Mesenchymal stem cells (MSCs) are considered the most promising seed cells for regenerative medicine because of their considerable therapeutic properties and accessibility. Fine-tuning of cell biological processes, including differentiation and senescence, is essential for achievement of the expected regenerative efficacy. Researchers have recently made great advances in understanding the spatiotemporal gene expression dynamics that occur during osteogenic, adipogenic and chondrogenic differentiation of MSCs and the intrinsic and environmental factors that affect these processes. In this context, histone modifications have been intensively studied in recent years and have already been indicated to play significant and universal roles in MSC fate determination and differentiation. In this review, we summarize recent discoveries regarding the effects of histone modifications on MSC biology. Moreover, we also provide our insights and perspectives for future applications. Mesenchymal stem cells are multipotent cells that can differentiate into various lineages whose nomenclature remains inconsistent. Apart from “mesenchymal stem cells”, MSCs are also called “mesenchymal stromal cells”, “bone marrow stromal cells” (BMSCs) and “multipotent stromal cells” . FriedenAccording to the International Society for Cellular Therapy (ISCT) , MSCs muGiven the great clinical and scientific significance of MSCs, understanding of their biological characteristics in vivo and in vitro, including their proliferation, differentiation, cellular senescence and responses to abnormal microenvironments, is urgently needed. In this review, we systemically summarize the most recent progress in the field of histone modification-mediated control of MSC biological processes and our perspectives on the latest advancements.Histone modification refers to posttranslational modification of histones. Most histone modifications involve sites within the first 30 amino acids of the N-terminal domains of histones , such as H3K4, H3K9 and H3K27 . There aHistone methylation, which is mediated by histone methyltransferases (HMTs) and histone demethylases (HDMs), mainly influences lysine and arginine residues on the histone side chains; through this process, lysine can be mono-, di- or trimethylated. Different histone methylations affect gene transcription in different ways in cooperation with other identifying proteins –25. HistAs mentioned above, many types of histone modifications exist apart from methylation and acetylation. The major enzymes and effector molecules corresponding to these modifications are summarized in Table RUNX2 and OSX in osteogenic differentiation, PPARG and CEBPA in adipogenic differentiation [SOX9 in chondrogenic differentiation  . A previs CXCL12 .To further clarify the exact roles of histone modifications in these various MSC processes, we will discuss how specific histone marks and histone-modifying enzymes impact the differentiation of MSCs.Hoxa10, a BMP2-inducible gene, impairs osteogenesis by decreasing H3K4 methylation [Runx2 and results in upregulation of osteogenic differentiation. Odontoblasts are cells that secrete dentin during tooth development. These cells differentiate from MSCs under the control of various signaling pathways, including the Wnt, Bmp, Shh and Notch pathways [Wnt5a, a member of the Wnt ligand family, as well as in odontogenic differentiation [Methylation of H3K4 is associated with an active or poised transcription state and is found in the promoters of most genes –49. Somehylation . Consisthylation , 52. Knopathways –55. Zhountiation .apM1 exhibit increased H3K4me3 levels in MSCs during adipogenic differentiation [Ash1l, an H3K4 methyltransferase, promotes adipogenesis while suppressing osteogenesis and chondrogenesis by affecting certain master transcription factors. Intriguingly, both ASH1L and H3K4me3 are present at the transcription start sites (TSSs) of Osx, Runx2 and Sox9, whereas only H3K4me3 is present at the TSS of Pparg. Therefore, silencing of Ash1l downregulates H3K4me3 levels on the Osx and Runx2 promoters but not on the Pparg promoter, consistent with the impact of Ash1l silencing on differentiation [In addition to the promoters of genes associated with osteogenesis, those of adipose tissue-specific genes such as ntiation . The H3Kntiation . A recenntiation . Furtherntiation .Runx2. Euchromatin HMT1 (EHMT1), also known as G9a-like protein (GLP), specifically dimethylates H3K9. Balemans and colleagues reported that knockdown of EHMT1 decreases H3K9me2 levels on the promoters of Runx2 and Col22a1 and thereby upregulates the transcription of these genes in brain and bone tissues. Although the authors did not provide direct evidence that EHMT1 regulates the osteogenic differentiation of MSCs, they found a severe type of craniofacial bone malformation, Kleefstra syndrome, in Ehmt+/− mice [H3K9 dimethylation and trimethylation are both repressive histone modifications and are mainly catalyzed by G9a/GLP and SUV39H1/2, respectively, mediating the formation of heterochromatic regions through interaction with HP1 , 62. Kno+/− mice . In addi+/− mice . KnockdoPparg promoter regions and the treatment with BIX01294 (a G9a inhibitor) thereby promotes PPARγ expression and adipogenic differentiation [Pparg and Fabp4 promoters, ultimately promoting adipogenic differentiation by lowering the H3K9 methylation levels in these regions [JMJD1C increases H3K9me2 levels on the C/EBP and PPARG promoters and suppresses adipogenesis by decreasing the expression of these master transcription factor genes [Cebpa promoter [Cebpa promoter region and examined their regulatory effects on gene expression and adipogenesis. These H3K4/H3K9me3 bivalent chromatin domains are induced by DNA methylation and SETDB1 recruitment [Cebpa promoter as well as on Wnt pathway gene promoters and promotes adipogenic differentiation by facilitating C/EBPα expression and inhibiting the Wnt signaling pathway [With regard to adipogenic differentiation of MSCs, G9a, an HMT that specifically methylates H3K9me1 and H3K9me2, has been proven to regulate PPARγ expression through enrichment of H3K9me2 on ntiation . In addi regions . Inhibit regions . Moreoveor genes . Knockdopromoter . Anotherruitment . Similar pathway , 72.Sox9, has shown that this molecule promotes chondrogenic differentiation by recruiting the H3K9 demethylase PHF2 to the promoters of the Sox9 target genes Col2a1 and Aggrecan, thereby decreasing H3K9me2 levels in these regions [Sox9 and thus upregulates SOX9 expression [Research on AT-rich interactive domain 5b (Arid5b), a transcriptional coregulator of  regions . Moreovepression . AccordiWnt genes, including Wnt1, Wnt6, Wnt10a, and Wnt10b [Runx2 and Tcf7 promoters [Runx2, Oc, Pparg and Cebpa, and knockdown of EZH2 or overexpression of KDM6A promotes osteogenesis [FHL1 and the osteogenesis regulators ZBTB16 and MX1 and establishes H3K27me3 modifications. Overexpression of EZH2 decreases the expression of these genes, which downregulates RUNX2, OPN and OC  [H3K27 methylation is another heterochromatic histone modification associated with transcriptional repression –76. Wu ad Wnt10b , suggestromoters . Similarromoters . In addiogenesis . A recenocalcin) .Wnt genes and subsequent repression of Wnt gene expression.EZH2 and KDM6A exhibit different regulatory functions in adipogenesis than in osteogenesis; a previous study revealed that overexpression of EZH2 or knockdown of KDM6A promotes adipogenic differentiation of MSCs . HoweverKdm6b−/− mice showed that KDM6B is recruited to the promoter of Runx2, a critical regulator of chondrocyte maturation and endochondral bone formation, and Ihh and activates the expression of these genes by decreasing the levels of repressive H3K27me3 marks [Sox9 and therefore inhibits chondrogenic differentiation through repression of SOX9 expression. These results suggest that both KDM6A and KDM6B play essential roles in the entire process of chondrogenesis, from the initial stage of differentiation to the maturation of chondrocytes.In addition to affecting osteogenesis and adipogenesis, the H3K27me3 demethylases KDM6A and KDM6B have also been reported to facilitate the chondrogenic differentiation of MSCs –87. A ste3 marks . Anothere3 marks . A furthSetd2 in Prx1-Cre mice decreases bone formation. RNA-seq and ChIP-seq analyses have shown that loss of Setd2 results in downregulation of H3K36me3 levels on the Lbp gene and impairs the transcriptional initiation and elongation of this gene [H3K36me3 is a histone mark that triggers transcription elongation . SETD2, his gene . In addihis gene . Genome-his gene .The impact of H4K20 methylation on gene transcription is intriguing. H4K20 monomethylation is found in euchromatic regions and is associated with active transcription, while H4K20 dimethylation and trimethylation are more related to transcriptional repression and chromatin compaction –93. SETDOct4, Sox2, and Nanog, through upregulation of H3R17me2 levels on their promoter regions. In addition, CPP-CARM1 treatment enhances osteogenic, adipogenic and myogenic potential [aP2, an adipogenic gene, and induce aP2 expression by upregulating H3R17 methylation [aP2 promoters in C3H10T1/2 cells and then facilitates the expression of these genes via recruitment of BRG1, an ATPase subunit of SWI/SNF chromatin-remodeling enzymes [In addition to those on lysine residues, histone modifications on arginine residues also influence MSC differentiation. Coactivator-associated arginine methyltransferase 1 (CARM1), a protein arginine methyltransferase (PRMT) also known as PRMT4, targets histone H3 asymmetric methylation on arginine residues 17, 26 and 42 , 96. Delotential . With reotential . CARM1 ahylation . PRMT5,  enzymes .Bmp2, Bmp3, Bmpr1b and Runx2, and knockdown of PCAF significantly impairs osteogenic differentiation of MSCs. In addition, osteoporotic mice show lower expression of PCAF in bone tissue than control mice [Wnt1, Wnt6, Wnt10a, and Wnt10b and increases the expression of these genes through upregulation of H3K9ac levels. This activation of Wnt signaling results in enhanced osteogenesis [OC, Opn, Bsp2, Osx, and ALP partly by binding to the