Understanding how the packaging of chromatin in the nucleus is regulated and organized toguide complex cellular and developmental programmes, as well as responses to environmentalcues is a major question in biology. Technological advances have allowed remarkableprogress within this field over the last years. However, we still know very little abouthow the 3D genome organization within the cell nucleus contributes to the regulation ofgene expression. The nuclear space is compartmentalized in several domains such as thenucleolus, chromocentres, telomeres, protein bodies, and the nuclear periphery without thepresence of a membrane around these domains. The role of these domains and their possibleimpact on nuclear activities is currently under intense investigation. In this review, wediscuss new data from research in plants that clarify functional links between theorganization of different nuclear domains and plant genome function with an emphasis onthe potential of this organization for gene regulation. We review recent discoveries that have elucidated how the spatial organization of thenuclear DNA in functional domains is relevant for the regulation of the genome inplants. PcBs concentrate distant transcriptionally inactive PcG-targeted genomicregions that form intra- or interchromosomal interactions also detectable by chromatinconformation capture techniques . A dispeCajal bodies  are dynamic substructures, which are found in animalas well as plant cells . CBs arede novoformation of the PBs  which surrounds the nucleoplasm consists of the nuclear envelope(NE), a double membrane layer with a continuum to the endoplasmatic reticulum (ER), nuclearpore complexes (NPCs), and the membrane adjoining the NPCs. The NP ensures the regulatedtransfer of mRNAs from the nucleus to the cytoplasm and of proteins in the reciprocaldirection, and has essential roles in gene regulation and genome organization in providingattachment sites for genomic regions and chromatin. While the cell biology of the NP and theassociated chromatin has been extensively reviewed (e.g. Daucus carota as the nuclear matrixconstituent protein (NMCP) family , and maize with two orthologues called NMCP/CRWNhomolog (NCH1 and 2) genes  in Arabidopsis results innuclear morphology changes such as reduced nuclear size and increased circularity, but doesnot lead to obvious growth defects  results in de-regulation of many genes which are involved in stressand defence responses, but also include other Gene Ontology (GO) terms  complex spanning the NE. The nuclear lamina in animals consists oflamins, type-5 intermediate filament proteins, and lamin-associated proteins. While some ofthe LINC complex members are conserved in plants, strictly defined lamins andlamin-associated genes are not present in plant genomes (2) genes . Anothercrwn4mutants, chromocentres are dispersed, while the number of chromocentres is reduced incrwn1 crwn2 double mutants  and of active chromatin (H2A.Z and H3K4me3)   (revieweH3K4me3) .PWO1 lead to a reduction innuclear size and misexpression of a set of genes which are also misregulated incrwn1 crwn2 mutants  in Arabidopsis to200 kb in tobacco  proteins, members of the Single-Myb-Histone proteinfamily . The TRBDvorackovaThe telomeric epigenetic pattern depends neither on telomere sequence composition nor ontelomere lengths, and shows large variability . ConsistThe impact of plant telomeres on long-distance interactions, the telomere gene silencing inother plant species, or participation of telomeres in formation of NBs also represent openquestions.Progressive approaches including CRISPR-based telomere labelling  describes chromatin regions that appearas ‘self-organized’ structures, formation of which is associated with chromatincompartmentalization, chromatin looping, and chromatin insulation (reviewed in Drosophila genome causing changes in chromatintopology (including TADs) showed that they are not predictive of changes in gene expression.These results suggest that the expression of a gene can endure alternative TAD patterns aslong as it maintains the same enhancer–promoter contact profile  showed thattissue-specific TAD borders in rice and maize often overlap with gene up-regulation. Anotherexample comes from comparisons of TAD patterns in diploid and subgenomes of tetraploid(formed via polyploidization) cotton genomes, which shows that conserved TAD boundaryregions tend to have a higher level of chromatin accessibility and the euchromatin histonemark H3K4me3 than do non-conserved regions  and bZIP (basic leucine zipper) proteins, which belong to twolarge plant transcription factor families  or liquid phase condensation is the de-mixing of ahomogeneous solution of proteins into two liquid phases where one is enriched for theprotein  providingthe biomolecules with an intrinsic capacity for LLPS required to form nuclear bodiesinvolving chromatin. The extensively studied non-histone chromatin protein family,Heterochromatin Protein 1 (HP1), first described in osophila , is a prDrosophila and a component of PRC1. CBX2 undergoes phase separation,thereby compacting PcG-associated chromatin  via LLPS.CBX2 is the homologue of chromodomain-containing Polycomb (Pc) protein oftin , is a clear example of a nuclearcompartment formed by LLPS. Fibrillarin (FIB1) in the dense fibrillar component andnucleophosmin (NPM1) in the granular component of the nucleolus can phase separateThe list of studies on LLPS-mediated formation of NBs is still growing, indicating thatphase transitions are key mechanisms for nuclear organization. For example,phosphatidylinositols, in particular phosphorylated PIP2, can play an important role innuclear compartment formation since they have been detected in the nucleoplasm, nuclearspeckles, and nucleolus. They interact with >300 nuclear proteins  and Bromodomain-containing protein 4 (BRD4) areenriched at clusters of enhancers and transcription machinery components, so-called superenhancers  to decipher in more depth the genetic andepigenetic information of an increased number of plant species, have allowed the existenceof several compartments in the 3D nucleus to be highlighted and are helping to uncoverconnections between regulatory domains of the 3D genome. Nevertheless, how spatial andstructural organization of the nucleus influences its function is far from being understood.Recent discoveries in this area have indeed proven to be key in depicting the complexity ofgene expression regulation within the reduced nuclear space as we have discussed. However,caution needs to be present in attributing functions to 3D nuclear organization. Theintrinsic capacity of chromatin to be plastic allied to adjustments of chromatinorganization and nuclear domain arrangements in relation to plant species, specifictranscriptional requirements, developmental stages, cell and tissue type, and epigenetic andstress factors can aid in allowing fast changes in gene expression and thus to inducequicker responses to specific requirements .LLPS is increasingly emerging as an important player in 3D genomics. Understanding theformation and organization of highly conserved and plant-specific nuclear domains inresponse to external and internal cues will contribute to our understanding of theregulation of these processes and plant phenotypes but also, most probably, to the discoveryof future molecular tools. On the other hand, this complex nuclear dynamism illustrates wellthe difficulty in finding universal rules for making direct connections between 3D nuclearorganization and predictable gene expression. Furthermore, chromatin-mediated regulation ofgenome accessibility may also be involved in molecular memories of responses given todifferent types of stimuli, but very little is known about perpetuating chromatin states andeven less about inheritable gene expression patterns between generations as a way to ensuremore prompt responses to challenges  (reviewe


During brain development, the genome must be repeatedly reconfigured in order to facilitate neuronal and glial differentiation. A host of chromatin remodeling complexes facilitates this process. At the genetic level, the non-redundancy of these complexes suggests that neurodevelopment may require a lexicon of remodelers with different specificities and activities. Here, we focus on the nucleosome remodeling and deacetylase (NuRD) complex. We review NuRD biochemistry, genetics, and functions in neural progenitors and neurons. Neurodevelopmental disorders (NDDs) are a highly heterogeneous and common group of conditions. NDDs include a number of “spectrum” conditions that can range widely in their severity, such as autism, attention-deficit/hyperactivity disorder, intellectual disability, epilepsy, and developmental delay. Relatedly, NDD etiology is highly complex. Genetics play a major role in NDDs, with hundreds of genes linked to disease. Moreover, the mutational landscape of NDDs is additionally complicated, with de novo mutations, structural rearrangements, and risk alleles all making important contributions ,2,3,4. ATo understand the mechanisms that drive NDD pathogenesis, we must first understand neurodevelopment. How is the production of different cell types and tissues programmed? Nowhere is this question more challenging to answer than in the developing brain, where hundreds of different neural subtypes must be produced, each of which must be programmed to ‘wire and fire’ with exquisite precision. Since cellular diversification must be achieved via the configuration and reconfiguration of an invariant genome, the role of epigenetic regulation in neurodevelopment has been the subject of intense interest. Indeed, chromatin remodelers—the genes responsible for epigenome dynamics—are prominently associated with NDDs. Deciphering how disparate chromatin remodeling functions contribute to neurodevelopment and NDDs remains an important unsolved problem. Here, we focus on the contribution of the nucleosome remodeling and deacetylase (NuRD) complex to brain development and NDD etiology.The NuRD complex was first characterized by several groups more than 20 years ago ,6,7. AmoThe NuRD complex contains a number of additional subunits, each of which is encoded by multiple paralogous genes a. RecentDrosophila Mi-2 chromodomains did not exhibit such a preference [Drosophila NuRD complexes appear to function similarly to their vertebrate counterparts despite the near absence of DNA methylation in flies. While this large complement of chromatin recognition modules can potentially endow NuRD with a complex valency for different chromatin states, a constellation of transcription factors have also been shown to play a role in recruiting NuRD to its targets (see below).Many NuRD subunits possess protein domains that recognize specific chromatin motifs . For inseference . The taneference . GATAD2Aeference . GATAD2Aeference . MBD3 poeference , but inseference . AccordiGenomic technologies have provided a definitive view of how chromatin states relate to NuRD occupancy. As with other chromatin remodeling complexes, NuRD is enriched at many transcriptional start sites and accessible regulatory elements ,29. HoweIn humans, brain development takes many years, and includes many distinct phases and processes. Beginning at gastrulation, ectodermal cells are converted into neuroepithelial progenitors via neural induction. Neuroepithelial cells form the neural plate, and the neural tube thereafter. These progenitors concomitantly take on positional information along the rostral-caudal and dorsal-ventral axes, and thereby become specialized to produce lineages that subsequently generate and populate specific brain regions and circuits. This process begins at neurogenesis. Neuroepithelial cells differentiate into neural progenitor cells, which self-renew and produce neuronal daughter cells. Next, neural progenitors typically enter a gliogenic phase, where they produce astrocytes or oligodendrocytes. Neuronal and glial daughter cells collaborate to generate specific tissue architectures and circuit structures, with neurons responding to environmental cues to migrate, and to pathfind their axons and dendrites. In humans, the histogenesis of the brain is largely complete by the end of the second trimester. Thereafter, neural progenitor cells become depleted in most regions. Neurons are permanently postmitotic, and glial cells are quiescent. Cellular proliferation therefore wanes in most regions of the perinatal brain. However, neurodevelopment continues at a furious pace postnatally. Waves of synaptogenesis, pruning, and myelination refine circuits. Waves of apoptosis delete neurons with inappropriate connections. Infants learn at an astonishing rate, as the brain goes through critical periods for sensory experience, language, and