As an effective and versatile strategy to compartmentalize cellular components without the need for lipid membranes, phase separation has been found to underpin a wide range of intranuclear processes, particularly those involving chromatin. Many of the unique physico-chemical properties of chromatin-based phase condensates are harnessed by the cell to accomplish complex regulatory functions in a spatially and temporally controlled manner. Here, we survey key recent findings on the mechanistic roles of phase separation in regulating the organization and dynamics of chromatin-based molecular processes across length scales, packing states and intranuclear functions, with a particular emphasis on quantitative characterizations of these condensates enabled by advanced imaging-based approaches. By illuminating the complex interplay between chromatin and various chromatin-interacting molecular species mediated by phase separation, this review sheds light on an emerging multi-scale, multi-modal and multi-faceted landscape that hierarchically regulates the genome within the highly crowded and dynamic nuclear space. Moreover, deficiencies in existing studies also highlight the need for mechanism-specific criteria and multi-parametric approaches for the characterization of chromatin-based phase separation using complementary techniques and call for greater efforts to correlate the quantitative features of these condensates with their functional consequences in close-to-native cellular contexts. Caenorhabditis elegans ,6261,62]In the spatial realm, super-resolution microscopy (SRM) has been widely used to characterize the spatial features of chromatin-based phase condensates at resolutions an order of magnitude below those afforded by conventional imaging techniques . Among the various approaches for breaking the diffraction limit, single-molecule localization-based methods, such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), leverage the labeling of a cellular structure with photoswitchable or photoactivable fluorophores, a sparse subset of which can be randomly activated, individually resolved and localized with nanometer precision. Iterating the process multiple times with a different subset of fluorophores activated each time allows a super-resolution image to be reconstructed from the collective localizations of all fluorophore molecules in the target structure D 76,77,,77,78. AWhile these imaging techniques are by no means specific to probing only intranuclear phase condensates (as opposed to condensates at other intracellular locations), they are nevertheless among the most widely adopted methods in previous studies of chromatin-based phase separation and are often used in combination with each other or in conjunction with other complementary approaches (such as in vitro biochemistry measurements of the concentration range associated with phase separation for a particular condensate). The extensive application of these quantitative methods has not only shed light on previously hidden physico-chemical parameters of a variety of chromatin-based phase condensates  and chromobox homolog 2 (CBX2), which recognize histone marks H3K9me3 and H3K27me3, respectively A,B 40,8,85,90. IMoreover, the intrinsic selectivity afforded by the combinations of macromolecular interactions through phase separation serves as a higher-level regulatory mechanism across different types of heterochromatin condensates. For instance, methyl-CpG-binding protein (MeCP2) condensates selectively incorporate HP1α and compete with H1 to form mutually exclusive and distinct heterochromatin foci ,88. DNA Similarly, phase separation has also been implicated in the formation of facultative heterochromatin (marked by H3K27me3). The Polycomb repressive complex 1 (PRC1), which recognizes H3K27me3 marks, can mediate phase separation via its CBX2 and PHC subunits B, with tIn contrast to heterochromatin, the role of phase separation in driving the formation of euchromatin as an intranuclear compartment has been studied less extensively. However, it is known that heterochromatin and active transcriptional condensates (which are mostly found in euchromatic regions) often form distinct phases from each other. Moreover, interactions between heterochromatin, but not between euchromatin, have been found to drive the compartmentalization of whole cell nucleus . In lineGoing further down the length scale, the organization of chromatin into smaller self-interacting TADs has been conventionally understood from a CTCF- and cohesin-mediated DNA loop extrusion mechanism ,137. HowAt the local level, phase condensates can nucleate at regions with either low or high chromatin density and selectively compartmentalize their interacting partners in close proximity to regulate chromatin-based processes, particularly transcription. Super-enhancers (SEs), which consist of a large number of enhancer elements drawn from distinct genomic regions into close proximity, are one of the earliest observed examples of such transcriptional condensates A. Many oIn addition to TFs, various components of the transcriptional machineries can also undergo phase separation to modulate the compartmentalization of chromatin and its interaction partners in the nuclear space. Firstly, RNA polymerase II (Pol II) and MED1 can both form small and transient (~100 nm in size and ~12 s in lifetime), as well as large and stable (>300 nm in size and >100 s in lifetime), clusters. The chromatin-associated stable clusters exhibit properties of phase condensates in which Pol II and MED1 colocalize at SEs that activate gene transcription , in lineAn important functional role served by phase separation-mediated transcription of specific genes is rapid adaptation to extracellular stimuli for cell survival. Indeed, the transcriptional condensates observed in vivo are often short-lived, reflecting the highly dynamic nature of the cell’s responses to various environmental signals. For instance, the transcriptional coactivator YAP forms condensates after redistributing into the nucleus upon hyperosmotic stress and reorganizes the genome into clusters of accessible chromatin regions. Such YAP condensates in turn enrich TFs, such as TEAD1, for downstream transcription of YAP target genes that regulate cell proliferation and survival C 100]. . 100]. ILastly, apart from transcriptional condensates, DNA damage response (DDR), which is critical for maintaining genomic integrity and stability, can also be regulated by phase separation via DNA repair foci where large amounts of double-strand break (DSB) repair proteins interact at DNA damage sites ,152,153.Since its initial demonstrations in biological systems more than a decade ago ,23, phasDespite that, the quantitative parameters reported in the majority of the previous studies were primarily limited to the size, density, lifetime/recovery half-time, diffusion coefficient and in vitro concentration range/phase diagram associated with these phase condensates . While tMoreover, despite the seeming “omnipresence” and “omnipotence” of phase separation, it is also important to exercise caution in not over-interpreting findings that could otherwise be attributed to alternative mechanisms. In particular, merely exhibiting phenomenological characteristics of phase condensates may not automatically mean that phase separation is indeed at work until definitive evidence is obtained. For example, it has been shown that herpes simplex virus replication compartments, while possessing many macroscopic properties of liquid-like condensates, are in fact mediated by a transient DNA-binding mechanism distinct from LLPS . AnotherAnother key deficiency in many of the previous studies of phase separation has been the inadequate effort in linking quantitative characterizations with the functional consequences of phase separation. For example, there has been evidence showing that enzymatic reaction rates can be significantly increased within condensates as compared to the surrounding milieu . This exFinally, the complexity of chromatin-based condensates involving a variety of distinct biomolecular species, as opposed to purely protein-based condensates, also raises concerns as to whether LLPS is still a sufficiently accurate mechanistic model for describing these systems, or if certain modifications are needed to account for the size and structural features of chromatin, as well as the distinct types of interactions involved. For example, the finding that Pol II clusters adopt a variety of shapes in zebrafish is consistent with a model in which regulatory chromatin provides surfaces for liquid condensation at concentrations too low for LLPS to occur and points to an alternative surface condensation mechanism distinct from canonical LLPS . In otheNeedless to say, the list of chromatin-based condensates surveyed here is certainly not exhaustive, and new discoveries are constantly emerging. Growing evidence also demonstrates that dysregulation of phase separation-mediated mechanisms could lead to various ailments, such as neurodegenerative diseases and cancers ,165,166.


