post-hoc pairwise Wilcoxon rank sum test. Plasmid maps were generated using SnapGene. Figures were assembled in Adobe Illustrator.Genome browser views were generated using the Integrative Genomics Viewer IGV (v2.4.19)Further information on research design is available in the Supplementary InformationDescription of additional Supplementary FileSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting Summary


Chromatin maintenance and remodeling are processes that take place alongside DNA repair, replication, or transcription to ensure the survival and adaptability of a cell. The environment and the needs of the cell dictate how chromatin is remodeled; particularly where and which histones are deposited, thus changing the canonical histone array to regulate chromatin structure and gene expression. Chromatin is highly dynamic, and histone variants and their chaperones play a crucial role in maintaining the epigenetic regulation at different genomic regions. Despite the large number of histone variants reported to date, studies on their roles in physiological processes and pathologies are emerging but continue to be scarce. Here, we present recent advances in the research on histone variants and their chaperones, with a focus on their importance in molecular mechanisms such as replication, transcription, and DNA damage repair. Additionally, we discuss the emerging role they have in transposable element regulation, aging, and chromatin remodeling syndromes. Finally, we describe currently used methods and their limitations in the study of these proteins and highlight the importance of improving the experimental approaches to further understand this epigenetic machinery. Chromatin protects and regulates the DNA; it is also tightly involved in nuclear processes that ensure the proper functionality of the cell. The basic unit of the chromatin is the nucleosome, composed of an octamer of histones  that surround 146 base pairs (bp) of DNA . The rolAlthough during the last 10 years the study of histone variants, particularly of H3 and H2A, and their chaperones has increased considerably, the majority of these studies have focused on a few cellular processes and pathologies, resulting in an imbalanced knowledge and scattered information. Given this, in the present work, we aim to focus on the involvement of histone variants, particularly H3 and H2A, and their chaperones in distinct processes, highlighting their adaptiveness as an important component of replication, transcription, DNA repair and regulation of transposable elements . For morIn order to maintain the structure of the chromatin, histones play a critical role. Two broad types of histones have been described. The first type comprises what are commonly known as canonical histones , and the second class encompasses histone variants . Replication-coupled histones’ genes are encoded in clusters , they are intronless, their messenger RNAs (mRNAs) have a special 3′-loop end and are especially transcribed and deposited during the DNA synthesis (S) phase . Meanwhiin vitro without the need for ATP  complex and the MCM2 (minichromosome maintenance complex component 2). Different studies have shown that the SPT16 (suppressor of Ty 16) subunit of the FACT complex displaces H2A-H2B dimers, while the other subunit, the structure-specific recognition protein 1 (SSRP1), stabilizes the H3-H4 tetramer . The abiThe cell differentiates between transcription states not only by the histone PTMs, but also by differentially depositing histone variants at particular genomic regions . This isHistone variants H3.1 and H3.2 show a high similarity to H3.3; however, one of the unique PTMs of H3.3 is phosphorylation of serine 31 (S31ph), which has previously been linked to processes like mitosis . This unAnother histone variant that has been broadly linked to transcriptional regulation is H2A.Z. This histone was originally linked to transcriptional activation . MoreoveA third variant involved in the transcription of genes in brain and testes is H2A.B. Cells are constantly exposed to DNA damage insults, and in order to counteract them, they have developed different DNA damage response (DDR) pathways. Importantly, distinct histone variants and their chaperones are implicated in some of these pathways . Once thIt was previously reported that H3.3 can be deposited by HIRA at UVC-damaged chromatin , howeverAnother H3 histone variant, whose role in DNA repair has not been clearly established, is CENPA . RecentlThe role of histone variants and chaperones in replication, transcription, and DNA damage repair are the most common studied molecular mechanisms. However, recent findings about their importance in genomic stability and chromatin structure related to transposable elements is starting to unravel, and we discuss the findings regarding this topic in the next sections.Mobile genetic elements (MGEs) are any type of genetic material that can move within a genome or between cells . The setTransposons contribute to the variation, adaptation, and evolution of genomes through the duplication or deletion of genes or their regulatory elements . TEs canThe CAF-1 complex is an H3-H4 chaperone conserved among all eukaryotes. It has important roles during DNA replication and repair, regulation of gene expression, and maintenance of chromatin accessibility . The CAFvia H3K9me3 and H4K20me3 marks. Specifically, CHAF1A reinforces transcriptional repression through its interaction with members of the NuRD complex  and ESET, while SUMO2 orchestrates the provirus repressive function