motor tasks. A comprehensive review of brain development goes well beyond the scope of this review, but the reader is directed to excellent general reviews on brain development ,42,43,44With ~80 billion neurons, ~80 billion glial cells , trillioMutations in chromatin remodelers are prominently linked to intellectual disability (ID) and autism spectrum disorder (ASD) ,51,52. IIDs are characterized by a generalized impairment of mental function and deficits in social and practical adaptive behaviors, which undermine the independence of afflicted individuals. Common examples include Down syndrome and Fragile X syndrome, but also conditions with environmental etiology such as fetal alcohol syndrome. The estimated prevalence of ID is approximately 1% across the population . ASD affCHD3 mutations lead to Snijders Blok-Campeau syndrome. CHD4 mutations lead to Sifrim-Hitz-Weiss syndrome, while GATAD2B mutations lead to GATAD2B-associated neurodevelopmental disorder. Each disorder is rare, with only ~30 to 50 individuals diagnosed to date in each case. These syndromes are designated as “NuRDopathies” due to their overall similarity . Theiewed in ,63,64,65CHD3 and CHD4 are clustered within the SNF2 ATPase domains and appear to structurally or functionally undermine their enzymatic functions [GATAD2B-associated mutations disrupt or truncate the CR1 or CR2 domains that are thought to, respectively, bind MBD3 or CHD proteins [CHD3/4 and GATAD2B mutations typically undermine the chromatin remodeling module within the resultant NuRD complex, this suggests that developmental defects might be driven by the persistence of functionally abrogated complexes that might compete with wild-type NuRD for genomic occupancy.De novo mutations in unctions ,61,63,64unctions ,73, and proteins . As CHD3MBD3 have additionally been observed in ASD patients, although it remains unclear whether these mutations are causative [De novo mutations in ausative . Interesausative ,75,76, rMbd3 or Chd4 during nervous system development leads to perinatal lethality [Chd4 conditional knockout neocortex [Mbd3, suggesting that gene misregulation might underlie progenitor depletion [NuRD function is essential for the development of the neocortex . Conditional deletion of either ethality ,77. In bethality ,77, but ethality ,79,80, aethality ,79,80. Teocortex . Howeverepletion . The conBrain function is predicated on the generation of a huge array of specialized neural cell types with different electrophysiology, morphology, and gene expression profiles. To generate neurons and glia in the correct sequences, progenitors must progressively change their developmental potential. Different phases of developmental potential are conceptualized as ‘competence states’, within which a progenitor has the potential to generate given cell-types in response to cell-intrinsic or -extrinsic cues ,83. ImpoIn vertebrates, the most thoroughly studied competence transition is the switch from neurogenesis to gliogenesis. Throughout the central nervous system, progenitors first generate neurons—often in stereotyped sequences. Most progenitors then irreversibly switch their output to produce glial cells before ceasing division . During Neurog1 . Neurog1 encodes a basic helix–loop–helix transcription factor that promotes neuronal determination [Mbd3 was in turn required for the timed recruitment of Polycomb to Neurog1 at the onset of gliogenesis, which is concomitant with promoter deacetylation [Mbd3 from neocortical progenitors led to prolonged and upregulated expression of the basic helix–loop–helix transcription factors Nhlh1, Nhlh2, Neurod1, and Neurod2, which are induced by Neurogenins and directly repressed by Mbd3 itself [During neocortical development, gliogenesis is timed to perinatal and postnatal stages of mouse development. Heterochromatic determinants, including DNA methylation and Polycomb, play a key role in this process ,94. Notamination , althougmination . Mbd3 watylation . Accordi3 itself ,97.Mbd3 conditional ablation led to prolonged neurogenesis during the gliogenic developmental window, Sparmann et al. found that Chd4 knockdown led to premature gliogenesis [Mbd3 failed to phenocopy Chd4 knockdown. Sparmann et al. concluded that Chd4 likely functioned independently of NuRD to suppress premature gliogenesis. Interestingly, a novel complex called ChAHP  has recently been described [Mbd3 conditional mutants, a subset of glial genes was prematurely upregulated. Taken together, these studies suggest that NuRD acts to reinforce the temporal competence state of progenitors, suppressing both premature gliogenesis during early phases of neocortical development and suppressing aberrant neurogenesis during late stages.Interestingly, whereas Tsuboi et al. found that ogenesis . Notablyescribed , which iescribed . These oHdac1 and Hdac2 double mutants resemble Chd4 or Mbd3 conditional knockout phenotypes in many respects, including reductions in brain size, reduced progenitor proliferation, and impaired neuronal migration [The above studies demonstrate considerable functional integration between NuRD and polycomb proteins. Accordingly, neocortical Polycomb mutants exhibit accelerated temporal development and premature gliogenesis ,100. Morigration . Mechaniigration . HoweverAdditional support linking NuRD to developmental timing has been uncovered in the developing retina. Like the neocortex, the retina possesses multipotent neural progenitors that undergo competence transitions to generate neurons and glia with a stereotyped birth order ,106. To Casz1 is the vertebrate orthologue of the Drosophila temporal transcription factor castor. In Drosophila ventral nerve cord neuroblasts, castor sits downstream of a cascade of sequentially expressed temporal transcription factors including the zinc finger transcription factor hunchback [Ikzf1 (Ikaros), which analogously acts upstream of Casz1 to regulate early retinal competence [Drosophila Mi-2 was first purified from a complex that included hunchback and Polycomb proteins [CASZ1 has recently been linked to ASD [In the retina, interactions between NuRD and temporal transcription factors such as Casz1 may additionally explain how the NuRD complex can be redeployed at different developmental stages to control fate decisions. unchback . The vermpetence , suggestmpetence ,112,113.proteins . During Mbd3 conditional mutant neocortices. However, during early phases of neocortical development, the Gotoh lab observed that Polycomb is required to maintain the birth order of neocortical neurons [Mbd3 conditional mutants, with markers of early-born and late-born neurons inappropriately coexpressed [Sox11, which encodes a transcription factor that contributes to the identity of early-born neocortical neurons [Precocious gliogenesis was not observed in  neurons . Similarxpressed . Finallyxpressed , which ixpressed . Muralid neurons . TogetheIn addition to Casz1, and Lhx2, the NuRD complex has also been shown to physically interact with a number of additional transcription factors that are known to regulate neurogenesis and neuronal cell fate. These include transcription factors expressed in progenitors (Ikzf1/2 , Fezf2 ,123,124,Taken together, studies in the neocortex and retina suggest that neural progenitor cells utilize the NuRD complex to reinforce multiple temporal competence states, ensuring that cell production is properly scheduled during development. NuRD appears to be redeployed at multiple stages to repress both past and future gene expression programs . The repUnderstanding the roles of the NuRD complex during neuronal differentiation has been challenging, in part due to the perinatal lethality of NuRD conditional knockout mice. To circumvent these issues, Nitarska et al. used RNAi and transfection-based conditional genetics to abrogate Chd3/4/5 in a mosaic fashion, permitting functional comparison of each NuRD complex . NitarskBdnf, and the Fos and Jun families [While the Nitarska et al. study supports the notion that Chd4 mainly contributes to progenitor functions in the neocortex, a prominent role for Chd4 in differentiated cerebellar granule neurons has been demonstrated by the Bonni lab. As with the neocortex, the differentiation of cerebellar granule cells is accompanied by extensive chromatin remodeling . In a sefamilies  (see belChd4 in postnatal granule cells led to defects in granule cell connectivity and electrophysiology [Chd4 was required to suppress promoter accessibility for a host of genes involved in synaptogenesis, as well as for immediate early genes, including Fos, Jun, and Arc members [Gatad2a and Hdac1, confirming that Chd4 functions via NuRD. In the cerebellum, Chd4 is prominently expressed in differentiating granule cells. The conditional deletion of ysiology , and theysiology . Yang et members ,39. GenoChd4 to regulate variant histone deposition at target gene promoters. Whereas the expression of canonical histones is restricted to S-phase, variant histones such as H2AX, H2AZ, and H3.3 can be transcribed throughout the cell cycle [Chd4 was required for its deposition at the transcriptional start sites of immediate early genes. In the absence of Chd4, a lack of H2AZ deposition abrogated the repression of these genes, leading to elevated immediate early gene expression in the absence of neuronal activity [Intriguingly, Yang et al. also found a requirement for ll cycle . Since nll cycle . Yang etactivity . ConsequSatb1, leading to defects in the synaptic density of mutant neurons [Interestingly, in the neocortex, immediate early genes are similarly misregulated in the absence of  neurons . Moreove neurons ,148, sugChd4 remodels transcription start sites, it was also found to bind to many distal regulatory elements. Focusing on enhancers, Goodman et al. found that Chd4 was required to restrict accessibility at enhancer elements [Chd4 conditional mutants. However, looping interactions within domains were markedly strengthened, elevating interactions between enhancers and promoters. Interestingly, while Chd4 mutation leads to similar increases in accessibility at enhancers and promoters, H2AZ deposition was only reduced at promoters, whereas Ctcf recruitment was only elevated at enhancers. While elements . ElevateImportantly, Goodman et al. provide strong support for the notion that Chd4 suppresses cohesin binding and thereby genome looping. However, it remains to be determined whether Chd4 performs these activities via NuRD. Indeed, the recently described ChAHP complex, containing Chd4 and Adnp, was similarly shown to suppress cohesin recruitment to cryptic Ctcf sites found within repetitive elements . NonetheHuman Clinical Genetics has identified a large number of genes that can contribute to ASD and ID. Despite this fact, it remains unclear how these genes lead to neurodevelopmental disorders. For example, a number of different mechanisms have been proposed to explain ASD pathogenesis, including imbalances in brain excitation versus inhibition, defective neural connectivity, and defects in neocortical neurogenesis ,154,155.Work by the Bonni lab in cerebellar granule cells has demonstrated that NuRD abrogation undermines neuronal plasticity, synaptogenesis, and thereby behavior. These studies have elucidated mechanisms that can directly explain the behavioral deficits associated with NuRD gene mutations. However, these studies cannot explain how NuRD mutations might lead to brain overgrowth. In earlier stages of neurodevelopment, a number of groups, including the Gotoh, Hendrich, and Riccio labs, have demonstrated that the NuRD complex regulates progenitor proliferation and temporal competence states. NuRD also regulates the migration of neocortical neurons. Going forward, the challenge will be to identify and understand the relative contribution of these processes to neurodevelopmental disorders—in progenitors, neurons, and different brain regions.Another question that will be critical to address in the future is to understand the mechanistic basis underlying NuRD-dependent gene regulation in neural cells. In embryonic stem cells, Bornelöv and colleagues performed a high-resolution time-course analysis, revealing that NuRD occupies almost all accessible genomic regions . Indeed,The unprecedented spatial and temporal resolution of the Bornelöv study underscores the ability of NuRD to globally regulate accessible elements throughout the genome. However, a somewhat different picture emerged when examining cooperative interactions between NuRD and transcription factors. Studying the zinc finger transcription factor Ikzf1, Liang et al. found that Ikzf1 recruited NuRD to target gene promoters, leading to dramatic abrogation of gene transcription within as little as 12 min . TranscrResearch by the Bonni lab in the developing cerebellum has provided the most detailed view of how NuRD controls the genome in neural cells. Similarly to the work by Bornelöv et al., they demonstrated that NuRD has widespread recruitment to regulatory elements. Like Liang et al., they found that a subset of target genes were completely decommissioned by NuRD ,39. CleaFinally, a critical missing piece of the puzzle is to understand how mutations associated with neurodevelopmental disorders alter NuRD complex composition and function. As the mutations associated with NuRDopathies are usually heterozygous de novo point mutations, neurodevelopmental pathogenesis may be driven by haploinsufficiency. Since NuRD abrogation affects global genome accessibility, subtle changes in complex levels could easily lead to widespread transcriptome misregulation. Alternatively, mutant proteins might incorporate into complexes, which would consequently be functionally defective. Defective complexes might compete with wild-type NuRD for genome occupancy in a dominant negative fashion. The large number of chromatin interaction modules present in NuRD subunits might also play a role in neurodevelopmental defects. Mutations that disrupt chromatin recognition or affect transcription factor interactions might lead to reduced or aberrant recruitment of NuRD to the genome. Distinguishing between these possibilities will be of critical importance for uncovering how NuRD function and dysfunction underlies neurodevelopmental disorders.