Runx2 C-terminus and adjusting Runx2 activity. HDAC1 also affects osteogenic differentiation. Lee and colleagues reported that HDAC1 recruitment to the promoters of Osx and OC is reduced during osteogenesis of mouse BMSCs, leading to upregulation of H3K9 and H4 acetylation [JAG1 [Col1a1 and Runx2 has recently been shown to be decreased in chondrogenic cells from Hdac3–CKOPrrx1 mice in osteoinductive culture, indicating a supportive role of HDAC3 in osteogenic differentiation [HATs and HDACs are both essential for osteogenic differentiation. PCAF, an H3K9 acetyltransferase also known as KAT2B, is recruited to the promoters of rol mice . GCN5, aogenesis . Notablyogenesis –103. Sevogenesis –106, indogenesis –109. Thetylation . Furthertylation . Wang anon [JAG1 . In addintiation . Anotherntiation .Pparg2 promoter and enhancer regions with enhanced H3/H4ac and H3K27ac, respectively [Pparg2 and Prdm16 promoters and increase the H3K9ac levels on the sites. Depletion of both Gcn5 and PCAF suppresses adipogenic differentiation of mice preadipocytes [Hdac9-KO transgenic mice [Cebpa promoter along with USF1 and p300 and that KO of Hdac9 promotes adipogenic differentiation of preadipocytes. However, a study on HDAC9 lacking the deacetylase domain showed that this effect of HDAC9 occurs through a deacetylase-independent mechanism. Although negative roles of HDACs in adipogenesis have been reported, Huang and colleagues proposed that HDAC6 facilitates adipogenic differentiation [Hdac6 with miR-22 represses adipogenic differentiation and relevant transcription factor expression but promotes osteogenic differentiation.Depletion of CBP/p300 with ribozyme strongly represses the expression of PPARγ-targeted genes and thus attenuates adipogenic differentiation of preadipocytes . Furtherectively , 117. GCipocytes . Yoo andipocytes  investignic mice ; such stntiation . Their sCol2a1 promoter regions in an interaction with Sox9 and promotes Col2a1 expression as well as chondrogenesis. Another study revealed that p300 promotes Col2a1 expression and chondrogenesis by increasing the histone acetylation levels of the Col2a1 gene [Hdac4-deficient mice show a phenotype with ectopic and early-onset chondrocyte hypertrophy, indicating upregulation of chondrogenic potential. In contrast, positive chondrogenic effects of the HDACs HDAC7 and HDAC3 have been identified by Bradley and colleagues [Hdac7 promotes chondrogenesis through upregulation of β-catenin. In addition, HDAC3 is recruited to the promoter of Phlpp1, a component regulating Akt signaling, and promotes chondrogenesis by repressing Phlpp1 expression and upregulating Akt signaling. However, HDAC7 is highly expressed in proliferating chondrocytes, while HDAC3 is highly expressed in prehypertrophic chondrocytes, suggesting that different HDACs exert various functions at different stages of chondrogenesis.Tsuda and colleagues first reported the positive function of CBP/p300 in chondrogenesis , finding2a1 gene . HDACs h2a1 gene , demonst2a1 gene . Similar2a1 gene . Overexplleagues , 127. DeIn addition to osteogenic, adipogenic and chondrogenic lineages, highly plastic and multipotent MSCs from different germ layers can differentiate into other cell lineages, such as neuron, epithelial cell, cardiomyocyte, hepatocyte and islet cell lineages, under certain induction culture conditions. Although the exact mechanism of transdifferentiation is largely unknown, epigenetic regulation has been reported to be critical in the process , 34. In PIP5K1C, a neuron-related gene regulating Ca2+ signaling, and downregulates PIP5K1C expression. Accordingly, knockdown of EZH2 promotes the neuronal differentiation of MSCs through activation of PIP5K1C-mediated Ca2+ signaling [CD133 and GFAP, by downregulating G9a as well as H3K9me2 levels at repressor element-1 (RE-1) of these genes [EZH2 is recruited to the promoter of ignaling . The G9ase genes . In addise genes . These rse genes . Recentlse genes .GATA4 and Nkx2.5, indicating that histone acetylation levels are possibly more vital than DNA methylation levels during cardiomyogenic differentiation [GATA4 and Nkx2.5 and enhances the expression of these genes under cardiomyogenic induction conditions [GATA4, Nkx2.5, CTnT, and MHC, thereby promoting cardiomyogenic differentiation [Hdac2 enhances the expression of the cardiomyocyte-specific genes Myh6 and Tnni3 through upregulation of both H3 and H4 acetylation levels on the corresponding promoters.Suberoylanilide hydroxamic acid (SAHA), an HDAC inhibitor, is much more powerful than 5-azacytidine, a DNA methylation inhibitor, in inducing the expression of the early cardiomyocyte-specific genes ntiation . GCN5 plntiation , 134. GCnditions . In addintiation . These fntiation , who demIn addition to cardiomyogenic differentiation, HDAC inhibitors can also promote hepatic differentiation of MSCs , 137. SnThe numbers of MSCs isolated from tissues are usually insufficient to meet clinical needs. Therefore, these primary MSCs are usually expanded in vitro. However, in vitro culture changes the morphology and reduces the differentiation potential and proliferation ability of late-passage MSCs, while in vivo senescence disrupts tissue homeostasis and eventually leads to aging-related diseases , 141. MeEzh2 results in premature senescence of MSCs in a study on Ezh2-CKONestin transgenic mice [− signature, express much less EZH2 than control MSCs. Downregulation of Ezh2 decreases H3K27me3 marks on the promoters of p15INK4b, p16INK4a, the cell cycle inhibitor genes p21CIP1 and p27KIP1 and facilitates the expression of these genes. Furthermore, KO of Ezh2 increases the percentage of SA-βGal+ cells, directly indicating that cellular senescence is upregulated.During cellular senescence, the repressive histone modification H3K27me3 is downregulated, indicating its vital role in aging , 146. Renic mice . Aged MSWRN in MSCs decreases H3K9me3 on α-Sat and Sat2 loci and upregulates the transcription of these genes. Knockdown of SUV39H1 or HP1α, a cofactor of SUV39H1, results in downregulation of global H3K9me3 levels and MSC senescence, while overexpression of HP1α upregulates H3K9me3 levels and therefore represses MSC senescence. Similarly, MSCs with catalytically inactivated endogenous SUV39H1 exhibit the same phenotype of accelerated cellular senescence, indicating that histone modifications induced by SUV39H1 and HP1α play significant roles in MSC senescence.Another HMT, SUV39H1, which specifically targets H3K9me3, also functions in MSC senescence . One stuWith regard to histone acetylation, Li and colleagues found that the expression of RUNX2 and ALP increases in MSCs during aging, whereas that of the stemness markers OCT4 and SOX2 decreases. These alterations in gene expression result from dysregulation of H3K9ac and H3K14ac marks in the promoter regions of these genes, while methylation of CpG islands appears to remain unchanged . As obsep16INK4A promoter and initiating expression of this gene [HDACs seem to exert various influences on MSC senescence. One study found that MSC senescence decreases the expression of HDAC1 and HDAC2. HDAC1 and HDAC2 upregulate the expression of HMT PcGs such as BMI1, EZH2 and SUZ12 through RB phosphorylation while downregulating the expression of KDM6B through direct promotion of H3 acetylation on the KDM6B promoter . As a rehis gene . In conthis gene . The HDAhis gene . Howeverhis gene , 157. ThVegf and increases H3K9ac levels, which facilitates VEGF expression and therefore enhances angiogenesis. Shen and colleagues found that the lncRNA H19 affects angiogenesis of human amniotic MSCs (HAMSCs) in an EZH2-dependent manner [The therapeutic potential of MSCs is associated with their paracrine effects , and regt manner . Knockdo+/CD4+ T cell populations and downregulates IL-17 and IL-2 expression. Sphingosine-1 phosphate (S1P) is used as a priming factor in MSC therapy to enhance MSC function; however, S1P exhibits low efficacy and can induce adverse inflammatory reactions in vivo [Efforts have been made to promote the therapeutic effects of MSCs through genetic modification and pretreatment (priming) before MSC administration –164. For in vivo . A recen in vivo .Furthermore, HDAC1 silencing in human umbilical cord-derived MSCs (hUC-MSCs) enhances the neuroprotective effects of these cells against traumatic brain injury (TBI) in mice . KnockdoThrough this discussion of various fruitful studies, we have provided a brief overview of the roles of histone modifications in MSC biology. Modulation of histone-modifying enzymes is likely a promising strategy for regulation of MSC differentiation and senescence.However, the targets of histone-modifying enzymes seem to be relatively nonspecific; thus, manipulating these enzymes could influence more than one cell function. For instance, KDM4B and KDM6B regulate RUNX2 and SOX9 expression, which may facilitate both osteogenic and chondrogenic differentiation. Inhibition of G9a promotes adipogenic, endothelial, neuronal and cardiomyogenic differentiation. Similarly, EZH2 facilitates both adipogenic and neuronal differentiation and is also associated with cell senescence.Therefore, precise, gene-specific control of certain histone-modifying enzymes remains a considerable challenge. However, there are a few possible directions for future research. First, a deeper and more systematic understanding of histone modification would help elucidate the gene-specific control of histone modification enzymes. In addition to more studies on individual histone modification marks or enzymes, comprehensive studies on the interactions of sequence-specific transcription factors with known histone modification systems are of great necessity and importance. Second, since some drugs or small molecules targeting histone-modifying enzymes have already been discovered and are even undergoing clinical trials –172, cocIn summary, histone modifications undoubtedly play important roles in the regulation of biological processes in MSCs. Precise control of these modifications in MSCs will not only help us understand their functions but also enable us to direct cell fate for optimal tissue regeneration and damage repair.