Interferon gamma (IFNγ) is a pro-inflammatory cytokine that directly activates the JAK/STAT pathway. However, the temporal dynamics of chromatin remodeling and transcriptional activation initiated by IFNγ have not been systematically profiled in an unbiased manner. Herein, we integrated transcriptomic and epigenomic profiling to characterize the acute epigenetic changes induced by IFNγ stimulation in a murine breast cancer model.cis-regulatory elements bound by Irf1 that were characterized by increased chromatin accessibility, differential usage of pro-inflammatory enhancers, and downstream recruitment of BET proteins and RNA polymerase II. To functionally validate this hierarchical model of IFNγ-driven transcription, we applied selective antagonists of histone acetyltransferases P300/CBP or acetyl-lysine readers of the BET family. This highlighted that histone acetylation is an antecedent event in IFNγ-driven transcription, whereby targeting of P300/CBP acetyltransferase activity but not BET inhibition could curtail the epigenetic remodeling induced by IFNγ through suppression of Irf1 transactivation.We identified de novo activation of These data highlight the ability for epigenetic therapies to reprogram pro-inflammatory gene expression, which may have therapeutic implications for anti-tumor immunity and inflammatory diseases.The online version contains supplementary material available at 10.1186/s13148-022-01316-5. Pro-inflammatory cytokines directly activate signaling cascades, however, epigenetic mechanisms are also critical for coordinated inflammatory gene expression. Interferon gamma (IFNγ) is a pleiotropic cytokine that is a key regulator of anti-tumor immunity , 2. In tIt is now well established that epigenetic therapies may modulate the immunogenicity of tumor cells and inflammatory gene expression in cancer . For exaHerein, unbiased transcriptional and epigenomic profiling was employed to provide mechanistic insight into the hierarchy of events occurring at the chromatin interface following IFNγ stimulation leading to the coordinated transcription of IFNγ target genes. These epigenetic events underpinning IFNγ-induced gene expression were uncoupled by antagonizing distinct nodes using small molecule inhibitors of epigenetic modulators. Taken together, these data illustrate the acute epigenetic remodeling that drives the IFNγ-induced transcriptional response.Cd274 (PD-L1), Irf1, Tap1, and Socs1  in AT3 cells treated acutely with recombinant IFNγ or vehicle control and subsequent differential gene expression analysis (DGEA) revealed that IFNγ stimulation led to a concerted transcriptional response Fig. A involvid274 PD-L, Irf1, TChromatin immunoprecipitation and sequencing (ChIP-seq) for RNA Polymerase II (RNAPII) was performed to assess the processivity across IFNγ-induced genes. IFNγ-stimulated genes were characterized by rapid de novo recruitment of RNAPII following IFNγ treatment with high levels of RNAPII occupancy across the coding region, concurrent with minimal promoter-proximal pausing Fig. E. This icis-regulatory elements following IFNγ-stimulation  was performed. Nucleosomes flanking Irf1-bound sites exhibited greatly increased H3K27ac following IFNγ stimulation  proteins bind acetylated histones and TFs and recruit pTEF-b, thereby stimulating transcriptional elongation , 20. AnaStat1 and Tap1, were impervious to JQ1 co-treatment , which may potentially limit CD8We demonstrated that catalytic P300/CBP KAT activity is required for IRF1 transactivation following IFNγ stimulation. We note this effect could be potentially resultant from (1) P300/CBP suppressing transcription of IRF1 itself, (2) loss of a functional acetylation site on IRF1, (3) P300/CBP inhibitors antagonizing the acetylation-independent allosteric interaction between IRF1 and P300 -STAT1 , anti-STAT1[total] , and anti-α-Tubulin . Membranes were incubated with horse radish peroxidase (HRP)-conjugated secondary antibodies at room temperature for 1 h and washed at least three times in TBS supplemented with 0.1% v/v Tween20. Immunoreactive bands were revealed using ECL reagents  by film exposure  using an Agfa CP1000 developer (Agfa). For both of the cropped immunoblots presented in Fig. 0 nM for p values were calculated using the Survival (v2.38) R package . BrieflSequencing files were demultiplexed using Bcl2fastq (v2.17.1.14) to generate Fastq files on which QC was performed using FASTQC (v0.11.5). Sequencing reads were then aligned to custom reference genome consisting the mouse genome (Mm10) and the Drosophila melanogaster genome (Dm3) using Bowtie2 (v2.3.3). The resulting SAM files were converted to BAM files using Samtools (v1.4.1) using the view command, which were subsequently sorted, indexed, and potential PCR duplicates removed using the rmdup function. BAM files were converted into BigWig files using the bamCoverage function  using the following settings . For experiments with external normalization, the reads mapping to either Mm10 or Dm3 genomes were quantified using FeatureCounts  and the percentage of mapped Dm3 reads as a total of total mapped Dm3 + Hg19 reads was calculated. A scale factor was then calculated as the ratio of Dm3 reads in the control treatment condition and the treatment sample, which was then manually applied as the scaleFactor in the bamCoverage function. BigWig files were imported into Integrative Genomics Viewer  for visualization of specific loci. Using Deeptools (v3.0.0), heatmaps were generated by computing read average read density (from BigWig files) across defined genomic intervals using computeMatrix, which we subsequently plot using the plotHeatmap command. Average profile plots were created using matrices generated by computeMatrix using a custom script in Rstudio. Annotation of putative super-enhancer regions from H3K27ac ChIP-seq data was performed using Ranking Ordering of Super-Enhancer (ROSE) using a 12.5 k.b. stitching distance and a 2.5 k.b. TSS exclusion to reduce promoter bias. Peak calling was performed with MACS2 with default parameters. Annotation of ATAC-Seq/ChIP-Seq peaks to proximal genes was performed using annotatePeaks.pl . Rstudio (v1.1.46) and R (v3.5.1) were used for all additional analyses and figure preparation using the following R packages: ggplots2, rcolorbrewer.https://pypi.org/project/coltron/) was used to perform core regulatory circuit analysis using the following parameters: -g MM10 -l 300. Rose2 and Coltron steps were repeated for both vehicle-treated and IFNγ-treated samples. Rstudio (v1.1.46) was used for figure preparation.MACS2 (v2.2.1) was used for identification of (1) ATAC-seq peaks on BAM files from vehicle-treated and IFNγ-treated cells using the following parameters:—call-summits—nomodel—extsize 300, and (2) H3K27ac peaks on BAM files from vehicle-treated and IFNγ-treated cells using the following parameters:—cutoff-analysis. ATAC-seq and H3K27ac ChIP-seq peaks (.narrowPeak) mapping to ENCODE’s recommended Blacklisted regions  for the RNA-sequencing data of B16-F10 cells stimulated with IFNγ or vehicle control were downloaded from NIH’s Gene Expression Omnibus (GEO) under the accession number GSE134264. RNA-sequencing of MC38 cells stimulated with IFNγ or control was downloaded from GEO (GSE112252). RNA-sequencing of AT3 cells stimulated with IFNγ ± JQ1, or vehicle control, from our previous study was downloaded from GEO (GSE94057). ChIP-sequencing for RNA polymerase II, BRD4, IRF1, and H3K27ac in AT3 cells stimulated with IFNγ ± JQ1, or vehicle control, from our previous study was downloaded from GEO (GSE94130). Next-generation sequencing data generated in this study have been deposited in the NIH’s Gene Expression Omnibus (GEO) under the accession number GSE201883.Additional file 1: Fig S1. Conserved activation of IRF1 in response to IFNγ. (A) RNA-seq of B16-F10 melanoma cells stimulated with IFNγ. (B) RNA-seq of MC38 colon adenocarcinoma cells stimulated with IFNγ. (C) Venn diagram overlap of genes induced by IFNγ stimulation  in AT3, B16-F10, and MC38 cells. (D) Genomic localization of IRF1-bound cis-regulatory elements identified following IFNγ stimulation. (E) De novo motif analysis in ATAC-seq peaks specifically found in IFNγ stimulated AT3 cells using peaks found in vehicle-treated AT3 cells as the background. (F) Clique fraction for highly connected core transcription factors in vehicle-treated cells. (G) Clique fraction for highly connected core transcription factors in IFNγ-treated cells.Additional file 2: Fig S2. BET inhibition with JQ1 depleted BRD4 binding