The three-dimensional configuration of the genome ensures cell type-specific gene expression profiles by placing genes and regulatory elements in close spatial proximity. Here, we used in situ high-throughput chromosome conformation (in situ Hi-C), RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) to characterize the high-order chromatin structure signature of female germline stem cells (FGSCs) and identify its regulating key factor based on the data-driven of multiple omics data. By comparison with pluripotent stem cells (PSCs), adult stem cells (ASCs), and somatic cells at three major levels of chromatin architecture, A/B compartments, topologically associating domains, and chromatin loops, the chromatin architecture of FGSCs was most similar to that of other ASCs and largely different from that of PSCs and somatic cells. After integrative analysis of the three-dimensional chromatin structure, active compartment-associating loops (aCALs) were identified as a signature of high-order chromatin organization in FGSCs, which revealed that CCCTC-binding factor was a major factor to maintain the properties of FGSCs through regulation of aCALs. We found FGSCs belong to ASCs at chromatin structure level and characterized aCALs as the high-order chromatin structure signature of FGSCs. Furthermore, CTCF was identified to play a key role in regulating aCALS to maintain the biological functions of FGSCs. These data provide a valuable resource for future studies of the features of chromatin organization in mammalian stem cells and further understanding of the fundamental characteristics of FGSCs.The online version contains supplementary material available at 10.1007/s00018-021-04107-y. The chromatin architecture of germline stem cells (GSCs) carries the information necessary for cells to perform their unique functions and is thus an essential factor in the transmission of the genome from generation to generation. GSCs renew themselves and differentiate into gametes that include sperm and metaphase II (MII) oocytes –3. DurinHigh-throughput chromosome conformation (Hi-C) is a powerful technology to study genome-wide architecture, which allows the high-order chromatin structure to be displayed and reveals the chromatin organization in the nucleus . The spaCCCTC-binding factor (CTCF) is a critical regulator of chromatin architecture, which underlies its functions that include gene expression and three-dimensional (3D) genome construction and regulation –22. In mIn this study, we used in situ Hi-C technology to compare the chromatin organizations of FGSCs and induced pluripotent stem cells (iPSCs), adult stem cells (ASCs), which included SSCs and neural stem cells (NSCs), and somatic cells  to explore the chromosome structure characteristics of FGSCs. Together with RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq), we identified distinct features  of the chromatin organization in FGSCs at three major levels: A/B compartments, TADs, and chromatin loops, and found that FGSCs were most similar to other ASCs and largely different from iPSCs and STO cells. By further analysis of the distinct features, we revealed that CTCF may be a crucial factor to maintain the properties of FGSCs through regulation of the high-order chromatin structure.The CAG-EGFP mice from the Model Animal Research Center of Nanjing University, also named C57BL/6-Tg (CAG-EGFP) C14-Y01-FM131-Osb . The Ddx1 progeny of DBA/2 × CAG-EGFP mice, as previously described  and incubated at room temperature for 30 min, followed by separation on a magnet and washing twice with 1× TWB. The beads were resuspended with mixture  and incubated at 37 °C for 30 min. Then, separation on a magnet was performed, after which the solution was discarded and washing was carried out twice. The beads were resuspended in 1× NEB Quick ligation reaction buffer , and NEB DNA Quick ligase  and an Illumina indexed adapter of NEBNext Multiplex Oligos for Illumina  were added at room temperature for 15 min. Then, USER enzyme of NEBNext Multiplex Oligos for Illumina (3 μl) was added to the ligation mixture at 37 °C for 15 min. The DNA was washed twice and eluted by resuspending the beads with Tris–HCl , followed by incubation at 98 °C for 10 min. The DNA suspension was transferred into a fresh tube and stored at − 20 °C. The Hi-C library was amplified in a PCR system  with the following PCR conditions: initial denaturation at 98 °C for 30 s; eight cycles of denaturation at 98 °C for 10 s and annealing/extension at 65 °C for 75 s; followed by final extension at 65 °C for 5 min, and then maintenance at 4 °C. The DNA fraction in the size range of 300–500 bp was selected using Agencourt AMPure XP beads (Beckman Coulter). The DNA was eluted with 1× Tris–HCl buffer (33 μl) and incubated at room temperature for 5 min, followed by separation on a magnet and transfer of the solution to a fresh labeled tube. This produced the final Hi-C library. The quality of the Hi-C library was determined using the Qubit dsDNA HS Assay and Agilent 2100 DNA 1000 HS kit. The high-quality libraries were sequenced using an Illumina sequencing platform.Cells were used for in situ Hi-C, including iPSCs , FGSCs , SSCs, NSCs, and STOs . Hi-C liThe preparation of ChIP and input DNA libraries was performed as previously described . In brieHi-C pair-end was trimmed of adaptor sequences and low-quality reads were filtered with BBmap (version 38.16). HiCPro (version 2.7)  was thenIij between two replicates, these were correlated by comparing each point’s interaction in the normalized interaction matrix. Considering that the interaction matrix was highly skewed toward proximal interactions, we calculated the correlation to a maximum distance restricted to 2 Mb between points i and j. R was used to calculate Pearson’s correlation between two duplicates.The data reproducibility was confirmed by calculating Pearson’s correlation coefficient between the two Hi-C repeats. For each possible interaction p(s) only considering intra interactions, was calculated with normalized interaction matrices at 40-kb resolution, as described previously . These results were confirmed by immunofluorescence and most cultured cells were also positive for PLZF expression, which confirmed their identity as SSCs . We confirmed high reproducibility of the Hi-C data  and combined the two biological replicates into a single set of merged Hi-C data per cell type to reach a maximum resolution of 20 kb.To reveal the signature of the chromatin architecture in FGSCs, we performed in situ Hi-C  with two5 to 1 × 108 bp for FGSCs and the other cells  (Suppl. Table S3). Well-defined TADs were occupied in ~ 90% of the genome across cell types . According to the proportion of overlapping TADs compared with FGSCs, we classified the TADs into five types: stable, merged, split, reorganized, and unique , which also suggested that CTCF plays a major role in the regulation of aCALs. Moreover, we observed that CTCF was enriched in the A compartment in FGSCs  technology . After CTCF knockdown in FGSCs, we observed that the size of FGSCs was obviously larger and the proliferative capacity of FGSCs was reduced significantly compared with the control Fig. a–c. Furtcis-interactions. The relative proportions of cis-short interactions were decreased in the CTCF knockdown group, which recovered with the distance of interactions . We observed the change of TADs and A/B compartments between the CTCF knockdown group and control Fig. a. Globalons Fig. c, indicaNotch2 showed higher expression than in the CTCF knockdown group in which it lost formation of the chromatin loop  and ASCs, have important implications in basic biology and regenerative medicine. Our previous studies have shown that FGSCs exist in postnatal ovarian tissues of mice, rats, humans, and pigs , 4–6, 49To identify the chromosome structure characteristics of FGSCs, we compared FGSCs with pluripotent stem cells (iPSCs), ASCs (SSCs and NSCs), and somatic cells (STO cells) by Hi-C technology. The results revealed that FGSCs had a distinct high-order genome structure in terms of the A/B compartment status, chromatin loops, and TADs. For further characterization, we identified FGSC-specific activated and repressed compartment regions, and identified some genes that were highly related to the switch of the FGSC compartment status. These genes were related to stem cell maintenance and differentiation pathways, which strongly supports the role of FGSCs as ASCs with some shared characteristics with SSCs and NSCs. This suggests that the compartment status was highly specific to the cells. However, the further analysis of TADs showed that they were stable across stem cells, while chromatin loops analysis demonstrated that there were less shared chromatin loops, which indicated that chromatin loops may be another feature of the 3D chromatin structure. Hence, we propose that the regulation of the 3D chromatin architecture is not at a single level. By the combination of the distinct compartments and chromatin loops in FGSCs, we finally identified aCALs and repressed CALs in FGSCs. The results of GO analysis showed that the genes of aCALs were involved in female development and stem cell development, which suggested that these aCALs were features of FGSCs and consistent with FGSC biology. Our data indicated that the characteristics of FGSCs were regulated by cooperation through multiple levels of the high-order chromatin structure, such as the compartment status and chromatin loops, which has revealed the features of the 3D chromatin architecture.By further exploring these specific chromatin loops, CTCF was identified as an important factor to regulate these features. Thus, we knocked down CTCF and found that CTCF knockdown inhibited FGSC proliferation and induced differentiation. Combined with RNA-seq and Hi-C results, we also found that the CTCF knockdown group lost most of the specific chromatin loops in which genes that did not form chromatin loops were enriched in female development. These findings not only revealed that CTCF is involved in maintaining the properties of FGSCs through regulating the high-order chromatin structure, but also suggested that FGSC development in vitro can be used to study female germline cell development.Previous researches reported CTCF shaped the chromatin structure accompanied with cohesin complex , 53–55. In conclusion, we present a comprehensive overview of the chromatin organization in FGSCs to create a rich resource for genome-wide maps. Our findings revealed that the chromatin architecture of FGSCs included a unique compartment status and chromatin loops, especially aCALs, which may contribute to their cell type-specific gene regulation. Furthermore, CTCF was identified to play an important role in maintaining the biological functions of FGSCs by regulating the chromatin organization. These data provide a valuable resource for future studies of the features of chromatin organization in mammalian stem cells and further understanding of the fundamental features of FGSCs.Supplementary file1 (PDF 1172 KB)Supplementary file2 (XLSX 12 KB)Supplementary file3 (XLSX 107 KB)Supplementary file4 (XLSX 294 KB)Supplementary file5 (XLSX 46 KB)Supplementary file6 (XLSX 12 KB)Below is the link to the electronic supplementary material.