In nematode Caenorhabditis elegans, however, pervasive chromatin contact domains are limited to the dosage-compensated sex chromosome, leaving the principle of C. elegans chromatin organization unclear. Transcription factor III C (TFIIIC) is a basal transcription factor complex for RNA polymerase III, and is implicated in chromatin organization. TFIIIC binding without RNA polymerase III co-occupancy, referred to as extra-TFIIIC binding, has been implicated in insulating active and inactive chromatin domains in yeasts, flies, and mammalian cells. Whether extra-TFIIIC sites are present and contribute to chromatin organization in C. elegans remains unknown.Chromatin organization is central to precise control of gene expression. In various eukaryotic species, domains of pervasive C. elegans embryos. Extra-TFIIIC sites constituted half of all identified TFIIIC binding sites in the genome. Extra-TFIIIC sites formed dense clusters in cis. The clusters of extra-TFIIIC sites were highly over-represented within the distal arm domains of the autosomes that presented a high level of heterochromatin-associated histone H3K9 trimethylation (H3K9me3). Furthermore, extra-TFIIIC clusters were embedded in the lamina-associated domains. Despite the heterochromatin environment of extra-TFIIIC sites, the individual clusters of extra-TFIIIC sites were devoid of and resided near the individual H3K9me3-marked regions.We identified 504 TFIIIC-bound sites absent of RNA polymerase III and TATA-binding protein co-occupancy characteristic of extra-TFIIIC sites in C. elegans autosomes, near the outer boundaries of H3K9me3-marked regions. Given the reported activity of extra-TFIIIC sites in heterochromatin insulation in yeasts, our observation raised the possibility that TFIIIC may also demarcate heterochromatin in C. elegans.Clusters of extra-TFIIIC sites were pervasive in the arm domains of  Eukaryotic genomes are organized into domains of various chromatin features including actively transcribed regions, transcription factor-bound regions, and transcriptionally repressed regions –4. DemarCaenorhabditis elegans has served as a model to study chromatin organization [C. elegans is the chromatin feature that distinguishes between the X chromosome and the autosomes. The X chromosome in C. elegans hermaphrodites is organized into large self-interacting domains that have some features shared with topologically associated domains (TADs) seen in other metazoan genomes [C. elegans evolution [C. elegans autosomes are demarcated remains an area of active investigation [The genome of nematode nization , 16–18.  genomes –22. The  genomes . The cen genomes , 25, a h genomes , and low genomes . The aut genomes  and hete genomes , and are genomes , 29. Wit genomes , 4. Whil genomes , define  genomes , 31. Furvolution . How chrtigation , 33, 34.Saccharomyces cerevisiae and Schizosaccharomyces pombe, extra-TFIIIC sites exhibit chromatin boundary functions both as heterochromatin barriers and insulators to gene activation [C. elegans genome is unknown.The transcription factor IIIC complex (TFIIIC) is a general transcription factor required for recruitment of the RNA polymerase III (Pol III) machinery to diverse classes of small non-coding RNA genes . TFIIIC tivation , 44, 45.tivation , 46. In tivation –43, 47. C. elegans genome. Extra-TFIIIC sites were highly over-represented within a subset of autosome arms that presented a high level of heterochromatin-associated histone H3K9 trimethylation (H3K9me3). Extra-TFIIIC sites formed dense clusters in cis and were embedded in the lamina-associated domains. Despite the heterochromatin environment of extra-TFIIIC sites, the individual clusters of extra-TFIIIC sites were devoid of and resided near the boundaries of H3K9me3-marked regions. Our study thus raised the possibility that, like extra-TFIIIC sites in other organisms, C. elegans extra-TFIIIC sites may have a role in demarcating chromatin domains.In this study, we unveiled extra-TFIIIC sites in the C. elegans genome includes extra-TFIIIC sites, we analyzed the ChIP-seq data published in our previous study [C. elegans. We identified 1029 high-confidence TFIIIC-bound sites exhibiting strong and consistent enrichment for both TFTC-3 and TFTC-5  machinery at small non-coding RNA genes such as tRNA genes Fig. a. Extra-us study  for TFIIC. elegans extra-TFIIIC sites could be unrelated to Pol III transcription and similar to extra-TFIIIC sites reported in other organisms. To distinguish these two possibilities, we examined the presence of transcription start sites (TSSs) of non-coding RNA genes near TFIIIC-bound sites. We observed that only 4% of extra-TFIIIC sites (20/504) harbored TSSs of non-coding RNA genes within 100 bp of the TFIIIC-bound site center  , and almost all of the overlapped elements  were the CeRep3 class of repetitive elements . Therefore, unlike extra-TFIIIC sites in yeast and humans, C. elegans extra-TFIIIC sites harbored both the Box-A and Box-B motifs; furthermore, a large fraction of these sites corresponded to a class of putative tRNA pseudogenes CeRep3.Because the Box-A and Box-B motifs constitute the gene-internal promoter for tRNA genes in eukaryotic genomes  Fig. 1aa1a, we hudogenes . To deteS. cerevisiae reported that extra-TFIIIC sites are overrepresented near protein-coding gene promoters, proposing a role in regulating RNA polymerase II (Pol II)-dependent transcription [C. elegans extra-TFIIIC sites were located near protein-coding genes, we measured the distance from extra-TFIIIC sites to TSSs of nearest protein-coding genes. C. elegans extra-TFIIIC sites were not located near protein-coding gene TSSs compared with Pol III-bound TFIIIC sites  or with randomly permutated extra-TFIIIC sites , but strongly under-represented in the X chromosome  consistent with tRNA gene overrepresentation in the X chromosome [The lack of robust association with local regulatory features of Pol II and Pol III transcription led us to hypothesize that extra-TFIIIC sites were related to large-scale organization of chromosomes as in the case of yeasts , 53. To romosome .Fig. 3ExC. elegans autosomes can be subdivided into three domains of similar size  based on repetitive element abundance, recombination rates, and chromatin organization [P < 0.001; Fig. U test vs. within-arm permutations P = 2 × 10−16; Fig. C. elegans extra-TFIIIC sites were fundamentally different from Pol III-bound TFIIIC sites in their genomic distribution and highly concentrated at specific locations within autosomal arm domains.nization , 23, 25.nization   or extra-TFIIIC sites permutated within autosomal arms   . Together, our results suggest that C. elegans extra-TFIIIC sites are localized at the nuclear periphery and intersperse H3K9me3-marked heterochromatin regions , the basal transcription factor for RNA polymerase III (Pol III), that do not participate in Pol III-dependent transcription in in yeast , 40, flyin yeast , mouse [in yeast , and humin yeast . Our datC. elegans extra-TFIIIC sites reported in this paper resemble characteristics of extra-TFIIIC sites participating in chromatin insulation. First, C. elegans extra-TFIIIC were densely clustered in cis, similar to clusters of TFIIIC-bound sites capable of insulating heterochromatin and enhancer activities in S. pombe and human cells [C. elegans extra-TFIIIC sites were located close to, but not within, H3K9me3-marked regions, similar to the observation that some extra-TFIIIC sites are located at the boundaries of heterochromatin [C. elegans extra-TFIIIC sites coincided with genomic regions known to be associated with nuclear membrane protein LEM-2 [C. elegans extra-TFIIIC sites may act as a chromatin insulator at the nuclear periphery.Previous studies have suggested that extra-TFIIIC sites act as genomic insulators by blocking enhancer activity or heterochromatin spreading , 56, 58,an cells , 58. Sechromatin , 56, 58.in LEM-2 , similarin LEM-2 , 46. TheC. elegans extra-TFIIIC sites and those in other organisms. First, C. elegans extra-TFIIIC sites possess both the Box-A and Box-B motifs, unlike yeast and human extra-TFIIIC sites that only possess the Box-B motif [C. elegans extra-TFIIIC sites were neither located near gene promoters nor associated with chromatin features of Pol II-dependent regulatory regions, unlike human, fly, and mouse extra-TFIIIC sites that are located near regulatory elements for RNA polymerase II (Pol II) transcription [C. elegans extra-TFIIIC sites are unrelated to CTCF binding, unlike human and mouse extra-TFIIIC sites that are located near CTCF binding sites [C. elegans genome does not encode CTCF [There are also differences between -B motif , 43. Seccription –43. Thirng sites , 43, becode CTCF . Our stuC. elegans autosomes remain poorly understood. Unlike the X chromosome, which is organized into large self-interacting domains that have some features shared with topological associated domains (TADs) reported in other organisms, the autosomes do not present strong and pervasive self-interacting domains [cis near the boundaries of H3K9me3-marked regions warrant future investigation of whether TFIIIC proteins participate in chromatin organization in C. elegans autosomes.The molecular mechanisms underlying the chromatin organization of  domains . The con domains . Several domains , 34; sma domains ; and act domains . Our obsD. melanogaster, CTCF is essential but does not appear to define TAD boundaries, and instead acts as a barrier insulator [C. elegans), plants, and fungi, CTCF orthologs are absent [C. elegans (this study), and yeast [How strategies to demarcate chromatin domains have evolved in eukaryotes remain unclear. In vertebrates, CTCF has a central role in defining TAD boundaries and is essential for development , 59, 60.nsulator –63. In te absent , 64. In e absent  and extre absent , mouse [e absent , fly [41nd yeast , 40. WheC. elegans genome. These “extra-TFIIIC” sites were highly over-represented in the arm domains of the autosomes interacting with the nuclear lamina. Extra-TFIIIC sites formed dense clusters in cis near the outer boundaries of individual H3K9me3-marked heterochromatin regions. These genomic features of C. elegans extra-TFIIIC sites resemble extra-TFIIIC sites reported in other organisms that have activities in insulating heterochromatin. Our study warrants future investigation of whether TFIIIC proteins participate in heterochromatin insulation in C. elegans.We identified TFIIIC-bound sites that do not participate in RNA polymerase III-dependent transcription in the http://www.ncbi.nlm.nih.gov/geo/) with accession numbers GSE28772 (TFTC-3 ChIP and input), GSE28773 (TFTC-5 ChIP and input), GSE28774 (RPC-1 ChIP and input), and GSE42714 (TBP-1 ChIP and input). ChIP-seq datasets for H3K4me3, H3K4me1, H3K27ac, H3K9me2, and H3K9me3, performed in chromatin extracts of early-stage N2-strain embryos [https://www.encodeproject.org/comparative/chromatin/).ChIP-seq of TFTC-3, TFTC-5, RPC-1, and TBP-1 was performed in chromatin extracts of the mixed-stage N2-strain embryos in duplicates and have been reported in our previous publication . These dThe ce10 reference sequence was used throughout. The chromosomal domains  defined by recombination rates  were useC. elegans transcripts were downloaded from the WS264 annotation of WormMine. The WS264 genomic coordinates were transformed to the ce10 genomic coordinates using the liftOver function (version 343) with the default mapping parameter using the ce11ToCe10.over.chain chain file downloaded from the UCSC genome browser.The genomic coordinates and the types of MACS2  (versiongeom_raster function (version 2.2.1) in R.For the heatmaps around TFIIIC sites, a set of 20-bp windows with a 10-bp offset that covered a 2-kb region centered around the center of TFIIIC sites was generated for each site. For each window, the mean of fold-enrichment score was computed from replicate-combined input-normalized fold enrichment bedgraph files. The signals were visualized using the ggplot2’s intersect function [The genomic location and classification of non-coding RNA genes was described in “function    with theintersect function [shuffle function (version 2.26.0). The TFIIIC sites were shuffled across the genome, or within the chromosomes, or within chromosomal domains in which they reside, as described in each analysis section. After each permutation, the permutated set of TFIIIC sites were assessed for the overlap with the features of interest. This permutation was repeated 2000 times to assess the frequency at which the number of intersections for the permutated set of the TFIIIC sites was greater or less than the number of intersections for the observed TFIIIC sites. If none of the 2000 permutations resulted in the number of overlaps greater or less than the observed number of overlaps, the observed degree of overlaps was considered overrepresented or underrepresented, respectively, with the empirical P value cutoff of 0.001. The mean number of overlaps after 2000 permutations was computed for visualization.Unless otherwise noted, the overlap between the 1-bp center of each of the TFIIIC sites and genomic features of interest (with size ≥ 1 bp) was assessed using the Bedtools function   such that the TFIIIC sites were shuffled within the chromosomes, and the distance between the permutated TFIIIC sites and closest protein-coding gene TSS was obtained. Mann–Whitney U test, provided by the wilcox.test function in R, was used to assess the difference of the distribution of the TFIIIC–TSS distances between groups.The genomic location of protein-coding genes was described in “function   were processed. The genomic coordinates were transformed to the ce10 genomic coordinates as described above. The intersection between these features and TFIIIC sites was assessed as described in “The chromatin state annotations and annotations of “active”, “regulated”, and “border” domains are reported previously . The intThe number of TFIIIC sites in each chromosome was assessed as described in “U test.For each chromosomal domain, the genomic distance between every pair of two neighboring extra-TFIIIC sites (center-to-center distance) was computed in R. To estimate the degree of closeness between extra-TFIIIC sites only explained by the frequency of extra-TFIIIC sites within chromosomal domains, the extra-TFIIIC sites were permutated 2000 times within chromosomal domains as described in “ChIP-seq dataset) was computed for each window using the Bedtools map function (version 2.26.0). Windows with the mean fold-enrichment score greater than 2.5  were considered enriched for H3K9me2 or H3K9me3 and merged if located without a gap. This yielded 2967 H3K9me2-enriched regions  and 1331 H3K9me3-enriched regions .To define H3K9me2-enriched and H3K9me3-enriched regions, the genome was segmented into 1-kb windows, and the mean fold-enrichment score of H3K9me2 and H3K9me3 (see The intersection between H3K9me2-enriched or H3K9me3-enriched regions and TFIIIC sites was assessed as described in “closest function [shuffle function (version 2.26.0). For the analysis of the distance to H3K9me2-enriched regions, this permutation was performed within the chromosomal domains. For the analysis of the distance to H3K9me3-enriched regions, permutation was performed with the chromosomal domains, but excluding the H3K9me3-enriched regions themselves because the TFIIIC sites were strongly underrepresented in the H3K9me3-enriched regions.For each TFIIIC site, the absolute distance between the center of the TFIIIC site and the closest H3K9me2-enriched and H3K9me3-enriched regions was obtained using the Bedtools function  (versionliftOver function (version 343). The intersection between NPP-13-binding sites (± 500 bp of NPP-13 binding site center) and TFIIIC sites was assessed as described in “The 223 NPP-13-binding sites identified in mixed-stage N2-stage embryos are previously reported . The genliftOver function (version 343). The intersection between LEM-2 subdomains or gaps of variable size classes and TFIIIC sites was assessed as described in “The LEM-2 subdomains and gaps between LEM-2 subdomains identified in mixed-stage N2-stage embryos are previously reported . The genAdditional file 1. TFIIIC-binding sites.