genome-wide. (A) BRD4 ChIP-seq signal  in presence of JQ1 (1 µM) or DMSO for 3 h at cis-regulatory elements active under baseline conditions (in the absence of IFNγ) as identified by ATAC-seq. (B) ATAC-seq signal  at cis-regulatory elements active under baseline conditions (in the absence of IFNγ) as identified by ATAC-seq. (C) Log2 fold-change in BRD4 signal (by ChIP-seq) at active cis-regulatory elements across 10 quantiles ranked by loss of BRD4. (D) Log2 fold-change in ATAC-seq signal at active cis-regulatory elements across 10 quantiles ranked by loss of BRD4. ****p < 0.0001, Mann–Whitney U test.Additional file 3: Fig S3. Catalytic P300/CBP inhibitors perturb cellular transcription. (A) RNA-seq AT3 cells treated for 3 h with A-485 (1 µM) or A-241 (250 nM) relative to DMSO. (B) Venn diagram overlap of differentially expressed genes  following treatment of AT3 cells with A-485 or A-241 relative to DMSO, respectively. (B) Row-normalized heatmap of gene expression values from RNA-seq of AT3 cells treated with A-485, A-241, or DMSO vehicle for genes responsive to A-241 treatment . (D) H3K27ac ChIP-Rx signal  in presence of A-241 or DMSO for 3 h at cis-regulatory elements active under baseline conditions (in the absence of IFNγ) as identified by ATAC-seq. (E) Log2 fold-change in H3K27ac ChIP-Rx at active cis-regulatory elements across 10 quantiles ranked by loss of H3K27ac. (F) Log2 fold-change in ATAC-seq signal at active cis-regulatory elements across 10 quantiles ranked by loss of H3K27ac. ****p < 0.0001, Mann–Whitney U test.Additional file 4: Fig S4. P300/CBP and BET inhibition have disparate effects on steady-state and IFNγ-inducible transcription. (A) Venn diagram overlap of genes down-regulated following 3 h treatment with JQ1 and A-241  in AT3 cells. (B) Row-scaled heatmap of normalized gene expression values for (log2 counts per million) of IFNγ-induced genes following treatment of AT3 cells with IFNγ ± A-241 or A-485, respectively. (C) Normalized counts (log2 counts per million) of Stat1 and Tap1 following IFNγ ± A-241. (D) Normalized counts (log2 counts per million) of IFNγ-induced genes following treatment of AT3 cells with IFNγ ± JQ1 or IFNγ ± A-241. *p < 0.05, ****p < 0.0001 t test.Additional file 5: Fig S5. Uncropped Western blot images. (A) Uncropped Western blot image of data presented in Fig. (B) Uncropped Western blot image of data presented in Fig.


PRPH2, GUCA1A, GUCY2D, CDHR1, ABCA4, and TTLL5) are implicated in the monogenic dominant inheritance of CACD. They are functionally related to photoreceptors . The identified genetic variants do not explain all observed clinical features, calling for further whole-genome and functional studies for this disease. A network analysis with the CACD-related genes identified in the systematic review resulted in the identification of another 20 genes that may influence CACD onset and symptoms. Furthermore, an enrichment analysis allowed the identification of 13 transcription factors and 4 long noncoding RNAs interacting with the products of the previously mentioned genes. If mutated or dysregulated, they may be directly involved in CACD development and related disorders. More than half of the genes identified by bioinformatic tools do not appear in commercial gene panels, calling for more studies about their role in the maintenance of the retina and phototransduction process, as well as for a timely update of these gene panels.Central areolar choroidal dystrophy (CACD) is a rare hereditary disease that mainly affects the macula, resulting in progressive and usually profound visual loss. Being part of congenital retinal dystrophies, it may have an autosomal dominant or recessive inheritance and, until now, has no effective treatment. Given the shortage of genotypic information about the disease, this work systematically reviews the literature for CACD-causing genes. Three independent researchers selected 33 articles after carefully searching and filtering the Scielo, Pubmed, Lilacs, Web of Science, Scopus, and Embase databases. Mutations of six genes ( Systematic Review Registration: website, identifier registration numberCentral areolar choroidal dystrophy  is a rare hereditary disease characterized by a bilateral, symmetrical, well-circumscribed loss of choroidal and retinal tissue , that maFour clinical stages of the disease have been described . In stagCACD may present with autosomal recessive or dominant inheritance; however, autosomal recessive cases are rare . Since tWe followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Three independent investigators carried out the systematic review, using the following Boolean operators in the PubMed, LILACS, SciELO, Web Of Science, Scopus, and Embase databases until 5 May 2021. Although no language restriction was imposed, only literature in English, Spanish or Portuguese was obtained and therefore screened. The search terms were as follows, with syntax adjustments for each database [ AND ]. The records were screened on the online platform Rayyan . ArticleCACD genetic association studies in the literature are scarce, likely due to its rarity. From almost 600 articles reviewed here, only 33 fulfilled all the criteria and truly associated genetic variants to a concise CACD diagnosis. It is crucial to cite here that Albertos-Arranz et al. (2021) (11), re-evaluated patients initially described by Coco-Martins et al. (2020) (12). Cases with phenotypes associated with CACD but not attributed to CACD were excluded to minimize bias.PRPH2) accounts for up to 85% of the mutations cited in the published studies  and Guanylate Cyclase 2D (GUCY2D) variants, make up 90% of the total identified CACD-related variants. Other genes with CACD-associated variants were ABCA4 (ATP Binding Cassette Subfamily A Member 4), CDHR1 (Cadherin-related family member one precursor), and TTLL5 (Tubulin tyrosine ligase like 5).The 33 publications published between 1995 and 2021 are presented in two tables.  studies , 3. PRPHTTLL5 are coexpressed with the following transcriptional regulators: NR2E3 , VSX 2 , ESRRB , RAX2 , NRL , CRX (Cone-Rod Homeobox), ZNF385A (Zinc Finger Protein 385A), and SIX6 (Six Homeobox 6), according to data from the ARCHS4  gene (ONECUT2 (One Cut Homeobox 2), EGR1 (Early Growth Response 1), NRL , and VAX2  seems to affect the expression of the genes found in association with CACD in this review, all based in knockout assays in mouse (MECP2 (Methyl-CpG-Binding Protein 2) was also included in this group but is the unique factor not associated with retinal diseases or eye development, playing a substantial role in early neurodevelopment  gene . Perturbin mouse . MECP2   . At leaspression . Of thospression . The usapression . In our pression  and CCSBpression .g.74267460C > T) of VSX2 was associated with higher susceptibility to ocular sarcoidosis , out of 70778 tests, 13 listed CACD (as MIM # 215500) among the conditions tested; of these, only 8 were NGS panels, with up to 307 genes. Only two of them included all six main genes identified in this review as linked to CACD. Other four panels only missed the TTLL5 gene (The remaining two were in fact offered for other pathologies.) Among the 13 transcription factors identified by our enrichment analysis, all the six valid panels also included CRX, NR2E3, NRL and RAX2; three included VSX2; ESRRB and NEUROD1 were present in one panel each. EGR1, MECP2, ONECUT2, SIX6, VAX2 and ZNF385A were absent. This trend was also present when including all tests in GTR that included at least four out of the six main genes in this review . The latest, unsigned version v2.242 also includes NEUROD1 with borderline evidence (amber list). This absence raises the discussion about possible variants of interest that might be missed with current panels, and reaffirms the need for continuous panel updating, as new works associating different genes with macular diseases are being published.Several other genes were additionally uncovered by gene set enrichment analysis. Polymorphisms of some of them have been associated with macular conditions. The rs149564368  for retinitis pigmentosa), mutations in the same gene could lead to different degrees of disease severity and mutations in different genes may lead to similar phenotypes. A primal example of this is CACD, classified into three different types, based on the causal mutation . In order to better understand these dynamics, family studies are fundamental to evaluate variable expressivity in the phenotype’s severity based on the identification of mutations disturbing gene regulatory networks. Whole