of the canonical zinc finger (ZNF) protein 809 (ZFP809)–TRIM28–ESET machinery by sumoylation of TRIM28.The CAF-1 complex has several interactors. Another important histone chaperone is the FACT complex, which mediates the deposition of H2A/H2B histones and binds to H3-H4 dimers simultaneously . This coAltogether, these results supported the mechanism that the SSRP1 subunit of the FACT complex recruits USP7 to repress MERVL and MERVL-fused genes in ESCs by impeding the ubiquitination of H2Bub. However, it is possible that other FACT-associated proteins may contribute to the repression of MERVL and MERVL-fused genes or that other pathways repressing cryptic transcription initiation may be regulated by the FACT complex itself .As we addressed previously, the histone variant H3.3 can be incorporated at distinct regions of the chromatin by either the HIRA or ATRX–DAXX histone chaperone complexes . While HIn this context, two models have been proposed for the mechanism by which DAXX and its interactors repress retrotransposons. Both models rely on the fact that ERVs are silenced through H3K9me3 by ESET  and TRIMOn the one side, a study by On the contrary, a structural and biochemical study by The set of elements of the DAXX-mediated transposon regulation mechanism is continuously being elucidated. Recently, The specific activity of HIRA lies in its ability to recruit and form complexes with histone-modifying proteins such as histone acetyltransferases and HDACs and to help regulate specific histone variant depositions . In geneFor the proper functioning of cellular processes, fine-tuning of the chromatin must be assured through the previously described mechanisms and genomic components that involve a balance of histones and their chaperones. Nevertheless, in health and disease the balance and function of the histones and chaperones changes, as we discuss in the following sections. Aging is a natural process, where recently the role of these epigenetic components is being elucidated. On the other hand, diseases, such as cancer, alterations, and mutations in both histones and their chaperones have been described. We will not review the information on cancer, but we invite the reader to refer to the following literature on the topic: Aging is a life-lasting event that results from the accumulation of damage and different molecular and cellular alterations through time, leading to a deterioration of physiological functions that are necessary for survival. Epigenetic alterations are a major contributor to cellular senescence, including the exchange of replication coupled histones for variants, and their concomitant accumulation. Given this, it is important to address the latest findings about the role of histone variants in cellular senescence and how they can contribute to altered gene expression and overall aging in proliferative vs. non-proliferative cells .Cellular senescence can be defined as a permanent or highly stable state of cell cycle arrest . In prolAs mentioned, senescence involves changes at molecular and cellular level, which can be related to organelle function, gene expression, epigenetic regulation, disruption in the energy metabolism, etc. Given this, several biomarkers have been established to characterize the senescent phenotype. A senescence-associated secretory phenotype (SASP) of several proinflammatory molecules, like cytokines and some other molecules, such as growth factors and proteases, is seen . BesidesIt is interesting to highlight that there are numerous epigenetic alterations seen as important elements of the senescent phenotype. Yet, only a few histone variants, such as macroH2A and γH2AX, have been studied, while others, like H3.3, have started to become widely explored, particularly because of their role in chromatin regulation and gene expression.In an adult organism, proliferative cells are expected to accumulate H3.3 in their chromatin due to the replication-independent kinetic deposition of the variant compared to the canonical H3.1/H3.2 histones. Some authors hypothesize that the accumulation of H3.3 in certain regions can be a strategy of the cell to follow a semiconservative replication and to “hold/mark” the sites where H3.1/H3.2 need to be deposited once the cell replicates; since eventually these cells stop replicating, H3.3 stays in those regions substituting the canonical histone . This H3The PTMs in canonical or histone variants add another level of complexity to the mechanisms of H3.3 accumulation through the aging process. Enzymes in charge of establishing PTMs selectively identify protein sequences, thus affecting the outcome: the functional readout. In this sense, the ZMYND11 protein specifically recognizes H3.3K36me3 in the body of genes where it regulates the elongation rate of the RNA pol II . AdditioChromatin reorganization is an important feature of senescent cells. When seen under a microscope with 4′-6-diamino-2-phenylindole (DAPI) staining, senescent cells show punctate DNA foci instead of the characteristic heterogeneous distribution of the staining that proliferating cells have. These are the SAHF, and they are enriched with macroH2A. The deposition of this variant is dependent on the HUCA histone chaperone complex activity , the samIL1B, CCL2, and CXCL5, as seen in aged tissues like the liver, kidney, and brain . This PTM is an important regulator of the HIRA complex: when absent, H3.3 deposition is reduced . InteresMost of the works and reviews show evidence of how epigenetic alterations are related to senescence through the