This review hopes to provide not only an improved and updated understanding ofthe epigenetics of breast cancer, but to also elaborate on tumour model development/refinement, biomarker evaluation, drugresistance and test of individual drugs or drug combinations and drug delivery systems.Breast cancer (BC) is a widely prevalent form of neoplasia in women with fairly alarming mortality statistics. This aspect maybe attributed, in part, to the current spatial and temporal heterogeneity-based limitations in therapies with possible recurrenceof this tumour at primary and/or secondary sites. Such an extensive phenotypic heterogeneity in breast cancer is unlikely to beadequately or completely comprehended by an immuno-histopathology-based classification alone. This finding has warrantedresearch and development in the area of microarray-based methods (i.e. transcriptomic and proteomic chips) for an improvedmolecular classification of this complex and heterogeneous tumour. Further, since epigenetics can also be an importantdeterminant in terms of diagnosis, prognosis and therapy, this review provides an insight into the molecular portrait of BC ingenetic and epigenetic terms. Specifically, the roles of characteristic DNA and histone-based modifications as well as mi-RNA-based alterations have been discussed with specific examples. Also, their involvement in epithelial mesenchymal transition(EMT) processes in cancer stem cells (CSCs) has been outlined. Last but not least, the salient aspects and the advantagesof  The most common site for the development of neoplasiain women is the breast. The mortality rate for thoseafflicted with this disease has been reported to be 25% . This stThe TCGA repository of cancer-related molecularinformation was compiled following data generated atseveral omics levels including whole exome sequencing-based mutational spectra and DNA copy number changes, transcriptomic expression patterns (expression data) and reverse-phase protein array (RRPA)-related alterations . in vitro assays. Hence, systematic cataloguing and updating of results obtained from in vitro models wouldserve as an extra piece of important information, provided the results are concordant with observations in humans or widely accepted in vivo xenograft animal models as well as transgenic animal systems. Furthermore, it iswidely accepted that one of the major causes of treatmentresistance, aggressive behaviour, disease severity, andrate of progression and relapse is due to cancer stem cells(CSCs)  . Some or all of these cells may survive the currentlyemployed treatment methods including chemo-andradiotherapy. This thus shows the need to evaluate and possibly refine existing model systems that can mirror, at least in part, the spatial and temporal epigenetic heterogeneity in breast CSCs. However, heterogeneity in the vasculature as well as the role of stromal factors is also an important determinant in mimicking the tumour in the context of its microenvironment. Hence, this review is to also provide an update with regards to the existing 3Dmodel systems. This approach has been substantiated by several reports demonstrating that these systems are better alternatives to the 2D environment, wherein a monolayer of cells is cultured in artificial conditions. Based on the shape, structure and site of origin, breast tumours are broadly classified as invasive ductal carcinoma, not otherwise specified  and ductal carcinoma in situ-ductal carcinoma in situ (DCIS). These tumours may be known as ductal or lobular based on the site of their origin. The term DCIS is a generic term that refers to the non-invasive, abnormal cell growth that is localized to the ducts and lobules and may become malignant. The IDCs refer to cancers that have infiltrated into the extracellular matrix region through the wall of the duct . A more recent and elaborate classification of BC has, however, changed IDC, NOS (2003) to invasive carcinoma of no special type (NST). The other types of BCs are of mixed types including invasive lobular carcinoma, tubular carcinoma and invasive cribriform carcinoma, carcinomas with medullary features, metaplastic carcinoma, carcinomas with apocrine differentiation, adenoid cystic carcinoma, mucinous carcinomas and carcinomas with signet-ring cell differentiation, invasive mucinous carcinoma, carcinomas with neuroendocrine features, invasive papillary and micropapillary carcinoma, secretory carcinoma, oncocytic carcinoma, polymorphous carcinoma, sebaceous carcinoma of the breast, lipid-rich carcinoma, glycogen-rich clear cell carcinoma, acinic cell carcinoma, microinvasive carcinoma and inflammatory carcinoma . Despite the similarities in the 5- and 10-year survival rates, the invasive lobular carcinoma (ILC) category of cancers  is more likely to metastasize and bilateral variants are more frequent. Since the clinical course and the underlying biology are different, histology-based studies may not be sufficient for the accurate classification/sub-stratification of the five subtypes of ILC. Further, the non-IDC and non-ILC cancers (not listed above) include those that are comedo as well as the mucinous A (paucicellular) and B (hypercellular) subtypes. As is evident from the classification mentioned above, the challenges posed during BC therapy can be attributed largely to the complex and heterogeneous nature of the tumour .In this context, the availability of RNA sequencing methods has provided the opportunity for a better classification based on the tumour transcriptome and for also identifying molecular mechanisms that may contribute to the observed variability in BC (e.g. exon skipping and promoter switching) . To circumvent this problem, molecular classificationnow differentiates ductal and lobular carcinomas intoER+/luminal , basal-like, Erb-B2+and normal breast. These results were obtained followingwhole-transcriptomic microarray analysis of 40 breasttumours. These results were correlated with thoseobtained from 11 cultured cell lines. The genes selected were those showing a similar expression pattern in thesame individual, while differences were observed amongpatients. Reproducibility of the results (independent and repeated sampling) as well as the strong correlation of the quantitative expression data between a primary and a metastatic tumour further added to the strength of the evidence. Hence, experimental designs of this nature  are warranted to refine the molecular signature and make it more representative of breast tumour variability . BRCA1. In terms of clinical outcome, the basal and ERBB2+ subtypes are the most severe in terms of the period of time between primary tumour formation and metastasis, while the luminal B subtype is an intermediate between the two . Next-generation sequencing of another cluster of tumours have showed that KCNB2, UTRN (6q24) and MDN1 (6q15) were mutated often in this subtype   , and alsHOTAIR was upregulated, while the SOX family of tumour suppressor genes, particularly SOX10, SOX11 and SOX15 as well HOXA5 was silenced  transitions, chromosomal gain (1q and 8q) and loss (11q) in addition to increase in the expression level (mRNA and the protein) of PGR, ESR1, GATA3 and FN1)  . The basal subtype of BC lacks ER, PR and HER2, and comprises approximately 16% of all BCs. This subtype is thus known as triple negative BC (TNBC), a phenotype that is recalcitrant to conventional therapies with an approximate 20% response rate. TNBC has a very poor prognosis with the medial survival being only 1 year and the relapse rate is about 30%. Hence, there is an imperative need to further stratify the TNBC subtype. Such an approach may provide a better understanding of the mechanisms involved in TNBC development as well as possibly introducing a better model for the development and/or refinement of ethno-based drugs .Another triple negative subtype with a poor prognosis is known to be in the claudin-low category. This subtype of cells showed expression of EMT marker genes associated with immune response and stem cell-like features . FurtherIn a gene expression analysis, 21 BC data sets comprising 587 TNBC cases were analysed, leading to the identification of six subtypes in addition to the identification of suitable model cell lines (for drug testing). The two basal-like subtypes (BL1 and BL2) had ahigher induction of cell cycle and DNA damage response genes. The other subtype was immune-modulatory (IM), while the mesenchymal (M) and mesenchymal stem-like (MSL) subtypes had a molecular profile which resembled that of EMT transition. The luminal androgen receptor (LAR) subtype was linked to AR-mediated signallingand patients under this category included those that had alower relapse-free survival rate . The heterogeneity seen in the tumours in vivo is mirrored largely in the commercially available BC cell lines. In cell line studies (MCF-7 versus MCF-7 derived cell lines), noncoding RNAs and possible differential splicing were identified apart from the presence of a cluster of genes whose expression was correlated to steroid-based drug response/lack of response . It is kIn specific, it has been shown that EMT processes, regulated transcriptionally and epigenetically, occur preferentially in BC cells with the basal-like phenotype. For instance, increased expression of markers that can be used to flag an EMT process  were observed. Also, an increased expression of ECM remodelling and invasion-related proteins  was also reported. Last but not least, classical epithelial markers (E-cadherin and cytokeratins) were also shown to be down-regulated . This final aspect should be contrasted with an earlier report wherein high expression of membrane E-cadherin was linked to invasive carcinomas , while its lack of expression was linked to lobular carcinoma. This study thus suggested E-cadherin membrane expression as a marker to distinguish between these two major histological subtypes of cancer .DNA hypo/hyper-methylation, histone acetylases and deacetylases, methyltransferases and demethylases are epigenetic changes considered to be important in BC. Micro-RNA-based alterations are also involved in terms of regulating epigenetic processes in BC.Of note, PRC2 complexes are, in general, associated with gene repression, while PRC1 complexes are related to gene activation. Specifically, the PRC2 complex proteins like Suz12, EED and Ezh2 have been known to mediate gene silencing by the trimethylation of lysine 27 in the H3 histone proteins. The general concept is that euchromatisation ("open form") around the promoter region would favour accessibility of the transcription factors for the initiation of transcription. Heterochromatisation, however promotes a more repressed chromatin state and this alteration may thus be linked with the silencing of gene expression. Epigenetic regulation has been reportedin diverse BC-related events including plasticity and EMT induction . The folThe three proteins  are part of the PRC2 complex that is associated with gene silencing. Murine cell-based data as well as results from primary human tumours has provided evidence for the activation of Ezh2. This activation has been linked to certain upstream events involved in the pRb/E2F pathway. Deregulation of certain tumour suppressor genes  results in the activation of the cyclindependent kinases (CDK4 and CDK6). This activation, in turn, hyper-phosphorylates pRb, thereby causing the release of E2F transcription factors to increased Ezh2 expression. EZH2 is known to methylate H3K27Me3 and H3K9Me3 , possiblIt has been reported that desmocollin 3 (a cell-cell adhesion molecule in the family of cadherins) is down-regulated in certain BC specimens and is linked to aberrations in cytosine methylation in its promoter elements . MASPIN in vivo recurrence of tumours and also a predictor of a decrease in relapse-free survival. The methylation of lysine 9 (H3K9Me2) in the region surrounding the E-cadherin promoter may contribute to the decreased expression of E-cadherin , a methyl transferase forming H3K9Me3 in the vicinity of the E-cadherin promoter, thus down-regulating its expression .Furthermore, it has been shown that there is a correlative increase in the DNA methylation status (discussed indetail below) flanking the same gene, thereby providing evidence of a link between this type of epigenetic phenomena with that of key changes in histone proteins. This mechanism of Snail-mediated E-cadherin silencing is reiterated again in a more recent paper, in which certain histone methylation enzymes  are recruited to contribute to the hetero-chromatisation in the vicinity of the E-cadherin promoter (H3K9Me3). The gene silencing then occurs due to the concomitant DNA hyper-methylation of the CpG islands. The DNA and histone-based epigenetic changes act in a coordinated manner to mediate EMT processes.The following sequence of events occurs during the Snail-mediated choreography of multiple epigenetic events, culminating in the down-regulation of E-cadherin expression and in turn EMT processes. LSD1 (demethylase)/HDAC (deacetylase) is recruited to