Towards the goal of making ‘smart’ cell therapies, one that recognizes disease conditions (e.g. hypoxia) and then produces mitigating biologics, it is important to develop suitable promoters. Currently, hypoxia responsive promoters are composed of strongly repeated sequences containing hypoxia response elements upstream of a minimal core promoter. Unfortunately, such repeated sequences have inherent genomic instability that may compromise the long‐term consistency of cell‐based therapeutics. Thus, we designed a synthesis‐friendly hypoxia‐inducible promoter (named SFHp) that has GC content between 25% and 75% and no repeats greater than 9 base pairs. In HEK293 cells stably integrated with genes regulated by synthetic SFHp, we demonstrated inducible reporter expression with fluorescent proteins, cell morphology rewiring with our previously engineered RhoA protein and intercellular cell signalling with secreted cytokines. These experiments exemplify the potential usage of SFHp in cell‐based therapeutics with integrated genetic circuits that inducibly respond to the disease microenvironment. HIFhypoxia‐inducible transcription factorHREhypoxia response elementSFHpsynthesis‐friendly hypoxia‐inducible promoterTSStranscriptional start site1Cell‐based therapeutics use genetically engineered cells as vehicles of delivery for biologics in the treatment or prevention of diseases , 2. In tPromoters regulate transcription initiation at the correct transcriptional start site (TSS) and control expression levels depending on the conditions of the cell. Both of these are achieved through the use of conserved sequence elements located upstream of transgenes. The minimal core promoter is responsible for specifying the TSS to transcription machinery . It ofteTargeting the hypoxic microenvironment with cell‐based therapeutics is particularly promising because of its role in a number of different diseases, including heart disease, cancer and rheumatoid arthritis , 16. WhiThe SFH promoter can be used in cell‐based therapeutics to conditionally regulate the expression of therapeutic transgenes in hypoxic microenvironments. The lack of exact repeats in the SFH promoter should improve genomic stability and cell line consistency over long‐term culturing.22.1HRE with the consensus sequence 5′ TACGTG 3′ was used to design the enhancer region of SFHp. The exact repeat including the HRE (i.e. 5′ GTGACTACGTGCTGCCTAG 3′) from plasmid pGL4.42 was concatenated seven times to form the seed sequence for optimization. This seed sequence was optimized using the dnachisel python package with constraints that enforce no repeats greater than 9 bp, GC content between 25% and 75% and seven occurrences of the HRE (i.e. 5′ TACGTG 3′). Upon program execution, dnachisel randomizes the seed sequence until all constraints are satisfied. The final optimized seed sequence was then concatenated with the minimal CMV core promoter to create SFHp. Sequence repeats were identified using the EMBOSS dottup online tool with a window size of 10 bp, plotting each sequence against itself. GC‐content plots were generated in RStudio using packages ‘seqinr’ and ‘ggplot2’ with a window size of 30 bp.2.21MGLTSQLLPPLFFLLACAGNFVHG24) and a fragment resulting from TACE cleavage of TNFα (amino acids 77–233). Similarly, the Ceru, CaRQ, Venus and active TNFα sequences were human codon‐optimized inserted into the SFHp plasmids by Genscript  was assembled as the tandem fusion of the IL4 leader sequence  supplemented with 10% fetal bovine serum  in T25 flasks and incubated at 37°C and 5% COescribed . Specifi2.42 (Sigma). Blebbing was induced in HEK293 cells expressing CaRQ with stimulation of 10 μM ATP (Sigma).Prior to imaging, cells were plated in 96‐well glass‐bottom plates (Mattek). Images were taken with the Olympus IX81 microscope, using a Lambda DG4 xenon lamp for the light source, and a QuantEM 512SC CCD camera with a 10× objective or 40× objective (Olympus). Excitation (EX) and emission (EM) filter bandpass specifications were as follows, for fluorescent proteins: Ceru  and Venus  (Semrock). Images were analysed via ImageJ and μManager software. Time‐lapse images were taken 10 s apart with 1 s exposure. Imaging was conducted with cells washed and maintained in PBS with CaCl33.1An SFHp was created by staggering the placement of seven HRE (i.e. 5′ TACGTG 3′) that have no repeats in the flanking subsequences upstream of a minimal CMV core promoter . The HRE3.2N‐oxylglycine (NOG) in the cytosol. NOG functions as a competitive inhibitor of prolyl hydroxylase domain proteins and blocks their ability to attach hydroxylase modifications on HIF‐1α transcription factors. These modifications occur during normoxic conditions to label HIF‐1α for proteasome degradation. In the absence of hydroxylation, cytoplasmic HIF‐1α concentration is stabilized and translocated across the nuclear envelope where HIF‐1α dimerizes with HIF‐1β to bind and activate gene transcription from promoters containing HRE sites [To show that SFHp has inducible gene expression, we created stable HEK293 cells by lentiviral infection that expressed cyan fluorescent protein Cerulean  all under regulation of SFHp Figure . HEK293 RE sites . Thus, a3.32+ activated RhoA protein (named CaRQ) under SFHp  ultimately resulting in directed cell migration  at the N‐terminus; to visualize expression, it is fused to the yellow fluorescent protein Venus [PMLyn requires Met1 to be cleaved for lipid modifications that anchor tagged the protein to the plasma membrane, the apparent membrane localization of CaRQ means transcription occurred at the SFH promoter rather than by read‐through expression [2+ efflux from endoplasmic reticulum, thereby raising cytosolic Ca2+ concentrations [To show that SFHp can inducibly express proteins that can alter the intracellular functions, we created stable HEK293 cells by lentiviral infection that expressed an engineered Cap Figure . Our gron Figure . The Ca2+ signal . To direin Venus . Likewispression . Next, atrations . After atrations . A CaRQ‐3.4Thosea asigna virus and shown to have high cleavage efficiency allowing for expression of bicistronic sequence from a single promoter [To show that SFHp can inducibly express paracrine signals for the intercellular signalling, we created stable HEK293 cells  by lentiviral infection that expressed Venus and active TNFα signalling protein joined in tandem by a T2A co‐translational, ‘self‐cleavage’ site—all regulated by SFHp Figure . The T2Apromoter . As expe4We engineered a synthesis‐friendly promoter named SFHp that constrains gene expression to hypoxic conditions when stably integrated into HEK293 cells. To do so, we arranged hypoxia responsive elements upstream of a minimal CMV core promoter and checked for repeating sequences and suitable GC content. These two features are common culprits that complicate the synthesis of engineered sequences and subject them to higher prices when commercially synthesized. Furthermore, the lack of these repeated subsequences in SFHp should make the genetic material more stable and less likely corrupted when integrated into ‘smart’ cell‐based therapeutics. We demonstrated the ability of SFHp to express fluorescent proteins (i.e. Ceru and Venus) and engineered protein switches (i.e. CaRQ) upon addition of the DMOG chemical used to activate the HIF‐1α transcription factor. Furthermore, we used SFHp‐controlled expression of active TNFα, called sender cells, to act as a paracrine signal for hypoxic conditions. This intercellular communication was demonstrated by co‐culturing sender cells with receiver cells containing a NFκB‐regulated gene circuit. We envision that our synthetic promoter SFHp can be used in engineered therapeutic cells that are administered systemically in order to identify and conditionally express active genes at hypoxic environments within the human body. Hypoxia can act as a therapeutic target for a number of different diseases, including heart disease, cancer and rheumatoid arthritis , 16. As The authors have declared no conflict of interest.Supporting informationClick here for additional data file.Supporting informationClick here for additional data file.