genome investigations would be more informative with this regard in the near future, especially in multigenerational affected families. Due to the rareness of these diseases  found in four family members with symptoms of CACD , a transmembrane glycoprotein also named retinal degeneration slow (RDS)  carrying a functional copy of PRPH2 regenerated outer segment structures and corrected electrophysiology (ow (RDS) . Highly sduction . In PRPHtor loss . In Prphysiology .PRPH2 mutations cause the malformation of the outer discs of the retina , another publication revealed a new CACD-causing mutation in the PRPH2 gene (p.Arg203Pro). This mutation was identified in four family members with CACD symptoms (Peripherin interacts with ROM-1 (rod outer segment membrane protein-1) to generate a functional series of rims in photoreceptors, explaining why e retina . Moreovesymptoms . In ordeGUCY2D or RetGC-1) is encoded by the guanylate cyclase 2D gene , located on chromosome 17p13.1. GUCY2D is responsible for the synthesis of cyclic guanosine monophosphate (cGMP) from guanosine triphosphate (GTP), which mediates the recovery of the dark state of photoreceptors following the transduction of a visual stimulus  is a gene located on chromosome 6p21.1 that encodes guanylyl cyclase-activating protein 1 (GUCA1A or GCAP1), a retinal protein highly expressed in the inner/outer segments of cones and rods  concentration during photoreceptor excitation and recovery from light  at high Ca2+ concentrations. This obstruction dysregulates intracellular Ca2+ and cGMP levels in photoreceptors, leading to cell degeneration and consequent loss of rod and cone response to light (GUCA1A gain-of-function mutation (p.Arg120Leu) kept GUCY2D in its activated state, causing abnormally high Ca2+ concentrations, which led to photoreceptor malfunction and eventually, maculopathy. In a zebrafish model, the mutation was proven to affect the retina and cause atrophy of the ocular vessels  encodes a protocadherin that belongs to the cadherin superfamily of homophilic cell-adhesion proteins  in mRNA processing, which leads to the loss of 48 residues from the protein’s ectodomain and consequently, loss of adhesion in cone and rod cells and a severe loss of retinal function (Patients with different truncating function .ABCA4 (MIM: 601691) gene encodes for a protein belonging to the member 4 of subfamily A of ATP-binding cassette of, and is actively involved in transporting various elements across the cell membranes  was associated with “refractive error linked to macular disorders”  gene is found on the long arm of chromosome 14. It encodes minuscule six protein-coding isoforms, including a glucocorticoid receptor that belongs to the tubulin family. This protein interacts with transcriptional intermediary factor 2 (TIF2) and steroid receptor coactivator 1 (SRC1), modulating the induction or repression of glucocorticoids  gene exhibit no tubulin glutamylation (addition of glutamate molecules). TTLL5 pathogenic mutations even lead to the absence of glutamylation on RPGR, compromising its function and leading to a retinal degeneration phenotype. The study also rules out the possibility that other tubulin family members like TTLL6 or TTLL7 could glutamylate RPGR, compensating for the loss of TTLL5. Mutations in these two genes could also affect humans, causing blindness and photoreceptor degeneration, like retinitis pigmentosa or cone/cone-rod dystrophies , encodes for a photoreceptor-specific nuclear receptor, also a ligand-dependent transcription factor. It plays a crucial role for photoreceptor development and differentiation, being preferentially expressed in rods, and acting in company with neural retina leucine zipper (NRL), and nuclear receptor subfamily 1, group D, member 1 (NR1D1), and cone-rod homeobox-containing gene (CRX) genes and other transcription factors in rod differentiation , encodes a homeobox regulatory protein responsible for the development and maintenance of the neuroretina. It is expressed abundantly in the inner nuclear layer of the retina   of this gene. The disruption of this motif interferes with DNA binding and gene repression, leading to a recessive phenotype with a group of associated ocular abnormalities. This was shown in different species, suggesting that this gene is evolutionarily conserved  , suggestonserved .PRPH2 expression and other transcription factors binding the 5′ flanking region of PRPH2 like OTX, NR2E3, Myocyte-Specific Enhancer Factor 2C (MEF2C), and also Retinoid X receptor family members  encodes an estrogen receptor-like transcription factor of road-specific genes. It most likely mediates  members . ESRRB a defects .RAX2 mutations may alter its affinity with CRX, disturbing normal transcription regulation  encodes for retina and anterior neural fold homeobox regulatory protein, whose variants may cause macular thickness. RAX2 interacts physically with CRX, recruiting other components of the basal machinery to allow transcription in both inner and outer layers of the retina. gulation . RAX2 an mammals .NRL  is a transcription factor expressed specifically in rod photoreceptors and the pineal gland, interacting with CRX, NR2E3, and other transcription factors required for retinal development rod photoreceptor differentiation  rod cells rescued retinal degeneration phenotypes. NRL negative rod cells started presenting cone features with subsequent improved survival rates and thus, without secondary cone degeneration in mice retina. It is possible that the ablation of this gene in germinative embryonal cells or adult rod cells presents different long-term consequences, due to specificities on gene regulatory networks of each cell type. Whereas germline mutations cause retinal degeneration, mutations in mature rod cells disturb a synergistic network of different gene products, with derepression of cone genes  encodes for a protein highly expressed in the retina and plays a role in photoreceptor cell development and maturity . While teceptors . CRX seeeceptors . Rescue proteins .RZF, is one of the various zinc finger regulatory proteins that work as a transcription factor , also named n factor . This fan factor . ZNF385Achanisms .Drosophila. This protein seems to work with the ventral anterior homeobox (VAX1) , homologous of sine oculis homeobox protein in x (VAX1)  transcrix (VAX1) . Therefox (VAX1) . SIX6 isrphology . Variantrphology . A studyrphology .NEUROD1 caused severe photoreceptor deficits in a chicken model. Essentially, the outer nuclear layer of the retina fragmented, with regions presenting few or no photoreceptor cells. It seems that the lack of this transcription factor affected the photoreceptors genesis as well , disrupting the normal function of these cells  encodes a primary helix-loop-helix transcription factor involved in neural and endocrine structures, a critical factor in regulating the regulation of insulin transcription . Repress as well . In micese cells .ONECUT2 or Oc2, located at 18q21.31, MIM *604894) is a transcription factor known for having a single cut domain and a characteristic homeodomain specific for ONECUT class family members  towards developing ganglion cells and horizontal cells (HC) in the retina. It seems that the lack of one or another generates a reduction of HC’s. However, both knockout leads to more profound defects in the development of all early cell types in the retina, also compromising the generation of cones , which controls the attachment of cells, primordial for sclera elongation and normal vision   gene encodes for a transcription factor that regulates the growth of cells like epithelial cells, fibroblasts, and lymphocytes in early stages. It seems to work with laminin (encoded by l vision . EGR1 knm layers . EGR1 in (TGFB1) .MECP2 is responsible for translating sensorial experience into synaptic connectivity, mediated by properly binding in methylated cytosines and provoking chromatin remodeling and promoter-mediated transcriptional regulation. This activity regulates specific genes in different expression levels and implies neuronal plasticity  encodes for a chromatin-associated protein that activates or represses transcription of critical genes for postnatal neuronal development . Mutatioasticity . Knockouturation ., or the distribution of retinoic acid metabolism, contributing to the expression of cone opsins in humans (VAX2 variant (rs3771395) was also associated with astigmatism  is a transcription factor responsible for the morphogenic process responsible for the correct dorsoventral pattern