perspective of cellular replication. Meaning, most of them focus on available reports on proliferative cells, such as fibroblasts . NeverthDuring the neurogenic process in embryogenesis, there is a differential deposition of histone variants. H2A.1 is enriched twice as much as H2A.2 both in neurons and neuroblasts. Nevertheless, during postnatal development H2A.1 decreases, suggesting that H2A.2 has more stability. On the other hand, another H2A variant, H2A.Z presumably deposited by the INO80 subfamily chromatin remodelers , accumulNanog and Oct4, the H3.3 enriched in the gene bodies is lost  showed that when the expression of pluripotency genes decreases, such as  is lost ; while t is lost . Further is lost . Additio is lost . This plBdnf Exon IV, c-Fos, Dusp6, among others. These genes, which are known as immediate early genes (IEGs) because they are transiently and rapidly activated upon neuronal activation, need a rapid chromatin remodeling, in part mediated by DAXX, which loads H3.3 at their regulatory elements  of human postmortem brains diagnosed with major depressive disorder  have been described . These arsk-2 gene in Coffin-Lowry syndrome, affecting phosphorylation of histone H3  4 syndrome, characterized by immunodeficiency, neurologic defects, and reduced growth  histone H3 (H3K4), leading to reduced histone methylation . Anotherstone H3 . As mentant H3.3 . This sud growth . TherefoHIRA is included. As it was previously mentioned, HIRA chaperone, when forming a four-subunit complex, is in charge of the deposition of H3.3 in many regions of the genome; for example, DNA damage sites and also bivalent genes in ESCs. For hematopoietic stem cells (HSCs) to function properly, epigenetic regulation needs to be carried out, including chromatin remodeling and histone PTMs. Therefore, aberrant epigenetic modifications may lead to impaired HSC development , it was proven that HIRA KO restricts the access to chromatin affecting regions crucial for the transcription of HSC-specific genes. ir genes .The phenotype seen in these patients is very heterogeneous, including heart defects, parathyroid hypoplasia, immune deficiency, and hypocalcemia . Given tATRX is a chromatin remodeler named after the developmental syndrome on which it was found mutated, the a-thalassemia/intellectual disability syndrome, X-linked . ThroughWith a DNA fiber analysis after HU-mediated replication fork stalling, one study evaluated the proportion of restart-competent replication forks between DAXX, FANCD2 and DAXX/FANCD2 double-deficient cells and found out they were similarly reduced. These results suggest that, when replication stress occurs, FANCD2 is ubiquitinated and locates to stalled replication forks to recruit homologous recombination factors and promote a replication fork start, while suppressing new replication origins; cooperating with the ATRX/DAXX complex, most likely including its H3.3 chaperone activity .Drosophila it was found that the clusters of genes of the linker histone H1 and the core histones  could be distinguished by the transcription factors that bind to the respective promoters. While TBP (TATA-box-binding protein)-related factor 2 (TRF2) regulated the H1 gene promoter, the core histones genes were controlled by TBP/TFIID  . This prBP/TFIID . This diin vivo: SNAP-tag System.At the protein level, a collection of methods and techniques have evolved to study the interactions of histones and chaperones. For a detailed revision on this topic, based on H3 but applicable to all histones, please refer to One of the first methods to isolate histones was through acid extraction of whole protein extract . This me7 cells.To study the deposition pattern of histones and their chaperones in chromatin, one of the gold standard methods is ChIP . This teNowadays, there are also several variations of the technique that grants different approaches, like the chromatin immunoprecipitation followed by selective isolation of chromatin-associated proteins (ChIP-SICAP). This ChIP-based technology allows differentiating stable from labile protein interactions and capture the stable ones using DNA biotinylation . Chromatin vivo tracking of newly synthesized proteins via a fluorescent microscope. Based on this method, the “quench-chase-pulse” assay was developed to follow and distinguish between new and old histones. in vivo dynamics, order of deposition, chaperones involved, and the distribution pattern in the nucleus. All of which provide a better understanding of these essential proteins.Finally, another technique that has been widely used to study histones and chaperones is the SNAP-tag system developed by During the last few years, the study of histone variants and their chaperones has increased considerably. However, most of these studies have focused on only a few variants and chaperones, resulting in scarce information. Aside from H3, H2A, and its variants, further studies addressing the rest of the histones are needed to have a bigger picture of how they influence chromatin regulation. Nevertheless, new emerging technologies are improving the experimental approaches for their study. Given this, we highlight the importance of further research about histone variants and their chaperones in the associated syndromes, physiological processes like aging, and their role in molecular processes, such as replication, transcription, DNA damage and their contribution to the regulation of transposable elements. This will further shed light on their involvement as important regulators of the ever-changing chromatin.