Diffuse large B-cell lymphoma (DLBCL) comprises at least two main biologically distinct entities: germinal center B-cell (GCB) and activated B-cell (ABC) subtype. Albeit sharing common lesions, GCB and ABC DLBCL present subtype-specific oncogenic pathway perturbations. ABC DLBCL is typically characterized by a constitutively active NF-kB. However, the latter is seen in also 30% of GCB DLBCL. Another recurrent lesion in DLBCL is an 11q24.3 gain, associated with the overexpression of two ETS transcription factors, ETS1 and FLI1. Here, we showed that FLI1 is more expressed in GCB than ABC DLBCL and we characterized its transcriptional network.Gene expression data were obtained from public datasets GSE98588, phs001444.v2.p1, GSE95013 and GSE10846. ChIP-Seq for FLI1 paired with transcriptome analysis (RNA-Seq) after FLI1 silencing (siRNAs) was performed. Sequencing was carried out using the NextSeq 500 (Illumina). Detection of peaks was done using HOMER (v2.6); differential expressed genes were identified using moderated t-test (limma R-package) and functionally annotated with g:Profiler. ChIP-Seq and RNA-Seq data from GCB DLBCL cell lines after FLI1 downregulation were integrated to identify putative direct targets of FLI1.. Genes negatively regulated by FLI1 included tumor suppressor genes involved in negative regulation of cell cycle and hypoxia. Among positively regulated targets of FLI1, we found genes annotated for immune response, MYC targets, NF-κB and BCR signaling and NOTCH pathway genes. Of note, direct targets of FLI1 overlapped with genes regulated by ETS1, the other transcription factor gained at the 11q24.3 locus in DLBCL, suggesting a functional convergence within the ETS family. Positive targets of FLI1 included the NF-κB-associated ASB2, a putative essential gene for DLBCL cell survival. ASB2 gene downregulation was toxic in GCB DLBCL cell lines and induced NF-κB inhibition via downregulation of RelB and increased IκBα. Additionally, downregulation of FLI1, but not ASB2, caused reduction of NF-κB1 and RelA protein levels.Analysis of clinical DLBCL specimens showed that FLI1 gene was more frequently expressed at higher levels in GCB than in ABC DLBCL and its  protein levels were higher in GCB than in ABC DLBCL cell linesWe conclude that FLI1 directly regulates a network of biologically crucial genes and processes in GCB DLBCL. FLI1 regulates both the classical NF-κB pathway at the transcriptional level, and the alternative NF-κB pathway, via ASB2. FLI1 and ASB2 inhibition represents a potential novel therapeutic approach for GCB DLBCL.The online version contains supplementary material available at 10.1186/s13046-021-02159-3. FLI1 gene is an oncogene rearranged in 95% of Ewing sarcoma, a pediatric tumor of neuroectodermal origin ) with 1x HALT Proteinase inhibitor cocktail (Thermo Scientific). Rabbit polyclonal α-FLI1, 5 μg  was added to the diluted chromatin samples. Antibody/protein/DNA complexes were captured with protein G magnetic beads at 4 °C (Millipore). Magnetic beads were washed using a magnetic rack and increasing stringencies of salt buffers in the following order: Low Salt washing buffer, 0.1% (w/v) SDS, 1%(v/v) Triton-X 100, 2 mM EDTA, 20 mM Tris–HCl [pH 8.1], 150 mM NaCl; High Salt washing buffer, (0.1% (w/v) SDS, Triton-X 100 1% (v/v), 2 mM EDTA [pH 8.0], 20 mM Tris–HCl [pH 8.1], 500 mM NaCl); LiCl buffer, 0.25 M LiCl, 1% (w/v) IGEPAL-CA 630, 1% (v/v) deoxycholic acid, 1 mM EDTA, 10 mM Tris–HCl [pH 8.1];Tris–EDTA buffer, .The Tris EDTA buffer wash was repeated twice. Immunoprecipitated complexes were eluted from the dynabeads using elution buffer (SDS 1% (w/v), 0.1 M NaHCO3) with RNAse A added and incubated at 37 °C for 30′ on a thermomixer (1200 rpm). This was followed by reversal of cross-links performed by adding 5 M NaCl together with 0.5 M EDTA, Tris-HCL and Proteinase K for 2 h at 62 °C on a thermomixer (1200 rpm). Lastly DNA was purified using the QIAquick PCR purification kit (Qiagen). For validation, qRT-PCR was performed using KAPA SYBR FAST qPCR Master Mix (2x) ABI Prism. Primers targeting g:Profiler using gene sets from the Molecular Signatures Database (MSigDB v5.1) [Standard settings were used for g:Profiler data mining [. Signatures with absolute log fold change > 0.1 and adj.P < 0.05 were considered as biologically relevant.All bioinformatic processing was performed using R/Bioconductor software packages in RStudio. RNA-Seq raw reads were quality assessed using fastqc . For eacDB v5.1)    and genea mining . SignatuFor ChIP-Seq analysis, raw sequencing was mapped onto the Genome Reference Consortium Human Build 37 (GRCh37) using bowtie2. Reads filtering was done using SAMtools to keep reads that map only once, with a quality score of 10 or more, and to remove duplicates. We first performed an exploratory analysis with IGV genome browser to assess the quality of the ChIP and detect issues and abnormalities. Peaks were then called using HOMER and selected to control the false discovery rate (FDR) at 0.001. To biologically interpret the results of ChIP-Seq experiments, we looked at genes and other annotated elements that are located in proximity to the identified enriched regions (peak annotations) using HOMER, PeakAnalyzer and BedTools (version 2.17). Promoter regions were defined within 3 kb from the closest TSS.Target peaks located further than 3 kb from the closest TSS were annotated using the enhancer-promoter interactions map of Mifsud et al. , derivedp < 0.01) correlated with expression levels of FLI1 in DLBCL clinical specimens (GSE10846). Overlapping between lists was done using the VENNY on-line tool [Pearson correlation was used to identify those genes significantly 2 anti–human IgM (Southern Biotech). Cells were coated on a poly-L-lysine matrix then fixed 20′ with PFA 4% at RT. Cells were permeabilized with PBS + 0.1% Triton X-100 10′ at RT. To block unspecific staining, samples were treated for 1 h with PBS + 5% BSA at RT before staining. The following primary antibody was used in PBS 5% BSA buffer: rabbit monoclonal α-NF-Kappa-B1 p105/p50 (D4P4D) . Samples were incubated overnight at 4 °C. For immunofluorescence, the following secondary antibody was used: goat anti-rabbit IgG labelled with Alexa 568 (Thermo Fisher Scientific) 1 h at RT in the dark. Slides were counterstained after three washes of PBS with 0.3 μg/mL 4,6-diamidino-2-phenylindole (Sigma-Aldrich). Images including Z-stacks were acquired on a Leica SP5 with an objective with × 63 magnification. Nuclear localization of NF-κB1/p50 was quantified by ImageJ software.FLI1 RNA expression in four publicly available datasets of DLBCL clinical specimens: GSE98588, phs001444.v2.p1, GSE95013 and GSE10846 [FLI1 expressors were enriched among GCB  compared to ABC  DLBCL samples (P < 0.05) . A similar difference, although not statistically significant, was observed in terms of RNA expression  after FLI1 downregulation by siRNAs Fig. SA-B. FLI1WEE1, a known FLI1 target.To identify FLI1 binding sites across the genome, we performed ChIP-Seq with an anti-FLI1 antibody on the same cell lines used for RNA-Seq. FLI1 binding sites were observed in intergenic regions (37% of the peaks), in intragenic regions (37%) including introns, exons and UTRs, as well as in promoter regions of annotated transcripts 26%)  or concomitant BCL2/MYC translocation   Fig. A and B. H2) Fig. A. At 48 H2) Fig. B, suggesH2) Fig. B. This rH2) Fig. B. These H2) Fig. B, pairedH2) Fig. . This inH2) Fig. C.Fig. 4AOf the two ETS transcription factors mapped within the 11q24.3 locus that is recurrently gained in approximately 25% of DLBCLs, ETS1 is more expressed in ABC than in GCB DLBCL , 9. HereCXCR5, CD40, CD79A, NF-κB1, ITGA4, FAIM3, DDX21, AATF, RASGRP1, LYN, JAK3 and TRAF1/4/5. Conversely, CDKN1B, EZR, E2F7 and TFDP2 were among the negatively regulated genes. Our results in cell lines were sustained by findings in clinical specimens: FLI1 positively regulated targets in cell lines overlapped with genes that positively correlated with the expression levels of the transcription factor in GCB DLBCL samples. Moreover, we took advantage of a genome-wide CRISPR-Cas9 screen of DLBCL cell lines [NFKBIA gene, encoding IκBα, are associated with a poor outcome in GCB DLBCL cases [NFKBIA) inactivation also in some GCB DLBCL belonging to ST2 tumors [Transcriptome analysis after FLI1 downregulation showed that FLI1 regulates important biological pathways. Integration of the identified binding sites with RNA-Seq from cell lines after FLI1 downregulation allowed the identification of putative direct targets of FLI1. Transcripts negatively regulated by FLI1 included tumor suppressor genes involved in the negative regulation of mitotic cell cycle and hypoxia. Among the FLI1 positively regulated targets we found genes annotated as MYC targets and members of BCR, CD40, TNFα and IL2 signaling pathways. Of note, direct targets of FLI1 overlapped with genes regulated by ETS1, the other transcription factor gained within the 11q24.3 locus in DLBCL , suggestll lines  and idenll lines , 42. Ourll lines . AlthougCL cases . FinallyCL cases , NF-κB i2 tumors . The NF-2 tumors . In dend2 tumors . In GCB 2 tumors –50, althIn conclusion, the transcription factor FLI1 was expressed at higher levels in GCB than ABC DLBCL and it directly regulated a network of biologically crucial genes and processes. We identified a mechanism of NF-κB activation mediated by a novel direct target of FLI1, ASB2, which downregulated IκBα and upregulated RelB in GCB DLBCL. ASB2 and FLI1 inhibition represents a potential novel therapeutic approach for GCB DLBCL.Additional file 1.