of the eye . Mutation humans . In agreigmatism .LINC02865 encodes two transcripts, LINC02865-201 and LINC02865-202, with 381 bp and 535 bp, respectively. According to the FANTOM5 Project (RHO) and Aryl hydrocarbon receptor-interacting protein-like 1 (AIPL1) genes. Perturbations of its function may cause several phenotypes of retinal disorders in rats, like abnormal retinal cone cell morphology, absent photoreceptor outer segment, absence of retinal rod cells, among many other conditions affecting the eye (listed in the lncHUB database)  . The LINLINC00575 encodes three transcripts with 1,055 bp, 910 bp, and 848 bp. Data retrieved from the lncHUB database  and expressed in the eye and choroid plexus. WWC2-AS1 downregulates miRNA mir16 levels by acting as a competing endogenous RNA, regulating the expression of fibroblast growth factor 2 (FGF2), a protein implicated in corneal vascularization and regeneration of tissues in the retina (WWC2-AS1, miRNA16, and proper regulation of FGF2 could lead to several implications starting from the proper development of tissues in the eye to lesions in the eye caused by melanoma or glaucoma (e retina . This miglaucoma .GUCY2D, recovery of retinal photodegradation photoreceptors in phototransduction pathway in the case of GUCA1A, or the formation and maintenance of specific structures within the photoreceptors, as in the case of PRPH2, TTLL5 and CDHR1. Enrichment analysis was crucial to compile a set of other genetic factors that could also be related to CACD, despite not appearing in the systematic review process. They are not commonly related to CACD or visual diseases and most of them do not appear in commercial gene panels; therefore, more studies about these genes need to be executed, and those panels reviewed in due time.CACD is a rare hereditary disease with dominant inheritance. Candidate genes for this disease encode proteins functionally related to photoreceptors, either in the phototransduction process, as in the case of


Drosophila. Quantitative image analysis reveals that elongation of RNA polymerase II across the internal core region of enhancers leads to suppression of transcriptional bursting from linked genes. Super-resolution imaging and genome-editing analysis further demonstrate that enhancer transcription antagonizes molecular crowding of transcription factors, thereby interrupting the formation of a transcription hub at the gene locus. We also show that a certain class of developmental enhancers are structurally optimized to co-activate gene transcription together with non-coding transcription effectively. We suggest that enhancer function is flexibly tunable through the modulation of hub formation via surrounding non-coding transcription during development.Non-coding transcription at the intergenic regulatory regions is a prevalent feature of metazoan genomes, but its biological function remains uncertain. Here, we devise a live-imaging system that permits simultaneous visualization of gene activity along with intergenic non-coding transcription at single-cell resolution in  Non-coding transcription at the intergenic regulatory regions is a prevalent feature of metazoan genomes, but its function remains uncertain. Here the authors show that enhancer function is flexibly tunable through the modulation of hub formation via surrounding non-coding transcription. Quantitative imaging and single-cell transcriptome analyses revealed that enhancers mainly act to drive successive bursts of de novo RNA synthesis from their target genes4. Recent whole-genome studies reported that non-coding transcription at the intergenic regulatory regions is a pervasive feature of the metazoan genome6. Among these, non-coding enhancer transcription is thought to be a widespread mechanism conserved across species including mammals7, flies9, and worms10, and often used as a hallmark for identifying active enhancers in the genome11. A number of studies reported that the level of enhancer transcription correlates with the activity of nearby genes13, implicating that there is a functional interplay between these two reactions to facilitate gene expression. It has also been reported that transcription start sites (TSSs) present within enhancers can function as a promoter when directly fused with a lacZ reporter gene in Drosophila14, yet its biological function still remains unclear. Whereas a variety of models have been proposed to explain the molecular function of enhancer transcription so far15, most of them stem from bulk and fixed analysis of the heterogeneous population of cultured cells, and studies that directly link non-coding enhancer transcription and gene activity at the single-cell level are scarce. The fact that live visualization of non-coding enhancer transcription in multicellular organisms has been challenging hindered the elucidation of how it impacts temporal dynamics of gene expression during animal development. In addition, it has also been implicated that non-coding transcription at the intergenic regulatory regions can lead to the downregulation of nearby genes21, which is seemingly incompatible with the proposed positive regulatory functions of enhancer transcription. More recently, the whole-genome study reported that in vivo activities of developmental enhancers negatively correlate with the level of non-coding transcription in Drosophila22. To reconcile these contradictory observations, there is a critical need for developing a new experimental framework that enables one to precisely modulate the mode of intergenic non-coding transcription and quantitatively visualize its functional impacts on gene activity in living multicellular organism.Enhancers are a class of regulatory DNAs that control spatial and temporal specificity of gene expression in developmentDrosophila embryos. Quantitative image analysis reveals that induction of transcriptional bursting from linked target genes is dramatically suppressed in the presence of enhancer transcription in cis. Using a variety of genome-engineering and genetic approaches, we provide evidence that transcriptional attenuation takes place specifically when elongating RNA polymerase II (Pol II) transverses the internal core region of enhancers. Super-resolution imaging and genome-editing analysis of key transcription factors Dorsal and Zelda further demonstrate that enhancer transcription counteracts molecular crowding of transcriptional activators to limit the formation of transcription hub at the gene locus. We also show that a certain class of developmental enhancers are structurally optimized to co-activate gene transcription together with non-coding transcription at the same time. We propose that regulatory activities of developmental enhancers are flexibly tunable through the modulation of hub formation via surrounding non-coding transcription during development.Here, we successfully devise an MS2/PP7 live-imaging system that permits simultaneous visualization of gene activity along with intergenic non-coding transcription in developing Drosophila25. First, a sequence cassette containing 24x MS2 repeats was engineered into the 5´ untranslated region (UTR) of the yellow reporter gene  shadow enhancer26 was placed ~7.5 kb downstream of the promoter region, which is similar to the enhancer-promoter distance at the endogenous sna locus. Transcription of the MS2-yellow is dependent on activation cue from linked enhancer since its expression is entirely abolished upon deletion of enhancer sequence from the locus27. For simultaneous visualization of intergenic transcription at the enhancer region, a sequence cassette containing 24x PP7 repeats was fused with the enhancer  29  . Conversely, the burst profile and transcriptional output of the MS2 reporter gene were partially restored in this genomic configuration  motif is enriched around the TSSs of transcribed enhancersted Fig. ; bottom.ion Fig. 5a, b. Ov34. According to this trans-acting model, it is expected that enhancer-derived non-coding transcripts produced from the PP7 allele located on the other homologous chromosome can also impact the expression profile of the MS2 allele lacking intergenic TSS in trans , a homolog of mammalian NF-κB. To directly visualize how enhancer self-transcription impacts the nuclear localization of Dl, we employed CRISPR/Cas9-mediated genome-editing to fuse GFP to the C-terminus of the protein. It was confirmed that the resulting Dl-GFP strain is homozygous viable and fertile. We then monitored endogenous Dl together with the PP7 signal using the Zeiss Airyscan2 super-resolution