the E-cadherin promoter by Snail via its SNAG domain. This demethylase is involved in removing methyl groups from H3K4Me2/3, while the deacetylase removes acetyl groups from H3/H4. This demethylation event is thought to promote Snail-mediated recruitment of G9a and Suv39H1 on the E-cadherin promoter. HDAC may also be involved in aiding the interaction of Snail with PRC2, thereby contributing to the binding of the latter to the promoter elements. The sequential methylation of H3K9Me to H3K9Me2 and H3K9Me3 is mediated by G9a  and Suv39H1 (via the SNAG domain of Snail) respectively. These two methyl transferases are also involved in the final step of E-cadherin down-regulation in recruiting DNA methyltransferases (DNMT) for hyper-methylationmediated silencing of E-cadherin, which is a significant event in EMT . There are other reports where G9a has been shown to act differentially in a cell type-specific manner. GATA3 forms a complex with G9a and NURD (MTA3) and silences ZEB2 (an important transcription factor involved in EMT induction). With BC progression, GATA3, G9a and MTA3 are down-regulated and ZEB2 is up-regulated. This upregulation, in turn contributes to the decrease in the expression levels of G9a and MTA3 via the G9a/ NURD (MTA1) complex . GATA3, a transcription factor involved in the mesenchymal epithelial transition (MET), plays a pivotal role in E-cadherin silencing via its transactivation domain. This event is mediated by the GATA-3-induced chromatin architecture changes  or other changes that do not result in an accessible chromatin. Such MET requires binding as well as recruitment of BRG1, an ATPase of the SWI/ SNF family of chromatin remodelers . The SET8  is a histone methyl transferase (HMT) with a SET domain. Its recruitment is mediated by TWIST (another transcription factor involved in the induction of EMT). This HMT, in turn, mono-methylates H4K20 and suppresses E-cadherin expression, while a similar methylation event in theN-cadherin promoter activates it . This apparently paradoxical finding can be explained based on the type of dimerisation of TWIST. In specific, homo-dimerization of TWIST leads to the activation of N-cadherin, however, hetero-dimerization of this transcription factor with Mi2/NuRD, MTA2, RbAp46, Mi2 and HDAC2 proteins leads to suppression by the formed complexes. This TWIST-mediated recruitment of the aforesaid complex proteins, to the promoter of E-cadherin, represses this gene, which is apart from direct binding of the transcription factor to the E-cadherin promoter , 30. A hydrolase inhibitor, 3-Deazaneplanocin A (DZNep), can cause the levels of ado-homocysteine to be elevated. This elevation, in turn, results in the decrease in the levels of EZH2, SUZ12 and EED. Hence, there is an inhibition of H3K27 and not H3K9 methylation marks, which leads to a reversible reactivation of certain genes. Significantly, activation of an effector of apoptosis (FBXO32) may account for DZNep-induced apoptosis in BC cells. This molecular baiss provides us an elegant approach for modulating epigenetic proteins that may possibly aid in selective activation of apoptosis in BC cells .An increase in EZH2 is associated with increased invasiveness, increased proliferation rate and increased aggressiveness behaviour. It is also considered to be a marker for a pre-cancerous lesion in a tissue that is histologically normal . In both cases, EZH2-mediated trimethylation of H3K27Me3 leads to local heterochromatisation as well as DNMT1-mediated gene silencing. However, the final outcome may to some extent be dependent on the types of genes that are silenced (e.g. those that contribute to the neoplastic phenotype or those with pro-apoptotic function). Although Snail is involved in recruiting G9a to the H3K9 site, it has been reported that the activation of Snail is mediated by the removal of the repressive H3K27Me3 marks. These methylation marks are removed by the de-methylating action of KDM6B  . The section below outlines the links between hypermethylation of the CpG islands in the promoter region and silencing of the gene while bearing in mind that multiple studies have reported DNMT1 and SNAIL1 to be involved in the repression of E-cadherin expression.hi/CD24lo/EpCAM+breast CSCs). However, DUSP6 overexpression has been observed in HER2+ BCs. In this context, it is pertinent to point out that there are inhibitory and activating phosphorylation marks (1834 active and 89 inhibitory marks) that regulate the activity of the p300 HAT enzyme which can activate certain genes involved in the formation of euchromatin (The p300-mediated acetylation (H3K27Ac mark), in addition to the repressive H3K27Me3 mark, is maintained by DUSP4, a phosphatase targeting threonine/serine and tyrosine residues. Knockdown of this phosphatase, as well as DUSP6, enhances stem cell formation, while down-regulation of DUSP1 decreases stem cell formation  to normal levels, thereby providing evidence for this epigenetic modification being responsible for promoter inhibition. Furthermore, the expression of a reporter gene under the control of the E-cadherin promoter provided fairly definitive evidence of the presence of the transcriptional machinery in the E-cadherin-negative BC cells. In a later study, it was again demonstrated that E-cadherin methylation correlated with fibroblast-like morphology in BC cell lines. This phenotype also correlated with the expression of genes associated with EMT transition including TGF-ß-related genes and the genes involved in CDH1 regulation (d TWIST) . Specifically, epigenetic regulation in the form of DNA hyper-methylation and the consequent inactivation of the Wnt pathway  has been known to be involved in BC development. In this regard, Dickkopf2  can arrest cells in G0 and G1, and induce apoptosis. This study was undertaken on 10 BC cell lines, 98 primary tumours and 21 normal breast tissues .Another study has reported that Dickkopf3 inhibited thecanonical Wnt/β catenin pathway, thereby leading up toβ-catenin migrating from the nucleus to the cytoplasmand the membrane. This mechanism along with thepresence of reduced levels of active β-catenin can furtheractivate the non-canonical JNK signalling. DKK3 wasshown to inhibit BC cell migration due to a reversal of EMTand a decrease in stem cell markers . RecruitThe ZEB1 transcription factor has been shown to beregulated by the asymmetric dimethylation of arginine3 of histone H4 by PRMT1 (an arginine methyltransferase) at its promoter. This modification has been linked to EMT induction as well as senescence . While tin vitro cellular model provided evidence for the simultaneous occurrences of these intermediate phenotypes. Specifically, the transcription factors ZEB1 and ZEB2 were up-regulated under these circumstances and may contribute to an increase in invasiveness and tumourigenicity -based data-mining, real-time PCR and correlation analysis with clinico-pathological features was followed. Seventy six differentially expressed miRNAs were identified by microarray analysis based on total RNA of blood samples from women with luminalA BC. The ANN-based strategy enabled the selection of 10 miRNAs  for follow-up. Of these, four of them may have biomarker potential, since they were down-regulated in affected women. In addition, the combined signature ofthree of these  may discern tumours from controls . While the increased expression of ZEB1/2 transcription factors, mediated by the down-regulation of miR200, has been reiterated in basal-like BC, distal BC metastasis has been associated with an increase of this miRNA family. This implies a possible role for them in the establishment of these cancer cells at a site distal from its origin, which may possibly be due to a feed-forward loop-mediated repression of ZEB 1/2 by miR200 . PTPN6 and miR200c/141 are tightly linked together under a wide variety of physiological conditions. The regulation of miR200c/141 involves by-passing the expression of PTPN6 (SHP1) either by the use of an alternative polyadenylation signal or by a later termination of the transcription of PTPN6 gene. The alternative mechanism may be based on DNA looping where the transcriptional machinery of both genes physically interact, providing an opportunity for a common epigenetic regulation  . For insSide-population BC stem cells expressing membrane-bound drug efflux transporters and other markers have been shown to contribute to the observed recalcitrance of the tumour to the drug as well as tumour recurrence. Also, these cells divided rapidly and exhibited a relatively high frequency of survival. BCSCs have been associated with the different stages of the multi-step process of BC including invasion and metastasis . A unifying model based on the presence of BC stem cells as well as the clonal evolution model has been proposed . This fi+/high, CD24+/low cancer cells belong to the low grade, luminal subtype. The high grade  subtype CSCs of the medullary, metaplastic cancer category exhibit the CD44+/CD24-/low/ALDH1+ CSC phenotype. This classification is important for diagnosis, prognosis and therapy (including the development of novel drug molecules)  . Such maThere is a strong association between DNA hypermethylation and histone methylation-mediated loss oftumour suppressor gene expression. There is also an association between DNA hyper-methylation and histone deacetylation. KDM5B, a histone demethylase, acts on H3K4Me3 and its over-expression can repress cell proliferation, adhesion and migration. This demethylase acts in concert with NuRD and HDAC1 in contributingtowards repression of genes associated with cellproliferation . DNMT1 expression has been associated with hypermethylation and suppression of ISL1 expression in mammary tumours as well as in BCSCs. Hence, down-regulation of DNMT1 and ISL1 may lead to a decrease in the population of stem cells. This axis may be useful for drug development . EMT traJARID1B (a H3K4 demethylase) expression was shown to be amplified in luminal breast tumours and is associated with an expression profile that is characteristic of this subset of cancers. High activity of this enzyme is also linked to poor outcome in patients .It is known that EMT transition has been consistently associated with CSCs in various cancers including BC. In all these cancers, epigenetic events may modulate the CSC phenotype and a number of examples with respect to this aspect are provided below. Apart from part/E2F and Ezh2, other signalling pathways such as Wnt/ß-catenin and RANK/RANKL have been associated with EMT induction in CSCs. Specifically, increase in RANK/RANKL signaling has been shown to increase the population of CD44+/ CD24- stem cells, and induce EMT and stemness in human mammary epithelial cells, thus being involved inBC tumour initiation, progression and metastasis . Studies have shown that Nodal signalling is associated with the aggressive features in BC. The endogenous negative regulator of Nodal  is not expressed in cancer cells , therebyThe position-dependent effect of GATA-3 has been demonstrated by the observation that GATA-3 can alter the open versus closed state of chromatin at certain loci. At other positions, the sliding of the nucleosomes may not be associated with the formation of accessible chromatin. In addition, removal of the transactivating domain of GATA-3 can affect the reprogramming of chromatin without altering its binding ability . This main vitro has led to the development and/or refinement of 3D model systems. Such 3D model systems can help in validating the results obtained in terms of testing the apoptotic/anti-oxidant potential of ethno-derived biomolecules in 2D systems  as well as other spatial and temporal variation in the breast tumour. Accordingly, knowledge gleaned from research in the area of patient-derived xenografts would be extremely useful in terms of better understanding the mechanisms involved in BC patho-physiology as well as possibly providing a molecular basis for the often observed increase in drug resistance. Mounting evidence has shown that xenografts have a strong potential since they mimic the The use of cutting-edge molecular tools has provided abetter molecular portrait (based on genetic and epigeneticfeatures) of BC that correlate with several variables including biological characteristics, diversity, clinical course and patient outcome. Comparative analyses of the epigenetic molecules, including those related to CSCs and EMT processes, in different tissues may facilitate the development and/or refinement of the existing signatures. This approach may not only aid the development and/or validation of the existing 3D model systems that better resemble the tumour phenotype, but it may also validate cell line-based and patient-derived xenografts. This would eventually lead to an improved understanding of the underlying mechanism and a better predictive power in terms of biomarker development, clinical course, responseto drugs and drug combinations  in addition to elucidating an epigenetic basis forthe acquisition and maintenance of drug resistance.