Runx1 in mouse metanephric mesenchyme-derived mK4 cells results in large-scale genome-wide changes to chromatin accessibility and gene expression. Open chromatin regions near down-regulated loci enriched for Runx sites in mK4 cells lose chromatin accessibility in Runx1 knockout cells, despite remaining Runx2-bound. Unexpectedly, regions near upregulated genes are depleted of Runx sites and are instead enriched for Zeb transcription factor binding sites. Re-expressing Zeb2 in Runx1 knockout cells restores suppression, and CRISPR mediated deletion of Zeb1 and Zeb2 phenocopies the gained expression and chromatin accessibility changes seen in Runx1KO due in part to subsequent activation of factors like Grhl2. These data confirm that Runx1 activity is uniquely needed to maintain open chromatin at many loci, and demonstrate that Zeb proteins are required and sufficient to maintain Runx1-dependent genome-scale repression.Runt-related transcription factor 1 (Runx1) can act as both an activator and a repressor. Here we show that CRISPR-mediated deletion of  Runt-related transcription factor (Runx) 1 & 2 impact development and disease by activating or repressing transcription. In this manuscript we used genome editing tools to remove Runx1, and as expected, observed widespread changes in chromatin accessibility. Newly closed areas contained Runx1 binding sites and were enriched near genes whose expression depended on Runx1. Interestingly, this occurred despite continued binding of Runx2 to the same regions of DNA, which suggests that Runx2 is insufficient to maintain open chromatin and expression of Runx1 target genes in this cellular context. By contrast, newly opened chromatin regions, many near genes that were upregulated in Runx1 knockout cells, did not enrich for Runx1 binding sites. Instead, these regions were enriched for sites for the repressor Zeb proteins. We found that the loss of Zeb 1 & 2 expression, direct transcriptional targets of Runx1, resulted in the opening of chromatin and upregulation of genes residing near the newly open sites in Runx1 knockout cells. The same sites were also open and nearby genes expressed in edited Zeb1 and Zeb2 knockout cells. Among them were transcription factors, such as the Grhl2 gene, which in turn bind to and upregulate their target genes. Thus, the loss of a single transcription factor initiates a cascade of direct and indirect ramifications with likely negative effects on development and health. Mammalian genomes encode over 1,000 Transcription factors (TFs) which precisely control gene expression through complex combinatorial interactions and transcriptional cascades . AchieviRunx/Runt TF family members recognize a characteristic TGTGGT DNA-binding motif, are conserved across all metazoans , and plaWe used the mouse metanephric mesenchyme-derived mK4 cells because they resemble cells undergoing mesenchymal to epithelial transition , which iIn this study, we show that Runx1 plays an important role in regulating chromatin accessibility at many genomic loci in mK4 cells. In the absence of Runx1, Runx2 bound most of the Runx1-bound chromatin but could not maintain Runx1-dependent accessibility or gene expression. As Runx1 can repress expression of some genes, we anticipated re-expressed genes in Runx1KO cells to be actively repressed by Runx1; however, we were surprised to discover that accessible chromatin near loci expressed only after Runx1 deletion were depleted of Runx sites and instead enriched for Zeb sites, suggesting indirect involvement of Runx1 in their regulation. Further investigation revealed that repression at multiple loci throughout the genome is mediated by two Runx1-dependent targets, Zeb1 and Zeb2. Zeb proteins are sufficient for repression since restoring Zeb2-expression in Runx1KO cells repressed ectopically expressed genes in Runx1KO cells. We demonstrated that Zeb repressors were required for repression in the presence of Runx1 by inactivating Zeb1 and Zeb2 in parental mK4 cells, which phenocopied the gained accessibility and expression seen in Runx1 knockout. Thus, the direct impact of Runx1 on chromatin in mK4 cells is mediated primarily through its ability to promote and maintain chromatin accessibility and transcriptional activator function, rather than through its repressor function. Collectively, these data provide mechanistic insight into how Runx and Zeb TFs interactively control gene expression and place Runx1 at a top of a TF cascade maintaining the global chromatin landscape.To generate cells lacking Runx1 activity, we targeted Runx1 with two gRNAs flanking exon 3, which contains the start codon of the transcript expressed in mK4 cells and encodes part of the Runt DNA binding domain . MultiplTo determine the impact of Runx1-deficiency, we performed multiple genomic assays comparing Runx1KO to parental mK4 cells. Specifically, we analyzed gene expression through RNA-seq, identified genomic locations bound by Runx1 and Runx2 through ChIP-seq, and mapped chromatin architecture by ATAC-seq . The RNA−07, FDR 2.3 10−04, Tables RNA-seq analysis identified 1,599 upregulated and 1,041 down-regulated transcripts that were significantly altered across highly consistent replicates in Runx1KO cells relative to control cells . Consist−1298)  . These d−58). In contrast, only 34% (545/1599) of upregulated genes had a nearby immunoprecipitated peak (a 1.41 fold enrichment). While the limited overlap of Runx1 ChIP peaks near upregulated genes cannot exclude the possibility that some of these may represent sites of Runx1 mediated repression, the results are consistent with the loss of expression in Runx1KO cells of direct Runx1 targets and less consistent with a model in which upregulated genes were repressed directly by Runx1.To further determine whether these Runx1 bound regions were involved in transcriptional regulation, we assigned genes to the Runx1 ChIP peaks using the GREAT annotation tool  and comp−2244 and 1 x 10−2363, respectively . Comparectively , and S2AThe Runx2 ChIP data indicated that most regulatory regions remained accessible to Runx2 binding in Runx1KO cells . To exam−1601), further implicating Runx1-dependent ATAC-seq regions as enhancers (−388) and as expected, the dataset had highly significant overlap with our Runx1 ChIP data , consistent with a role for Runx1 in promoting and maintaining open chromatin in these cells, but not with Runx1 maintaining repression. Since enrichment analysis found significant enrichment for our mK4 Runx1 ChIP sites in AML  and HPC-7 cells , as expected from Runx1-dependent maintenance of enhancers regulating expression of nearby genes.These changes in chromatin accessibility could reflect Runx1 functioning as an activator at some loci  and a repressor at others . If Runx1 is directly acting as both an activator and a repressor in this manner, then both classes would be expected to be enriched for Runx1 motifs. To test this hypothesis, we repeated the analyses described above and again found strong enrichment for AP-1 motifs  for proximal genes whose expression decreases in Runx1KO cells  and near sites not immunoprecipitated by Runx2 in Runx1KO cells . Collectively, the Runx1 and Runx2 ChIP data and subsequent enrichment analyses indicate that Runx1 binds to and promotes or maintains chromatin accessibility at a large number of loci, many of which are associated with Runx1-responsive genes. Despite remaining bound to these same regions in the absence of Runx1, Runx2 is unable to compensate for the lack of Runx1.Other Runx1-dependent regions display greatly reduced Runx2 binding. For example, two potential enhancers near get gene , are opeOur analyses above suggest that while Runx1KO-induced ATAC-seq regions require Runx1 to remain inaccessible, the lack of Runx1 binding to these regions is consistent with indirect repression by Runx1. To explore the possibility that particular Runx1-dependent protein(s) are maintaining repression, we performed TF binding motif enrichment analysis at these sites. Indeed, Runx motifs were absent from the top 1,500 enriched motifs , consistPard6b, that was upregulated in Runx1KO cells nearly 10-fold based on RNA-seq analysis  We are sorry that we cannot be more positive about your manuscript at this stage. Please do not hesitate to contact us if you have any concerns or questions.Yours sincerely,John M. Greally, D.Med., Ph.D.Section Editor: EpigeneticsPLOS GeneticsGregory BarshEditor-in-ChiefPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: The manuscript reports the contribution of the Runx1 transcription factor to chromatin organization that is functionally linked to control of gene expression. Utilizing CRISPR-ablation of Runx1, the consequences for chromatin accessibility, evaluated by ATAC seq, was examined and related to gene expression that was assessed by RNA-seq. The observed modifications in gene expression are consistent with well-established parameters of biological control and pathology that have been reported for Runx transcription factors. The influence on the Runx1 mediated genomic/epigenomic landscape was directly addressed by Chip seq. The shared and unique activities of Runx1 and Runx2 were examined with insight into Runx control of proximal and distal genomic regulatory domains. The influence of Runx1 on Zeb1 and Zeb2 expression, within the context of chromatin accessibility was reinforced by overexpression experiments. And, while somewhat un-physiological, these experiments provided insight into regulatory cascades that are linked to Runx regulation of the genomic landscape. The experimental approaches were straightforward and findings were appropriately discussed in relation to results in the literature, particularly those secured from studies on Runx1 control in mammary epithelial and breast cancer cells. The reported findings are a valuable contribution to advancing understanding of Runx1 control of the chromatin landscape and competency for gene expression. The results provide a blueprint for mechanistically exploring Runx regulation of epigenetic control and chromatin organization that supports transcriptional competency.Reviewer #2: The transcription factor RUNX1 plays important roles in regulating gene expression in many cell types, including hematopoietic, skin, and bone cells. It appears to have positive effects on some genes and repressive effects on other. This manuscript delves more deeply into positive and negative roles of RUNX1 in the mouse kidney cell line mK4, which is derived from metanephric mesenchymal cells. This cell line can be considered an informative model for cells undergoing the mesenchymal to epithelial transition, a process important in development of the kidney. The role of RUNX1 in kidney development has not been extensively studied. The authors generated a RUNX1 knockout (KO) subline of mK4 cells, and determined the impact of RUNX1 loss on the transcriptomes by RNA-seq, the genome-wide binding profiles for RUNX1 and RUNX2 by ChIP-seq, and chromatin accessibility by ATAC-seq. All these determinations were in triplicate to allow stringent determinations of changes. The results show that primary role of RUNX1 in this kidney cell context is that of a transcriptional activator. Most of the genes whose gene expression is positively regulated by RUNX1 (down-regulated in the KO) have, within a reasonable vicinity, plausible candidate enhancers bound by RUNX1. In contrast, most of the genes whose expression is negatively regulated by RUNX1 (up-regulated in the KO) do not appear to be direct targets of RUNX1. Instead, studies of motif enrichment and further biochemical examination reveal a role for ZEB1 and ZEB2 as repressors. The authors conclude that the role of RUNX1 is to activate expression of the repressor proteins, thereby leading to gene repression by an indirect mechanism. These experiments and analyses lead to important new insights into the mechanisms of regulation by RUNX1. The authors also provide some discussion about the possible application of these insights into RUNX1 and ZEB1 and 2 function in other cellular contexts.The experiments are performed carefully and with a good replication structure. The analyses are appropriate and rigorous. The text is clear for the most part but it could be more concise.The manuscript could be improved by addressing the following specific points.