imaging system . Overall, our results are consistent with the idea that intergenic non-coding transcription modulates enhancer activity by impacting the formation and the function of the transcription hub in developing embryos.Then, how does Pol II elongation across the internal core enhancer region lead to attenuation of transcriptional bursting at the molecular level? Notably, recent cryo-EM studies suggested that elongating Pol II can progressively peel off template DNA from histone surfacesion Fig. . As seenion Fig. , the snatem Fig. . We firstem Fig. ; bottom.48 to quantify read counts for >650 functional enhancers that are reliably assigned to their target genes in fly embryos30, resulting in the identification of highly transcribing enhancers at this developmental stage  and Abdominal-B (Abd-B) represent one of the most actively transcribing enhancers  that is known to be required for Ubx expression at the middle part of embryos  at the Ubx BRE   between the level of non-coding transcription and the enhancer strength32. Importantly, however, a subsequent study by Rennie et al. separately analyzed housekeeping enhancers and developmental enhancers, and found that activities of developmental enhancers negatively correlate with the level of enhancer transcription (ρ = −0.20), while housekeeping enhancers exhibit a positive correlation22. In agreement with this, our analysis estimated that developmental enhancers in early embryos are more prone to contain inward TSS , DSCP-MS2-yellow-sna shadow enhancer-PP7-No TSS (this study), DSCP-MS2-yellow-sna shadow enhancer-PP7-TSS (this study), DSCP-MS2-yellow-sna shadow enhancer-PP7-Inverted TSS (this study), DSCP-MS2-yellow-sna shadow enhancer-PP7-TSSweak (this study), DSCP-MS2-yellow-sna shadow enhancer58, TSS-PP7-sna shadow enhancer (this study), DSCP-MS2-yellow-TSS-PP7-sna shadow enhancer (this study), DSCP-MS2-yellow-sna shadow enhancer-TSS-PP7 (this study), DSCP-MS2-yellow-Ubx BRE-PP7 (this study), DSCP-MS2-yellow-inverted Ubx BRE-PP7 (this study), DSCP-MS2-yellow-inverted Ubx BRE-PP7-TSS (this study), DSCP-MS2-yellow-rho NEE-PP7-No TSS (this study), DSCP-MS2-yellow-rho NEE-PP7-TSS (this study), DSCP-MS2-yellow-rho NEE-TSS-PP7 (this study), DSCP-MS2-yellow-hairy enhancer-PP7 (this study), dorsal-GFP (this study), zelda-GFP (this study), sna-MS2 (this study), rho-MS2 (this study), DSCP-MS2-yellow-2.5 kb spacer-sna shadow enhancer-PP7-No TSS (this study), DSCP-MS2-yellow-2.5 kb spacer-sna shadow enhancer-PP7-TSS (this study), DSCP-MS2-yellow-sna shadow enhancer-TSSinverted-TSS-PP7 (this study), No TSS-PP7-rho NEE-rho-MS2 (this study), TSS-PP7-rho NEE-rho-MS2 (this study).In all experiments, we studied Plasmid construction is detailed in the supplementary information.59. phiC31 was maternally provided using vas-phiC31 strain60. Microinjection was performed as previously described61. In brief, 0–1 h embryos were collected and dechorionated with bleach. Aligned embryos were dried with silica gel for ~8 min and covered with FL-100-1000CS silicone oil (Shin-Etsu Silicone). Subsequently, microinjection was performed using FemtoJet (Eppendorf) and DM IL LED inverted microscope (Leica) equipped with M-152 Micromanipulator (Narishige). The injection mixture typically contains ~900 ng/μl plasmid DNA, 5 mM KCl, 0.1 mM phosphate buffer, pH 6.8. mini-white marker was used for screening.All the reporter plasmids and NLS-mCherry-MCP expressing plasmid were integrated into a unique landing site on the third chromosome using VK00033 strainnanos-Cas9 or nanos-Cas9/CyO strain62. The injection mixture typically contains ~500 ng/μl pCFD3 gRNA expression plasmid and ~800 ng/μl pBS-GFP-3xFLAG-3xP3-dsRed donor plasmid. 3xP3-dsRed was used for screening. Resulting dorsal-GFP flies were crossed with y[1] w[67c23] P{y[+mDint2]=Crey}1b; sna[Sco]/CyO (BDSC #766) to remove 3xP3-dsRed marker from the locus. For MS2-tagging of endogenous snail and rhomboid genes, corresponding pCFD3 gRNA expression plasmid and pBS-MS2-3xP3-dsRed donor plasmid were co-injected using either nanos-Cas9 or nanos-Cas9/CyO strain57. The injection mixture typically contains ~500 ng/μl pCFD3 gRNA expression plasmid and ~500 ng/μl pBS-MS2-3xP3-dsRed donor plasmid. 3xP3-dsRed marker was used for screening. For endogenous rho NEE editing, two pCFD3 gRNA expression plasmids, pBS-Hsp70-Cas9 plasmid (addgene #46294) and pBS-3xP3-GFP-TSS/No TSS-PP7-rho NEE donor plasmid were co-injected to homozygous rho-MS2 embryos. The injection mixture contains ~200 ng/μl pCFD3 gRNA expression plasmids, ~300 ng/μl pBS Cas9 expression plasmid, and ~400 ng/μl donor plasmid. 3xP3-GFP was used for screening. Microinjection was performed as described above.To endogenously label Dorsal and Zelda with GFP, corresponding pCFD3 gRNA expression plasmid and pBS-GFP-3xFLAG-3xP3-dsRed donor plasmid were co-injected using either sna probe was PCR amplified from genomic DNA using primers (5′-CGTAATACGACTCACTATAGGGCAGTTGGCTTAACAGTACTG-3′) and (5′-ACCTGTCACAGCCACCTCAGC-3′). Template DNA for sna shadow enhancer probe was PCR amplified from pbphi-TSS-PP7-sna shadow enhancer plasmid using primers (5′-GCATTGAGGTGTTTTGTTGGTCAAC-3′) and (5′-CGTAATACGACTCACTATAGGGTAAATTCCGATTTTTCTTGT-3′).Antisense RNA probes labeled with digoxigenin  or biotin  were transcribed using in vitro Transcription T7 Kit (Takara). Template DNA for sna shadow enhancer) and biotin (for sna gene) were used. Hybridization was performed at 55 °C overnight in hybridization buffer . Subsequently, embryos were washed with hybridization buffer at 55 °C and incubated with Western Blocking Reagent (Roche) at room temperature for ~2 h. Then, embryos were incubated with 1:1000 dilution of sheep anti-digoxigenin  and mouse anti-biotin  primary antibody at 4 °C overnight, followed by incubation with 1:1000 dilution of Alexa Fluor 555 donkey anti-sheep  and Alexa Fluor 488 donkey anti-mouse  fluorescent secondary antibody at room temperature for ~2 h. Embryos were mounted in ProLong Gold Antifade Mountant (Thermo Fisher Scientific). Imaging was performed on a Zeiss LSM 900 confocal microscope. Plan-Apochromat 20x/0.8 N.A. objective was used. Images were acquired with the following settings: 1024 × 1024 pixels, 16-bit depth, and 15 z-slices separated by 0.5 μm. The maximum projection was obtained for all z-sections, and the resulting image was rotated with the bilinear interpolation method. The brightness of images was linearly adjusted using Fiji.Embryos were dechorionated and fixed in fixation buffer  for ~25 min at room temperature. The aqueous solution layer was removed and ~10 ml 100% methanol was added, and then shaken for ~1 min to devitellinize embryos. Devitellinized embryos were washed with methanol, and then stored in methanol at −30 °C before use. Antisense RNA probes labeled with digoxigenin  for ~45 min at room temperature. The aqueous solution layer was removed and ~10 ml 100% methanol was added, and then shaken for ~1 min to devitellinize embryos. Devitellinized embryos were washed with methanol, and then stored in methanol at −30 °C before use. smiFISH probes targeting the yellow reporter gene were designed using the Biosearch Technologies Stellaris RNA FISH probe designer tool (https://www.biosearchtech.com/support/education/stellaris-rna-fish). The following sequence was added to the 5′ end of each 20 nt probe: 5′-CCTCCTAAGTTTCGAGCTGGACTCAGTG-3′. This is the reverse complement of the X FLAP sequence used in ref. 64. The X FLAP sequence (5′-CACTGAGTCCAGCTCGAAACTTAGGAGG-3′) that contains Cy3 both at the 5′ and 3′ ends was synthesized by Eurofins Genomics. Probes and the X FLAP were annealed, and then stored at −30 °C before use. Hybridization was performed at 37 °C overnight in hybridization buffer . Subsequently, embryos were washed with wash buffer  at 37 °C. After washing and DAPI staining, embryos were mounted in ProLong Gold Antifade Mountant (Thermo Fisher Scientific). Imaging was performed on a Zeiss LSM 900 confocal microscope. Plan-Apochromat 20x/0.8 N.A. objective was used. Images were acquired with the following settings: 1024 × 1024 pixels, 16-bit depth, 25 z-slices separated by 0.6 μm. The maximum projection was obtained for all z-sections, and the resulting image was rotated with the bilinear interpolation method. The brightness of images was linearly adjusted using Fiji. Probe sequences are provided in Supplementary Table Single-molecule inexpensive FISH (smiFISH) was performed as previously describedyellow, 5′-TGGCACTCATCAATGCCGTA-3′ and 5′-CAGACAGCAAGA AAACGGGC-3′; rp49, 5′-TACAGGCCCAAGATCGTGAA-3′ and 