The pioneer activity of transcription factors allows for opening of inaccessible regulatory elements and has been extensively studied in the context of cellular differentiation and reprogramming. In contrast, the function of pioneer activity in self-renewing cell divisions and across the cell cycle is poorly understood. Here we assessed the interplay between OCT4 and SOX2 in controlling chromatin accessibility of mouse embryonic stem cells. We found that OCT4 and SOX2 operate in a largely independent manner even at co-occupied sites, and that their cooperative binding is mostly mediated indirectly through regulation of chromatin accessibility. Controlled protein degradation strategies revealed that the uninterrupted presence of OCT4 is required for post-mitotic re-establishment and interphase maintenance of chromatin accessibility, and that highly OCT4-bound enhancers are particularly vulnerable to transient loss of OCT4 expression. Our study sheds light on the constant pioneer activity required to maintain the dynamic pluripotency regulatory landscape in an accessible state. Transcription factors (TFs) regulate the expression of genes through interactions with specific DNA sequences located in gene promoters and distal regulatory elements. A minority of TFs display pioneer activity, that is they have the ability to bind and induce the opening of nucleosome-occupied chromatin regions, allowing for the subsequent binding of other TFs and co-factors required for transcriptional activation . PioneerPou5f1) and SOX2 pioneer TFs  and Sox2, respectively , see Materials and methods) to a previous dataset acquired with ZHBTc4 cells +/- dox for 24 hr but cultured in serum + LIF (SL) . The gooTo compare the loci impacted by OCT4 vs SOX2 depletion, we next focused on all regions that were bound by OCT4 and/or SOX2 as identified from available and newly generated ChIP-seq datasets see . All thrSurprisingly, all groups were enriched for the binding of both OCT4 and SOX2 . 89% of To understand which features distinguish OD, SD, and CD loci, we performed motif analysis on the underlying sequences. While both OD and CD loci were strongly enriched for the OCT4::SOX2 canonical motif and the OCT motif, SD loci were more enriched for the SOX motif . SD siteSeveral lines of evidence suggest that OCT4 and SOX2 exhibit cooperative DNA binding. In vitro electrophoretic mobility shift assays and fluorescence correlation spectroscopy experiments have shown that OCT4 and SOX2 display enhanced binding to the OCT4::SOX2 motif when binding together . While iUpon loss of its partner protein, OCT4 loses binding at 8’324 loci  and gains binding at 739 loci . Conversely, SOX2 loses binding at 6’892 loci  and gains binding at 4’136 loci . This indicates that the ability of OCT4 to occupy its specific binding sites is more impacted by the absence of SOX2 than vice-versa, and that SOX2 can get rerouted to new loci in the absence of OCT4. We further noticed that loci gaining accessibility upon loss of OCT4, which are enriched for differentiation terms , also gaTransient depletion of OCT4 or SOX2 at the M-G1 transition has been shown to hinder pluripotency maintenance , but theTo test whether depletion of OCT4 at the M-G1 transition affects chromatin accessibility, we treated cells with dox for 40 hr to ensure that all cells have gone through at least one cell division expressing only MD or MD*-tagged OCT4. Note that dox-treated cells had a longer G1 phase as compared to wt ES cells, as shown before to be a consequence of lower than wt OCT4 levels . HoweverTo characterize the different dynamic behaviors of chromatin accessibility changes across the cell cycle, we used k-means clustering on the change in accessibility between MD-OCT4 and MD*-OCT4 cells at all accessible loci displaying an OCT4 ChIP-seq peak . Two cluWe then further characterized these clusters by analyzing their enrichment in proximity to genes regulated by OCT4. Loci in clusters 1–3 were enriched near genes that decreased in nascent mRNA expression upon loss of OCT4, in line with these loci being involved in transcriptional regulation . We nextWe analyzed the fraction of regions in the clusters overlapping previously annotated ES cell super-enhancers (SEs) and ‘typical’ enhancers (TEs) . We founAs mentioned above, pluripotency was shown to be maintained at lower than wildtype OCT4 expression levels. To ask whether chromatin accessibility of the observed clusters was OCT4 level-dependent within a higher OCT4 concentration range, we interrogated chromatin accessibility in the context of physiological variations of OCT4 levels. To do so, we took advantage of ATAC-seq data we previously acquired from cells differing in their OCT4 levels by a factor of ~2, due to temporal fluctuations in their endogenous levels . We compTo understand the reason for the differential impact of transient OCT4 depletion on chromatin accessibility, we performed motif search analysis and compared OCT4 binding at the different clusters. We found a higher enrichment for the canonical OCT4::SOX2 motif  and a hiWe next asked whether OCT4 also plays a role in maintaining enhancer accessibility in other cell cycle phases. To do so, we generated a cell line allowing drug-inducible degradation of OCT4. Briefly, we used lentiviral vectors to constitutively express the Tir1 ubiquitin ligase  and OCTTo verify that OCT4 degradation kinetics are similar across the cell cycle, we applied IAA for 0.5 hr  and 2 hr (full degradation) before analyzing the mCherry signal by flow cytometry. At 2 hr of treatment, mCherry levels were similar to those of mCherry-negative cells . We obseNext, we quantified the recovery of chromatin accessibility across the cell cycle. We treated OCT4-AID cells with dox for 24 hr, then with IAA or not for 2.5 hr, washed out the drug and incubated cells for 4.5 hr, sorted cells in different cell cycle phases and performed ATAC-seq . While bWe next aimed to quantify the dynamics of chromatin accessibility changes in response to OCT4 loss. Since residence times of OCT4 on specific DNA sites are in the second-range , we reasMyc) showed a statistically significant (p<0.05) change (Cntln) displayed a significant increase in mRNA levels after OCT4 depletion  and reads from single nucleosomes (180–250 bp). Both categories of reads displayed reduced accessibility after 2 hr of IAA treatment, in line with these being bona fide changes in accessibility . To test) change . In contepletion . This inIn this study, we dissected the roles and interplay of OCT4 and SOX2 in regulating chromatin accessibility in ES cells. To our surprise, we found a large number of enhancers that were bound by both transcription factors but for which chromatin accessibility was regulated by only one of them. In the future, it will be interesting to explore whether differences in the topology of OCT4 and SOX2 binding sites on the nucleosome surface or genomic location-dependent DNA residence times could explain these findings. While we found a larger influence on chromatin accessibility upon depletion of OCT4 than SOX2, we cannot fully exclude that this is partly caused by differences in protein half-lives or cell lines. Regions bound but not regulated by SOX2, including OD loci, could in principle also be controlled by other SOX family members such as SOX3 or SOX15 . As OCT4Surprisingly, upon OCT4 loss chromatin accessibility increased at a large number of genomic sites enriched for proximity to differentiation genes, even when OCT4 was degraded for only a brief period of time at the M-G1 transition. The fact that SOX2 occupies these sites and is required to maintain their accessibility suggests that in the absence of OCT4, SOX2 is rerouted to these loci and promotes differentiation together with other partners such as TFAP2C. Therefore, the rapid action of OCT4 in early G1 phase might be required to ensure both the maintenance of chromatin accessibility at pluripotency enhancers and to silence differentiation enhancers. This is further substantiated by the fact that clusters 1 and 3 were particularly enriched for the binding of pluripotency regulatory factors and contained sites that did not fully recover upon OCT4 depletion at the M-G1 transition. Whether the previously shown association of OCT4 to mitotic chromosomes  facilitaWe found that OCT4 degradation led to a rapid decrease in chromatin accessibility at all clusters of OCT4-regulated enhancers across the cell cycle with very similar kinetics, which tightly mirrored changes in OCT4 concentration and thus suggests highly dynamic regulation of chromatin accessibility by OCT4. However, the recovery of chromatin accessibility upon increase of OCT4 concentration displayed locus-dependent behavior. In contrast to clusters 1 and 2, cluster 3 loci did not recover over the time course of several hours either after M-G1 or auxin-induced degradation. While the mechanisms underlying these findings are unclear, loss across the whole cell cycle (cluster 3) or incomplete recovery (cluster 1) of chromatin accessibility may explain why OCT4 loss at the M-G1 transition results in impaired pluripotency maintenance.Protein depletion by degron systems works by increasing protein degradation rates without affecting their synthesis rate. Therefore, they suffer from an inherent tradeoff in maximizing expression levels when the degron is inactive while minimizing residual expression level when the degron is active. Here we expressed OCT4 at relatively low levels to ensure sufficient depletion, allowing us to show that the pioneering function of OCT4 is required constantly and throughout the cell cycle to maintain enhancer accessibility. However, the low dynamic range of accessibility changes prohibits sensitive detection of specific loci that are quantitatively more or less sensitive to OCT4 loss at different cell cycle phases. Furthermore, whether recurrent, transient loss of OCT4 outside of the M-G1 transition would also lead to pluripotency loss would have to be addressed in future studies.Drosophila for proper gene expression  using the following culture medium: GMEM (Sigma #G5154-500ML) containing 10% ES-cell qualified fetal bovine serum (Gibco #16141–079), nonessential amino acids (Gibco #11140–050), 2 mM L-glutamine (Gibco #25030–024), sodium pyruvate (Sigma #S8636-100ML), 100 μM 2-mercaptoethanol (Sigma #63689–25 ML-F), penicillin and streptomycin (BioConcept #4–01 F00-H), in-house produced leukemia inhibitory factor (LIF), CHIR99021 (Merck #361559–5 MG) at 3 μM and PD184352 (Sigma #PZ0181-25MG) at 0.8 μM. Cells were passaged by trypsinization (Sigma #T4049-100ML) every two to three days. All cell lines used in this study were tested by Eurofins Genomics at the end of the study (August 2019) and found to be Mycoplasma-negative.Lentiviral vectors were produced by transfection of HEK 293 T cells with the envelope , packaging  , and lenCloning of overexpression constructs pLV-PGK-YPet-MD was derived from pLVTRE3G-SOX2-YPet-MD  by ampliTo generate MD-OCT4 cell lines, ZHBTc4 cells were transduced with SNAP-MD-OCT4 and SNAP-MD*-OCT4 lentiviral vector particles and sorted to display near-identical average SNAP levels , subsequ2 one day before the start of treatment. ZHBTc4 YPet-MD SNAP-MD-OCT4 and SNAP-MD*-OCT4 were treated with 1 mg/ml dox for 40 hr prior to cell sorting. ZHBTc4 YPet-MD TIR1-V5 mCherry-OCT4-AID cells were treated with 1 mg/ml dox for 24 hr before adding IAA. Dox was maintained throughout the experiment. Cells were treated with 500 nM IAA (or not for control) for 2 hr or treated with 500 nM IAA (or not for control) for 2.5 hr, washed five times with PBS with 2 min incubation, and placed back in medium containing 1 mg/ml dox for 4.5 hr. For the time course experiment, OCT4-AID cells were seeded in different wells of a 24-well plate and treated with dox for 24 hr before adding IAA. Dox was maintained throughout the experiment. IAA was added at different time points (with one well left untreated) prior to cell collection. All wells were collected at the same time and subjected to ATAC-seq as described below.Cells were seeded at a concentration of 9’000–18’000 cells per cmCells were trypsinized, resuspended in culture medium with 50 mM Hoechst33342 (Thermo Fisher Scientific #H3570), and incubated for 15 min at 37°C. Cells were then spun down, resuspended in cold PBS with 1% FBS, and sorted according to their YPet-MD and Hoechst profile . Cells wAll ATAC-seq experiments were performed in biological duplicates except for IAA-treated mCherry-OCT4-AID cells sorted in EG1, LG1, and S phase where three replicates were performed. 