(1) The results of the triplicate determinations are shown for RNA-seq in Fig. 2, but the patterns across replicates are only shown in the heatmaps of signal density in peaks in the Supplement. Showing at least some of the differentially bound or accessible regions  for all three determinations would provide compelling examples of consistency in the data. Such a figure panel would be a strong addition to the Supplementary figures.(2) The authors should state that mK4 cell line is from mouse early in the paper; the first I read of mouse as the species of origin was in the Discussion.(3) Some important labels are obscured in "Figure 2-Supplemental Figure 1", e.g. which panels for for RUNX1 ChIP-seq and which are for RUNX2?(4) What is the x-axis in Fig. 2C and 3C and in "Figure 2-Supplemental Figure 1B"? The label says transcription factor binding motif, but there are multiple values for each of the motifs in the color key. Are there many motifs in the RUNX class, in the AP1 class, etc?(5) Lines 203-205: The conclusion drawn about direct repression is overly broad. The results presented do not make a case for one conclusion that applies to all repressed genes. Just using the numbers in the preceding sentence, it seems that the data DO support a model for a direct role of RUNX1 in repression of about 30% of the genes whose expression is up-regulated in the Runx1 KO. Of course, that leaves a majority of the upregulated genes as not consistent with a direct role of RUNX1, and that would be an appropriate way to describe the conclusion.(6) In Fig. 2B, are the genomic regions with the RUNX2 ChIP-seq signal the same ones and in the same order as those shown for the RUNX1 ChIP-seq signals? Or are they for the peaks of RUNX2 binding, ordered by the strength of RUNX2 signal? These heatmaps indicate a substantial overlap in binding between RUNX1 and RUNX2, but the Venn diagram in Fig. 2D indicates that roughly half the peaks overlap. These panels need to be reconciled.(7) The observations on lines 257-258 should be expanded. What fraction of the RUNX1-dependent ATAC-seq peaks are also bound by RUNX1? Is it a high majority? More information is presented later, but the relevant supplemental figure panels are missing, and no explicit answer is given to this question.(8) "Figure 3-Supplemental Figure 1" appears to be missing panels A, B, and C.(9) For GSEA , the gene sets examined need to be stated in the text or figure legend and labeled in the Figure. What is blue and what is red along the x-axis?(10) line 280: What exactly is being referred to by the term "pioneer/activator function"? The concept of a pioneer function has evolved, and in some contexts it refers to an activity that opens previously inaccessible chromatin. Is that what is meant, and if so, how is that involved in maintenance of accessibility?(11) lines 288-290: What aspect of the data in Fig. 3E show a "slightly decreased" RUNX2 ChIP signal at the RUNX1-dependent ATAC-seq sites in Runx1KO cells? The heat maps look the same for + and - RUNX1. The specific examples are pretty clear in panel F, but the overall pattern in panel E does not show a clear decrease.(12) line 395: need to add "those encoding" before "several other transcription factors".(13) lines 411-412: What data in this paper support the conclusion that RUNX1 appears to "act by making chromatin accessible to other TFs"? In order to see such an effect, one might expect an analysis of DNA sites that were previously in inaccessible chromatin, but which become accessible upon introduction of RUNX1. It is not clear how a knock-out experiment shows an effect on initiation of chromatin opening. The loss of accessibility upon RUNX1 knock out supports a role in maintaining accessibility, as the authors point out in other text.Reviewer #3: The article by Hass et al. describes how knocking out RUNX1 in a kidney derived cell line leads to changes in chromatin organisation and gene expression even at genes that are also bound by RUNX2. They also demonstrate that lost accessible sites are enriched in AP-1 motif. In addition, they show that genes which are down-regulated are direct Runx1 targets but genes which are up-regulated are not. They propose that the up-regulation of such genes is caused by the down-regulation of ZEB repressor proteins as sites associated with such genes are enriched in ZEB motifs..The data is of good quality and the results are interesting and if taken further, could expand upon known functions of RUNX1 in a novel cellular context.However, I am afraid that this study is not developed far enough to support the conclusion put forward by the authors, this holds true in particular for the proposed role of ZEB proteins.Major Comments1. Loading controls (such as Gapdh or B-actin) must be shown for western blots in Figure 1, Figure 4 and Supplementary Figure 1.2. Lines 183-185 and 252-255 presence of an AP-1 motif alone is not sufficient to describe these cis-regulatory regions as enhancers. Along the same vein: The loss of AP-1 motifs does not mean that this factor is binding there. To ensure that RUNX1 is required for AP-1 binding, ChIP data need to be provided3. The fact that some down-regulated genes cannot be rescued by the presence of RUNX2 is very interesting, but again, the mechanistic basis of this finding is unclear. How does histone modification look like at these regions? Could chimeras between RUNX1 and RUNX2 be used to examine which domain of RUNX1 is required for the activation of these genes?4. Figure 2/Supplementary Figure 2 the Venn diagram in panel D shows around a quarter of Runx2 peaks are each gained and lost following Runx1 KO. The authors mention that replicates were well correlated but this is not easy to confirm with the heatmaps shown. Here either a correlation matrix should be provided or a similar Venn diagram of peak numbers to see if the changes in response to Runx1 KO are more than expected by chance/technical variation.5. It is puzzling to see that RUNX2 binding can be associated with inaccessible chromatin - how many of its peaks lie within open chromatin  and what distinguishes these from the inaccessible sites?6. Results/discussion: Lines 203-205, Figure 4. A central claim to the article is that RUNX1 is not acting as a repressor via Zeb proteins. However, the data does not support this claim. 30% of upregulated genes having a nearby RUNX1 peak still seems high even compared to the 45% of downregulated genes although a p-value is only given for downregulated genes - is this because it is also higher than expected by chance? In the absence of Hi-C data, how do they know which binding site belongs to which gene. It is known that only about 50% of all ChIP sites belong to the nearest promoter – which will create a problem with the statistical significance.7. In the follow up experiments binding at these genes by Zeb1/2 is not documented by ChIP so there is no direct evidence that these proteins are acting as the repressors at these sites. The authors make a point that there is no antibody available, but they work with a cell line into which tagged ZEB proteins could be introduced and expressed in an inducible fashion, which would nail the issue.8. Could RUNX1 and ZEB proteins be acting in a complex and therefore Runx1 binding is indirect given the lack of RUNX motifs? Is the t-test in Fig4 panels G & I vs the Runx1KO? If so this needs to be done against the control too to confirm if there is a full rescue - there does not appear to be, further suggesting it is not ZEB proteins alone.9. The discussion is way too long and too speculative for the limited evidence provided.Minor Comments1. Introduction: It would be helpful to describe the differences between Runx1 and Runx2 so the different behaviours discussed later can be better understood.2. Methods: Some detail is missing from the methods section making the study difficult to interpret and impossible to replicate. There is no information on RNA-seq analysis past alignment - how were differential genes called? Primer sequences and antibodies used are not provided. Data has been aligned to mm9, unless there is a good reason for this mm10 (released 2011) should be used.3. The authors mentioning the “pioneering” function of RUNX1. However, this idea is way too simplistic. The review they cite does not show such a thing. RUNX1 when expressed can cause the opening of chromatin, but it may need other factors to do this. The authors are advised to read one of Ken Zaret’s reviews for a correct definition of pioneer factors4. Supplementary Figure 3 panels A-C are missing.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: None**********what does this mean?). 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Greally, D.Med., Ph.D.Section Editor: EpigeneticsPLOS GeneticsGregory BarshEditor-in-ChiefPLOS Geneticswww.plosgenetics.orgTwitter: @PLOSGenetics----------------------------------------------------Comments from the reviewers (if applicable):Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: Adequate response to concerns in the initial review have been made. No remaining reservations with the manuscript.Reviewer #2: The authors have thoroughly addressed the issues raised in the first round of reviews. They have also conducted additional experiments, such as knockouts of the Zeb1 and Zeb2 genes to further develop the story about these targets of RUNX1 serving as repressors of downstream genes.I noticed one passage that the authors may want to clarify:Line 267: I think that "in the Runx1-dependent sites" should be added after "motifs" to clarify the class of ATAC-seq peaks being described (unless the observed enrichment was observed in both classes).**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: Yes**********what does this mean?). 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PLOS Genetics may also choose to issue a press release for your article. If there's anything the journal should know or you'd like more information, please get in touch via  7 Jun 2021PGENETICS-D-20-01576R1 Runx1 Shapes the Chromatin Landscape Via a Cascade of Direct and Indirect Targets Dear Dr Kopan, We are pleased to inform you that your manuscript entitled "Runx1 Shapes the Chromatin Landscape Via a Cascade of Direct and Indirect Targets" has been formally accepted for publication in PLOS Genetics! Your manuscript is now with our production department and you will be notified of the publication date in due course.The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any errors. 