5′-TCCAAGAAGCGCAAGGAGA-3′. The expression level of yellow was calculated using the standard curve method. rp49 was used as an internal control.Fly cages were cleared 1 h prior to embryo collection. Then collected 0–1 h embryos were allowed to develop for 2 h at room temperature. Subsequently, nc14 embryos were manually collected under the microscope, and they were homogenized in TRI Reagent (Molecular Research Center) and stored at −80 °C. Total RNA was then extracted according to the manufacturer’s protocol and cDNA was synthesized using PrimeScript Reverse Transcriptase (Takara) and oligo-dT primer. qPCR reaction was carried out using KAPA SYBR Fast qPCR Kit (KAPA Biosystems) and LightCycler 480 System II (Roche). The relative copy number of samples were calculated by LightCycler 480 software (release 1.5.1.62). The following primers were used: 2, 0.5% Triton X-100, 0.5 mM DTT, 1x EDTA-free Protease Inhibitor ). The homogenate was centrifuged at 400×g for 2 min at 4 °C. The supernatants were collected and centrifuged at 15,000×g for 5 min at 4 °C. The pellet was resuspended in buffer A2 ) and sonicated using the Bioruptor Pico . Then, sonicated samples were centrifuged at 15,000×g for 10 min at 4 °C, and supernatants were collected. For pre-blocking, protein G magnetic beads (Invitrogen) were washed three times with . For pre-clearance, the chromatin extract was incubated with protein G magnetic beads for 2 h at 4 °C and supernatant was collected using a magnetic stand. For immunoprecipitation, protein G magnetic beads were preincubated with 1.1 μg of antibodies  in  over 8 h at 4 °C. The chromatin extract was incubated with a pre-mixed magnetic beads-antibody mixture overnight at 4 °C. The beads were washed four times with RIPA buffer  and then once with ice-cold TE50 buffer . Elution buffer  was used to resuspend the beads, and immunoprecipitated samples were eluted by incubating at 65 °C for 40 min. Then, ChIP samples and input samples were reverse crosslinked by incubating at 65 °C overnight. TE buffer  containing RNaseA  was added and incubated at 37 °C for 1 h, and then treated with Protease K  at 55 °C for 2 h. Samples were purified by phenol/chloroform extraction and ethanol precipitation. qPCR was performed as described above. The following primers were used for the analysis: 5′-GGAAAAGCCCACGTCCTACC-3′ and 5′-GCCACCGTACCAAAGCAATC-3′. Enrichment of Dorsal and RNA polymerase II was expressed as the percentage of input chromatin.After pre-laying, 2–3 h embryos were dechorionated and shaken in a mixture of 2 ml of  for 5 min at room temperature. Then, 5 ml of  was added to quench the cross-linking 10 min after the addition of formaldehyde and shaken for 1 min at room temperature. After washing three times with , fixed embryos were flash-frozen in liquid nitrogen and stored at −80 °C. Embryos thawed on the ice were homogenized in buffer A1  and a coverslip (18 mm × 18 mm), and embedded in FL-100-450CS (Shin-Etsu Silicone).For MS2/PP7 two-color live-imaging, virgin females of sna shadow enhancer), 430 × 430 pixels (Ubx BRE), 300 × 512 pixels (rho NEE), or 300 × 350 pixels (hairy enhancer) to remove nuclei outside of the expression domain. One hundred eighty timeframes starting from the entry into nc14 as defined by the progression of prior anaphase were used for subsequent image analysis. The temperature was kept between 22.0 to 23.0 °C during imaging.Embryos were imaged using a Zeiss LSM 900 confocal microscope. Plan-Apochromat 40x/1.4 N.A. oil immersion objective was used. Images were acquired with the following settings: 512 × 512 pixels, 16-bit depth, 18 z-slices separated by 0.6 μm, ~16.8 s/frame time-resolution. The fluorescence of GFP, mCherry, and eBFP2 was excited using 488-, 561-, and 405-nm lasers, respectively. Excitation power was measured and calibrated using X-Cite XR2100/XP750 Optical Power Measurement System (EXCELITAS Technologies) to keep the same experimental setting for each set of experiments. Image acquisition was started before the end of nc13 and ended after the onset of gastrulation at nc14. During imaging, data acquisition was occasionally stopped for a few seconds to correct the z-position. Obtained data were concatenated and cropped into 430 × 512 pixels , 16-bit depth, 41 z-slices separated by 0.2 μm. For the analysis of endogenous Drosophila melanogaster embryos (E-MTAB-4787)48 were used to quantify the level of non-coding transcription at the enhancer regions. Sequenced reads were mapped to the BDGP Drosophila melanogaster genome release 3 (dm3) using HISAT2 (version 2.2.0)65. Samtools (version 1.10) and bedtools (version 2.29.2) were used to convert files to bed format. To exclude TSS signals derived from the coding regions, reads aligned within a window of 50 bp from any exonic sequences were removed using “bedtools intersect” function. The remaining reads were integrated into a single file. Subsequently, to quantify the TSS score on enhancers, “bedtools coverage -counts” function was used to calculate the number of reads on developmental enhancers that were reliably assigned to their target genes in the previous study30. For quantitative comparison of the TSS score, the number of reads was normalized to the size of each enhancer.Publicly available 5´ CAGE-seq data of 2–4 h WT GSM763061)66 were integrated to reliably determine Zelda binding sites in early embryos. Obtained Zelda binding sites were then assigned to overlapping developmental enhancers30 using “bedtools intersect -wa -wb” function. In total, 1062 enhancers that contain Zelda binding sites were obtained and used for further analysis. Subsequently, plus and minus TSS peaks identified by RAMPAGE analysis in Drosophila (GSE36212)67 were assigned to each Zelda binding site within a window of ±500 bp using “bedtools window” function. By integrating these datasets, enhancers with Zelda binding sites adjacent to one or more inward TSS were classified into the “inward TSS” group. Similarly, enhancers with Zelda binding sites adjacent to outward TSS were classified into the “outward TSS” group.Initially, publicly available Zelda ChIP-seq data of nc13 and nc14 (https://fiji.sc), MATLAB , and R (version 4.1.2).All the image processing methods and analysis were implemented in Fiji . They were colored with the pixel intensity proportional to the total output in corresponding nuclei. Burst size was determined by integrating signal intensities during individual bursts using raw trajectory.To obtain the averaged intensity of active PP7 transcription , 5% (Ubx BRE), or 50% (endogenous sna-MS2) of integrated MS2/PP7 signal were pooled from all the analyzed embryos. Then, obtained images were separated into bins based on distance from the center in a pixel increment. To determine the relative enrichment of transcription factors  or Zld-GFP signal at 41 × 41 pixels (~1.4 × 1.4 μm) region centering the brightest MS2/PP7 signal was measured on the same z-plane. As a control, Dl-GFP or Zld-GFP signal centering the random XY coordinate within the segmented region on the same z-plane was measured. To analyze nuclei that reliably contain active MS2/PP7 transcription sites, nuclei with top 15% (ors Fig. a, 14a, DFor quantification of the radial profile of Dl-GFP and Zld-GFP distribution Fig. , 14b, reFurther information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2Supplementary Movie 3Supplementary Movie 4Supplementary Movie 5Supplementary Movie 6Supplementary Movie 7Supplementary Movie 8Reporting Summary