50’000 cells were collected either directly after trypsinization or after sorting as described above and subjected to ATAC-seq as described previously . All cenAll ChIP-seq experiments were performed in biological duplicates. Roughly 10 million cells per sample were collected after trypsinization and fixed with 2 mM disuccinimidyl glutarate (Thermo Fisher Scientific #20593) in PBS for 50 min at room temperature, spun down at 600 g for 5 min and washed once with PBS. Cells were then treated with 1% formaldehyde  for 10 min at room temperature and quenched with 200 mM Tris-HCl pH 8.0 for 10 min, washed with PBS and spun down. For ZHBTc4 YPet-MD SNAP-MD-OCT4 and SNAP-MD*-OCT4 cells, cells were subsequently resuspended in cold PBS with 1% FBS and at least 500’000 cells per cell cycle phase were sorted (see Cell cycle phase sorting section above). Fixed cell pellets were kept on ice and resuspended in LB1 , incubated 10 min at 4°C, spun down at 1700 g, and resuspended in LB1 a second time, spun down and resuspended in LB2 , incubated for 10 min at 4°C, spun down and washed without disturbing the pellet three times with SDS shearing buffer  and finally resuspended in SDS shearing buffer. All buffers contained Protease Inhibtor Cocktail (Sigma #P8340-1ML) at 1:100 dilution. Chromatin was sonicated for 20 min at 5% duty cycle, 140 W, 200 cycles on a Covaris E220 focused ultrasonicator. Sonicated chromatin was equilibrated to 1% Triton X-100 and 150 mM NaCl and incubated with each antibody overnight at 4°C. Antibodies used were anti-BRG1 (Abcam #ab110641) at 5 μg per 10 million cells, anti-OCT4  at 20 μl per 10 million cells, and anti-H3K27ac (Abcam #ab4729) at 2 μg/25 μg chromatin. Protein G Dynabeads (Thermo Fisher Scientific #10003D) were blocked with 5 mg/ml BSA in PBS, added to chromatin, and incubated at 4°C for 3 hr. Beads were washed twice with Low Salt wash buffer , once with High Salt wash buffer , once with LiCl wash buffer , and finally with 1X TE  before being resuspended in ChIP Elution buffer  with 400 ng/μl Proteinase K (Qiagen #19131) and reverse-crosslinked overnight at 65°C. DNA was purified using a MinElute PCR purification kit (Qiagen #28004) and libraries were prepared with the NEBNext Ultra II DNA Library Prep Kit (NEB #E7645S). Libraries were sequenced on an Illumina NextSeq 500 using 75-nucleotide read length paired-end sequencing.(-Ct) value of each primer pair was normalized to that of Rps9 in the same sample. Primers are listed in ZHBTc4 YPET-MD cells expressing SNAP-MD-OCT4 or SNAP-MD*-OCT4 or ZHBTc4 cells expressing mCherry-OCT4-AID from the EF1α promoter were plated at 400 cells per well in a 6-well plate with ES cell medium (see above) with 0 or 1 µg/ml dox and medium was refreshed every other day. At day 7, flat and dome-shaped colonies were scored according to morphology and counted (SNAP-MD-OCT4 and SNAP-MD*-OCT4) or total colonies were counted (mCherry-OCT4-AID) followed by alkaline phosphatase staining (Sigma #86R-1KT). For RT-qPCR experiments, cells were collected at day 7  or after2TS22C and ZHBTc4 cells were plated in a 96-well plate coated for 1 hr at 37°C with 1:25 diluted StemAdhere (Primorigen Biosciences #S2071-500UG), treated with 1 mg/ml dox for different durations and fixed with 2% formaldehyde for 30 min at room temperature, washed with PBS, permeabilized with PBS with 5% FBS and 0.5% Triton X-100 for 30 min at room temperature, and incubated with the primary antibody, anti-OCT4 C-10 (Santa Cruz #sc-5279) at 1:500 dilution and anti-SOX2 (ThermoFisher #48–1400) at 1:200 dilution, in PBS with 5% FBS and 0.1% Triton X-100 at 4°C overnight. After washing with PBS, cells were incubated with the secondary antibody, anti-Mouse IgG AF488 (Thermo Fisher Scientific #A28175) and anti-Rabbit IgG AF647 (Thermo Fisher Scientific #A27040) at 1:1000 dilution, in PBS with 5% FBS and 0.1% Triton X-100 for 60 min at room temperature, with 2 ng/ml DAPI (Thermo Fisher Scientific #62248) for 10 min at room temperature and subsequently washed and imaged on an IN Cell Analyzer 2200 . Images were background-subtracted using FiJi  with a rZHBTc4 YPet-MD TIR1-V5 mCherry-OCT4-AID cells were plated in a 96-well plate coated for 1 hr at 37°C with 1:25 diluted StemAdhere (Primorigen Biosciences #S2071-500UG) in Phenol Red-free medium and imaged on an IN Cell Analyzer 2200  using the TexasRed and Brightfield channels. Cells were treated with IAA or washed just prior to imaging. Images were background-subtracted using FiJi  with a rMus musculus genome (GRCm38 release 87) with STAR 2.6.1c  was used. Background was calculated as the mean of HOMER-estimated background frequency in all groups/clusters. The HOMER2 function scanMotifGenomeWide.pl was used to determine the number of OCT4::SOX2 motifs per region . For GO http://cistrome.org/db) and for all peak files where the cell type was ‘Embryonic Stem Cell’ overlap with our cluster regions was determined using the BEDTools function intersect. Regions were randomly sampled from clusters 2–4 to contain the same number of regions as cluster 1 (n = 1’897). These were split into training  and test  regions. The function randomForest in R was used with the settings ‘formula = Cluster ~ ., mtry = 4, ntree = 2001’ on the training regions. The predict function in R was used with setting ‘type = "response"’ to use the model for predicting the clusters of the regions in the test data.The model was generated as described previously . Brieflyhttps://github.com/guifengwei/ChromHMM_mESC_mm10 +c where a, b, and c are constants. Half-life values were derived as log(2)/b.Exponential decays were fitted using the R function nls with the formula y ~ a*eDistributions were tested for non-normality using the Shapiro-Wilk test and if p<0.05 for any of the samples a non-parametric  test was used, otherwise a t-test was used. These were performed using two-tailed distributions and with unequal variance. In cases where comparison experiments were matched (e.g. treatment and control handled at the same time), paired testing was performed, except for non-parametric tests with n < 5 where the Wilcoxon signed rank test cannot give precise p-values. For average lineplots e.g. , distrib In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The authors explore to what extent the pioneering activity of SOX2 and OCT4 – a pair of collaborative pluripotency-linked transcription factors – overlaps and depends on each other for opening chromatin in ES cells and how this is regulated during the cell cycle. This is an important question for understanding the requirements and dynamics of pluripotency maintenance, cell differentiation and reprogramming. The study brings an unprecedented level of temporal resolution and functional hierarchy. It demonstrates the master role of OCT4 in rendering chromatin accessible to other transcription factors involved in pluripotent identity and reveals the striking dynamism and rapid reactivity of the chromatin of pluripotent cells compared to differentiated cells.Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Jessica Tyler as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Hamish King (Reviewer #2); Ken Zaret (Reviewer #3).Thank you for submitting your article "Dynamic regulation of chromatin accessibility by pluripotency transcription factors across the cell cycle" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:SOX2 and OCT4 – a pair of collaborative pluripotency-linked transcription factors – overlaps and depends on each other for opening chromatin in ES cells and how this is regulated during the cell cycle. This is an important question for understanding the requirements and dynamics of pluripotency maintenance, cell differentiation and reprogramming. Using inducible systems of expression and silencing, as well as cell-cycle stage-specific degradation, the authors draw the following conclusions: 1) OCT4 and SOX2 regulate partially independent loci for chromatin accessibility, 2) OCT4 has a larger effect than SOX2, 3) the cooperative binding of OCT4 and SOX2 is itself regulated by chromatin accessibility, 4) chromatin accessibility is very dynamic and requires OCT4 to be re-established after M phase and also throughout the cell cycle, 5) depletion of OCT4 can reroute SOX2 binding to new sites and 6) TF binding and chromatin accessibility are tightly coupled in pluripotent cells, in contrast to the temporal separation between these two events previously reported in somatic (pituitary) cells. This last point may relate to the hyperdynamic aspect of pluripotent cell chromatin, allowing sensitivity and/or rapid response to developmental signals. Some of the conclusions confirm previous works, but the temporal resolution brought by the study is clearly novel and uniquely interesting. The reviewers appreciated the quality of the experimental design and the impact of the conclusions. There were also some recurrent concerns – mostly implying nuancing the conclusions – and requests for additional experiments to support the conclusions, as listed below.The authors explore to what extent the pioneering activity of Essential revisions:1) Additional descriptive analyses of the four identified types of OCT4 target sites (clusters 1 to 4) in Figures 3-5 are needed, to allow speculation about the different properties that may define these distinct classes of binding sites. For example, do they display differences in the number of OCT4/SOX2 binding sites? Are they differentially bound  or do they exhibit motifs  by other relevant TFs, such as bookmarking factors (ESRRB or CTCF would be of primary interest)? Do regulatory sites within a cluster tend to be in proximity/regulate the same category of genes (ontology)? Position regarding TADs? A greater depth of discussion/conjecture on this point is really required – why might these sites behave so differently?2) There is little analysis relating chromatin accessibility with changes in expression at nearby genes . The functional impact of the observed (rather modest) chromatin changes should be tested at the level of gene expression, at least at a few target genes. This would be an interesting point to infer whether the different properties of the various clusters are functional or not and perhaps whether different clusters are more likely to be more or less important for maintaining pluripotency when exiting mitosis. The OCT4-AID-degron cell line would be the perfect system to examine this question and should avoid a lot of secondary effects that may occur even at 24 hours DOX treatment in the ZHBTc4 cell.3) ATAC-seq is a non-specific assay that is largely interpreted as chromatin accessibility, which likely reflects TF binding. Since the authors are specifically looking at peaks that change in ATAC-seq signal before and after OCT4/SOX2 degradation/silencing, changes in ATAC-seq peaks may reflect TF binding loss, rather than direct change in accessibility. To address this concern, the authors should computationally parse the ATAC-seq peaks into different size classes, such as short fragments that represent TF binding regions and 180-250 bp fragments that represent