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Enhancers are DNA sequences at a long genomic distance from target genes. Recent experiments suggest that enhancers are anchored to the surfaces of condensates of transcription machinery and that the loop extrusion process enhances the transcription level of their target genes. Here, we theoretically study the polymer dynamics driven by the loop extrusion of the linker DNA between an enhancer and the promoter of its target gene to calculate the contact probability of the promoter to the transcription machinery in the condensate. Our theory predicts that when the loop extrusion process is active, the contact probability increases with increasing linker DNA length. This finding reflects the fact that the relaxation time, with which the promoter stays in proximity to the surface of the transcriptional condensate, increases as the length of the linker DNA increases. This contrasts the equilibrium case for which the contact probability between the promoter and the transcription machineries is smaller for longer linker DNA lengths. Enhancers are short regulatory DNA sequences that activate the transcription of target genes. Enhancers are located a long genomic distance (in the order of 10k–1 Mbps) away from target gene promoters and the linker genome thus has to form loops to drive the interactions between enhancers and gene promoters. Mediator complexes that bind to enhancers recruit RNA polymerase II (Pol II) to promoters ,3.Xenopus cohesin in recent single molecule experiments  , which aeriments ,20. It iRao and coworkers used auxin-inducible degron technique, which degrades cohesin in response to a dose of auxin, to eliminate chromatin loops . They shWe have therefore theoretically analyzed the dynamics of chromatin, which is extruded by cohesin, at the surface of a transcriptional condensate ,30. FirsLarge transcriptional condensates are stable for the experimental time scale (with which mouse embryonic stem cells are differentiated), whereas the lifetime of small transcriptional condensates is in the order of 10 s . For simN0 chain units, Kuhn units, and the promoter is composed of Ns units, where the length of each unit, the Kuhn length, is b for both the linker and the promoter . For simplicity, we treat cases in which the number of units in the promoter is smaller than the number of units in the linker chromatin, Ns ≪ N0. We also neglect the unbinding of enhancers from the condensate.We consider a linker chromatin between a promoter and an enhancer, which is part of a super-enhancer associated to the surface of a transcriptional condensate, see Figure b is twice the persistence lengths, with which the correlation function of tangent vectors along the chain decays (as predicted by the worm-like chain model) (The Kuhn length n model) . A Kuhn n model) , see refn model)  for a syn model) ,39,40.l2 of the linker chromatin is given by2 in Equation \docum\docum\doEquation ). The lekB is the Boltzmann constant and T is the absolute temperature. For cases in which the loop extrusion does not influence the polymer dynamics, the probability distribution function t) of the position t is derived by the Smoluchowski equationζ0 is the friction constant of each chromatin unit. The first term of Equation (kBT/(N0b2) and the contribution of the effective potential −2kBTlog Following refs.  we treat equation\document equation\document equation\documentCohesin is preferentially loaded at the site, at which NIPBL-MAU2 is localized . Indeed,t = −N0τm) and translocates the linker chromatin from the arm region to the loop region with a constant rate t = 0, see Figure t = 0, the promoter is located at the surface of the condensate, ψ(t asτex ( = N0τm) is the time scale with which a chromatin section of length N0 is extruded. The linker chromatin is relaxed toward equilibrium during 0 < t < t0 . We note here that although the size of the loop continues to increase with time t, the size of the linker chromatin saturates to the equilibrium value leq when the time period t0 is longer than the relaxation time, which is necessary for the linker chromatin to return to the equilibrium conformation  becauset = t0 (t′ = 0). We denote the time elapsed from the loading of the new cohesin as t′. The loading of cohesin may be modeled by the Poisson process of rate t0 = τon to simplify the model, τex < τon; this assumption simplifies the treatment of the loop extrusion process and highlights the roles played by the dynamics of the linker chromatin. The new cohesin produces a new loop region and translocates units in the linker chromatin to this region with a constant rate t0 < t < t0 + τex (0 < t′ < τex), which we call loop extrusion process, see Figure t′ < τex, the number N(t) of chromatin units in the arm region is given byt < t0, is N(t) = N0). The entire linker chromatin is included in the new loop and the system returns to the initial state at t = t0 + τex. Once the entire linker chromatin is included in the new loop, the loop extrusion by the old cohesin  in the local equilibrium has the forml2(t) of the linker chromatin at the local equilibrium has the formThe probability distribution function  the form\documentt) of the position t) of the position During the relaxation process, the time evolution of the probability distribution function  the form\documentEquation  in an exEquation , see the the form\document the form\documentEquation  in an ex the form\document the form\documentt) of promoters that bind to the surface of the transcriptional condensate has the formk0 is the rate constant that accounts for this process. We assume that the promoter binds to the surface of the condensate with a constant rate k0 when it is located at the reaction zone 0 < a due to the finite size of the promoter, see Figure Ψa is the probability with which the promoter is located at the reaction zoneε is the binding energy between the condensate and Pol II bound to the promoter. 〈〉n is the average with respect to the number n of Pol II bound to the promoter  that the promoter is occupied by Pol II in the initiation state has the formρ is the concentration of Pol II in the transcriptional condensate and Kini is the equilibrium constant with respect to the stochastic binding and unbinding dynamics of Pol II to the promoter. λini denotes the rate with which Pol II bound to the promoter becomes the initiation state. λelo is the rate with which Pol II in the initiation state enters the elongation state. For simplicity, we treat cases in which not more than one Pol II can occupy a promoter. We also assume that the difference of Pol II concentration between the interior and exterior of the transcriptional condensate is very large and neglect the transcription by Pol II in the exterior of the transcriptional condensate. We use the probability Pini(t) in the steady state to derive the factor We simplify a transcription model used by Stasevich and coworkers  to deriv the form\documentt) of the position of the promoter. When the promoter is extruded by a cohesin, the promoter is located at the surface of the condensate To understand the chromatin dynamics during the loop extrusion process and during the relaxation process, we first analyze the distribution function r(t) is proportional to the mean square distance between the promoter and the enhancer, 〈2〉 = b2N0r(t), and its form depends on the process, see Equation (S47) in the r(t) in the relaxation process. The relaxation becomes slower as the number N0 of units in the linker chromatin increases, see Figure N0 of units in the linker chromatin, see Figure N0 of units reflects the Rouse dynamics of the linker chromatin  is different from the relaxation process, see Equation (S56) in the Supplementary File. For cases in which the ratio A new cohesin is loaded at the enhancer end of the linker chromatin and a new loop extrusion process starts at time uation S5 in the St0 at which a new cohesin is loaded is larger than the relaxation time t0 is shorter than the relaxation time For cases in which the time τon of cohesin and the relaxation time Our theory therefore predicts that the average loading time Kelo ( = λeloKini/(λelo + λini)) is the effective equilibrium constant. The factor αelo has the formλelo (because the promoter is occupied by pol II in the initiation state most of time) and λelo (because the promoter is not occupied by pol II in the initiation state most of time).The solution of Equation  for the erived as\documentρ of Pol II in the condensate is constant because the number of genes anchored to the condensate is small and the concentration ρ is relaxed to the equilibrium value in a relatively short time. For cases in which the loop extrusion is inhibited, the contact probability σ decreases monotonically as the number N0 of units in the linker chromatin increases, see the cyan line in Figure N0 of units). This is expected from the polymer physics: the linker chromatin acts an entropic spring which anchors the promoter to the surface of the transcription condensate and the stiffness of spring decreases as the number N0 of units in the linker chromatin increases . This is because the loop extrusion process drags the promoter to the surface with a constant rate and the relaxation time N0 of units in the linker chromatin increases, see Equation . The contact probability has an asymptotic form σ = Ψa/(Ψa + αelo) for large concentrations ρ. The asymptotic probability reaches unity only for λelo/λini → 0 because Pol II tethers the promoter to the transcriptional condensate only in the initiation state. Our theory therefore predicts that the concentration of pol II in the condensate and the elongation rate are also important factors that determine the contact probability of the gene promoter to the transcriptional condensate.The contact probability Equation , see Figented as1\documentEquation , and theOur theory predicts the contact probability of a promoter of a gene to the surface of a transcriptional condensate when the gene is anchored to the condensate via a superenhancer. This theory treats a relatively large transcriptional condensate, which is stable for the experimental time scale . TranscrWe used a couple of assumptions to simplify the theory:The binding and unbinding dynamics of the gene promoters to the condensate is rate limited. It is motivated by the fact that among the genes that are at the proximity to a condensate and move together with the condensate, only ndensate . If the ndensate  is in thτon is larger than the time scale τex of the loop extrusion process.Cohesin is trapped at the surface of the condensate. This is probably the case because the loop extrusion starts from the (super)enhancer  and mediThe linker chromatin shows repulsive interactions with the transcriptional condensate. This treatment is motivated by the fact that chromatin tends to be excluded from the transcription condensate .Np = N0τon/τex and N(t) = N0(τon − t)/τex.There are at most one cohesin in the linker chromatin. The cases in which there are multiple cohesin molecules in the linker chromatin are treated by using We treated a relatively large condensate, which is stable for the experimental time scale (with which mouse embryonic stem cells are differentiated) . The lifThe contact probability of a promoter to the condensate is not affected by other gene promoters.We neglected the excluded volume interactions, the hydrodynamic interactions, and the topological interactions between chromatin chains. Indeed, recent experiments on He-La cells  revealedC. elegans. The contributions of the excluded volume interactions, the hydrodynamic interactions, and the topological interactions to the polymer dynamics have been extensively studied  the coupling between the assembly/disassembly of transcriptional condensates and (ii) the transcription dynamics and the interaction between gene promoters by using an extension of our theory.There are growing number of researches on phase separation in biological systems . Many rehttps://doi.org/10.6084/m9.figshare.14102156).The Mathematica file (transcriptiondynamicsVer8.nb) used to derive the data that support the findings of this study are available in figshare with the identifier (gkab275_Supplemental_FileClick here for additional data file.