nucleosomes. The authors could then plot the nucleosome fragments in the different peak lists and show that nucleosome occupancy is changing as a function of TF loss.4) All reviewers agreed that statistical analyses are required throughout the manuscript. For example, in Figure 2—figure supplement 2B, a small decrease in ATAC-seq signal is observed at OD sites after SOX2 depletion, yet the major conclusion from the authors is that chromatin accessibility is unchanged. Are the authors arguing that this change is insignificant? Hence the need of statistical analyses.5) Data should be presented as heatmaps more consistently, not only as bar plots (as it currently is) to really reflect the order of magnitude of the effects observed on chromatin accessibility and histone marks . It is at least the case for Figure 3—figure supplement 2C-D  and in Figure 4D. Essential revisions:1) Additional descriptive analyses of the four identified types of OCT4 target sites (clusters 1 to 4) in Figures 3-5 are needed, to allow speculation about the different properties that may define these distinct classes of binding sites. For example, do they display differences in the number of OCT4/SOX2 binding sites? Are they differentially bound  or do they exhibit motifs  by other relevant TFs, such as bookmarking factors (ESRRB or CTCF would be of primary interest)? Do regulatory sites within a cluster tend to be in proximity/regulate the same category of genes (ontology)? Position regarding TADs? A greater depth of discussion/conjecture on this point is really required – why might these sites behave so differently?We agree that additional analysis can be informative about the nature of these clusters. As described in the original manuscript, we found that unaffected regions were enriched near promoters and we had identified an enrichment for OCT4-SOX2 motifs  and OCT4 binding  in cluster 1. We had also performed motif analysis that did not reveal other clear differences between the clusters (revised Supplementary file 2) and commented on this in the original manuscript.We have now expanded this analysis substantially. As suggested, we analyzed the number of OCT4/SOX2 binding sites , showing that cluster 1 loci have a higher prevalence of two binding sites in the same region. We also analyzed motif enrichment in the entire region , as opposed to 200bp close to the peak center as done previously, and replaced all motif analysis in the manuscript with whole region motif enrichment. This yielded mostly similar results to what we already commented on in the original manuscript. However, this analysis also yielded additional differential motif enrichments, including lower enrichment for CTCF motifs in Cluster 1 and slight enrichment for ESRRB motifs in Cluster 3. In addition, we have now used the large body of publicly available ChIP-seq datasets that have been processed by a standardized pipeline as part of the cistromeDB project to perform a more unbiased screening of potential co-binding factors in the different clusters that may not be detected by motif analysis. We analyzed the peak overlap of 3’628 ChIP-seq datasets from mouse ES cells in cistromeDB that overlapped with at least one region in our clusters and used this information to train a random forest model to classify the different clusters. The trained model predicted the correct cluster in the test data in 46.5% of cases, as opposed to 25% expected by random chance. Therefore, the features used by the model and enriched in the different clusters can inform us on factors that distinguish the clusters. Top parameters in the model included data from dox-treated ZHBTc4 cells, including a depletion of SOX2 and SS18 binding in cluster 1 after OCT4 depletion compared to the other clusters. This confirms that our approach can identify features that distinguish the clusters. The model uncovered several other expected top parameters, including promoter marks  enriched in Cluster 4 and POU5F1 (OCT4) enriched in Cluster 1. In addition, we detected several other pluripotency factors enriched in clusters 1 and 3 including NANOG, SOX2, NR0B1, and SALL4. We thus decided to check for overlap with the network of pluripotency regulators from Dunn et al., 2014, which were enriched in clusters 1 and 3. In accordance with our motif analysis, we found lower enrichment of CTCF, as well as RAD21, binding in cluster 1 compared to the other clusters. This new analysis is described in the manuscript  and can be found as Figure 3—figure supplement 4C-E and Supplementary file 3. We have also included a statement on the relevance of these findings in the Discussion (second paragraph) in the context of pluripotency loss when OCT4 is depleted.http://chromosome.sdsc.edu/mouse/hi-c/download.html) and found a very minor enrichment in larger distance to TAD boundaries in cluster 1. Because of the small difference, we have not included this analysis in the manuscript . This is described in the third paragraph of the subsection “OCT4 is required at the M-G1 transition to re-establish enhancer accessibility”. Note that we have utilized a Z-normalized scale for relative GO enrichment among the different clusters to avoid bias coming from the different number of regions, as previously done in Schwanhäusser et al. Nature 2011. We have modified all our previous GO analysis to utilize this method, which did not change any of the conclusions  and described this in the Materials and methods section. We also show that genes near clusters 1-3 are enriched for downregulation upon OCT4 depletion . As suggested, we looked for the position of loci with regards to TAD boundaries (from nuscript .2) There is little analysis relating chromatin accessibility with changes in expression at nearby genes . The functional impact of the observed (rather modes)– chromatin changes should be tested at the level of gene expression, at least at a few target genes. This would be an interesting point to infer whether the different properties of the various clusters are functional or not and perhaps whether different clusters are more likely to be more or less important for maintaining pluripotency when exiting mitosis. The OCT4-AID-degron cell line would be the perfect system to examine this question and should avoid a lot of secondary effects that may occur even at 24 hours DOX treatment in the ZHBTc4 cell.This is a good point. Importantly, it is not straightforward to directly compare the effect of changes in chromatin accessibility of the different clusters on transcription, due to the difficulty in assigning specific regulatory elements to their corresponding gene. Based on chromosome conformation capture assays, only 47% of distal regulatory elements interact with the nearest expressed TSS . Furthermore, we do not expect large changes in transcription because of the relatively small changes in chromatin accessibility inherent to our experimental system.Nevertheless, we annotated the closest OCT4-bound region to each gene (excluding those where the region was <1 kb from TSS) and among these and for Clusters 1-3, selected 5 genes for which expression was significantly downregulated upon OCT4 depletion for 24 hours according to King et al., 2017. As controls, we chose 7 genes closest to Cluster 4 regions that were shown unaffected by OCT4 depletion . We extracted RNA from 5 replicates of mCherry-OCT4-AID cells untreated or treated with IAA for 2 hours and performed RT-qPCR using primers flanking intron-exon junctions and exon-exon junctions. Pre-mRNAs of genes close to elements in cluster 1-2 and some in cluster 3 tended to be modestly downregulated upon OCT4 depletion, while those close to cluster 4 regions or mature mRNAs were generally not . This suggests that transcription of genes near loci whose accessibility depends on OCT4 can be affected by acute OCT4 depletion. This new analysis is included in the last paragraph of the subsection “Dynamic relationship between OCT4 concentration and chromatin accessibility”.3) ATAC-seq is a non-specific assay that is largely interpreted as chromatin accessibility, which likely reflects TF binding. Since the authors are specifically looking at peaks that change in ATAC-seq signal before and after OCT4/SOX2 degradation/silencing, changes in ATAC-seq peaks may reflect TF binding loss, rather than direct change in accessibility. To address this concern, the authors should computationally parse the ATAC-seq peaks into different size classes, such as short fragments that represent TF binding regions and 180-250 bp fragments that represent nucleosomes. The authors could then plot the nucleosome fragments in the different peak lists and show that nucleosome occupancy is changing as a function of TF loss.We thank the reviewers for this suggestion. We have now split the reads into bins of 0-100bp (nucleosome-free regions) and 180-250bp (single nucleosomes flanked by accessible regions). We decided to perform this analysis on the acute degradation of OCT4 using IAA treatment for 2 hours as this allows us to clearly assess the direct effects of TF loss on chromatin accessibility. Figure 5—figure supplement 1A-E show that the loss in accessibility upon acute OCT4 depletion also affects nucleosomal regions and therefore excludes that changes in accessibility simply reflect loss of TF binding. We have modified the text to incorporate this analysis (see the last paragraph of the subsection “Dynamic relationship between OCT4 concentration and chromatin accessibility”).4) All reviewers agreed that statistical analyses are required throughout the manuscript. For example, in Figure 2—figure supplement 2B, a small decrease in ATAC-seq signal is observed at OD sites after SOX2 depletion, yet the major conclusion from the authors is that chromatin accessibility is unchanged. Are the authors arguing that this change is insignificant? Hence the need of statistical analyses.We agree that more thorough statistical analysis of our data is useful. We have now included null hypothesis testing using either t-tests or Mann-Whitney U/Wilcoxon tests  at all comparisons of distributions . We have also included Fisher’s exact tests for comparisons of categories . Furthermore, we have displayed the p-values of all motif enrichments in the plots. We have justified and explained our choice of statistical tests in the Materials and methods section.Note that concerning the example mentioned above , these loci have been statistically tested for significant difference in accessibility using the limma algorithm at the differential analysis stage . However, we did not want to claim that there is no statistically significant difference when analyzing these data as a group, but rather that the effect size is small. We have now included statistical analysis of the distribution of values used to derive metaplots (such as the one referred to) where comparisons are made (see Supplementary file 1). This reveals that there is indeed a strong statistical significance at all comparisons due to the large number of data points measured. We have been careful in our writing so that our claims do not conflate effect size and significance.5) Data should be presented as heatmaps more consistently, not only as bar plots (as it currently is) to really reflect the order of magnitude of the effects observed on chromatin accessibility and histone marks . It is at least the case for Figure 3—figure supplement 2C-D  and in Figure 4D.We agree that heatmaps are informative to appreciate that while differences can be observed globally, they are rather small using our experimental system . We have included the suggested heatmaps in revised Figure 3—figure supplement 2E and Figure 4—figure supplement 2B, D and Figure 5—figure supplement 1E. Because it is difficult to visually appreciate these differences using such plots, we have also included heatmaps of fold-change values .