Streptomyces coelicolor A3(2). The RIViT-seq data expands the transcriptional regulatory network in this bacterium, discovering regulatory cascades and crosstalk between sigma factors. Implementation of RIViT-seq with other transcription factors and in other organisms will improve our understanding of transcriptional regulatory networks across biology.Transcriptional regulation is a critical process to ensure expression of genes necessary for growth and survival in diverse environments. Transcription is mediated by multiple transcription factors including activators, repressors and sigma factors. Accurate computational prediction of the regulon of target genes for transcription factors is difficult and experimental identification is laborious and not scalable. Here, we demonstrate regulon identification by in vitro transcription-sequencing (RIViT-seq) that enables systematic identification of regulons of transcription factors by combining an in vitro transcription assay and RNA-sequencing. Using this technology, target genes of 11 sigma factors were identified in  Streptomyces coelicolor A3(2) and successfully identified target genes of 11 of these, expanding the regulatory characterisation in this organism.Here the authors present their method ‘regulon identification by in vitro transcription-sequencing’ (RIViT-seq), which enables systematic identification of target genes of transcription factors of interest. They applied RIViT-seq to 13 sigma factors from  Though all bacteria encode at least one principal sigma factor that is responsible for directing transcription of housekeeping genes, many bacteria encode multiple alternative sigma factors that exhibit varying promoter selectivity and specificity and initiate transcription of different sets of genes linked to specific functions such as stress response and cellular differentiation. In Escherichia coli, a total of 7 sigma factors are encoded in the genome and each of them directs the transcription of genes with specific functions. For example, σ70 is the principal sigma factor and σE controls the expression of genes involved in extracytoplasmic stress response2. While some model organisms including E. coli and Bacillus subtilis encode around 10 sigma factors, several organisms such as soil actinomycetes encode a far greater number of sigma factors. Streptomyces coelicolor A3(2), a soil actinomycete known to produce a wide variety of secondary metabolites, encodes 61 proteins that possess the minimum set of domains required for the sigma factor function that are classified into four subfamilies or groups of the σ70 family  and trascriptomics does not guarantee the identification of their target genes, hindering their systematic characterisation.Transcription is one of the most fundamental steps of gene expression in all living organisms that ensures genes required under given environmental conditions are expressed. Therefore, transcriptional regulation is a crucial system for proliferation, sensing and adapting to the environment, and communicating and cooperating with the surrounding organisms and cells, and any aberrant regulation may lead to undesired consequences, such as disease or cell death. A gene is transcribed to an RNA molecule, or a transcript, by an RNA polymerase enzyme complex. In eukaryotes, three distinct RNA polymerases transcribe different types of genes. In bacteria, however, only one type of RNA polymerase is responsible for transcribing every gene. Bacterial RNA polymerase consists of a core enzyme complex and a sigma factor. A core enzyme is comprised of five subunits and is responsible for RNA synthesis during transcription without preference for DNA sequence. During the transcription initiation process, the dissociable subunit of RNA polymerase, sigma factor, directs RNA polymerase to specific promoters and initiates transcription, conferring promoter selectivity to RNA polymeraseS. coelicolor A3(2), successfully identified at least one target gene for 11 sigma factors, and expanded the transcriptional regulatory network. Applying this technology to other proteins involved in transcriptional regulation such as transcriptional regulators should simplify the identification of their regulons and facilitate expanding transcriptional regulatory networks.In this study, we demonstrate a high throughput technology, regulon identification by in vitro transcription-sequencing (RIViT-seq), which enables systematic characterisation of transcriptional machineries for transcription factors of interest. In this assay, transcriptional machinery, or RNA polymerase, is reconstituted by combining its components such as a core enzyme and a sigma factor and an in vitro transcription assay is performed to transcribe the regulon of the transcription factor. These RNA molecules specifically produced by the reconstituted enzyme complex are identified by RNA-sequencing. We applied RIViT-seq to 13 purified sigma factors encoded in E. coli RNA polymerase core enzyme and the sigma factor of interest, which recognises the sigma factor-specific promoter sequences. E. coli RNA polymerase core enzyme was previously used for in vitro transcription assays with sigma factors from diverse bacteria including streptomycetes14. Notably, one study demonstrated E. coli RNA polymerase core enzyme exhibiting similar activity to the mycobacterial RNA polymerase core enzyme at a mycobacterial promoter11. A mixture of genomic DNA digested by four different restriction enzymes was used as the template DNA of in vitro transcription. The NTP mixture was added to initiate the in vitro transcription reaction. Following the in vitro transcription reaction, the genomic DNA was digested by DNase, ERCC RNA Spike-in Mix was added as normalisation controls and the RNA molecules were purified. To optimise the in vitro transcription reaction conditions, two sigma factors, ShbA and SigR, which are known to initiate transcription at the hrdB and trxB promoters, respectively, were used15. Recombinant ShbA and SigR with a C-terminal hexahistidine tag were overproduced in E. coli, purified and used to determine the optimal concentrations of the RNA polymerase core enzyme, sigma factor and genomic DNA  in vitro transcription assay using a mixture of RNA polymerase core enzyme, purified sigma factor, genomic DNA and NTP mixture; (ii) whole transcriptomics by RNA sequencing; (iii) determination of 5′-ends by 5′-end sequencing Fig. . In the rol Fig.  and the rol Fig. . These fhrdB and trxB transcripts increased by 2.2 and 2.7 times, respectively  using the procedure described in Methods. By integrating these two datasets, a gene was determined a target of the sigma factor if it was upregulated and at least one TSS was identified within 300 nt upstream from its initiation codon. As multiple genes may be transcribed from a single promoter in prokaryotes, an additional gene was considered a target if it was upregulated and located within 50 nucleotides downstream of a direct target gene oriented in the same direction  in the in vitro transcription assay which are required to initiate the transcription of SigR target genes. WblC, a WhiB-family transcriptional activator, promotes transcription from one of the SigR-dependent promoters23. Regardless, additional target genes of SigR, were identified by RIViT-seq, thus expanding the SigR-mediated transcriptional regulatory network. Some target genes had possibly been previously unidentified because negative transcriptional regulation is involved in vivo. Of the SigR regulon identified by RIViT-seq, SCO6404 was most highly expressed. This gene was not previously identified as a SigR target gene. While the function of SCO6404 is unknown, the downstream gene, SCO6405, encodes a DNA recombinase. The known regulon of SigR includes DNA repair proteins to cope with UV- and electrophile-incurred DNA damages19. DNA recombinase encoded by SCO6405 may also be involved in this stress or similar response.We then searched for other genes directly transcribed by ShbA and SigR. Because the RNA polymerase core enzyme is capable of initiating transcription randomly, only genes satisfying both of the following criteria were considered target genes of a sigma factor: (i) genes determined upregulated by whole transcriptomics and (ii) genes of which a proximal TSS is detected by 5′-end sequencing. For criterion (i), fold change of ≥2 and adjusted ion Fig. . Using tbA Table . A totaleB Table 18,19. In18-19-GTT) including the 18 to 19 nucleotides spacer between and –10 and –35 regions19. Overall, RIViT-seq was able to identify genes directly transcribed by the RNA polymerase holoenzyme. In addition, the promoter sequences that the sigma factor recognised were inferred from RIViT-seq when a sufficient number of target genes were found and the promoter sequences were highly conserved.Mapping the 5′-ends of transcripts enabled prediction of the promoter sequences the sigma factors recognise. Because ShbA initiated the transcription from only two promoters, no significantly enriched motifs were found. When the 5′-ends of transcripts generated by SigR were compared, a consensus DNA sequence motif was modelled Fig. . This moS. coelicolor A3(2), additional sigma factors were characterised by RIViT-seq. A total of 59 sigma factors that possess both Sigma70 region 2 and region 4 are encoded on the chromosome of S. coelicolor A3(2)  and S. griseus28.In order to better understand the transcriptional regulatory network in icolor A3, additiosigH transcription . As the activity of these 17 sigma factors may be negatively affected by these extensions, genes encoding truncated versions of these 17 sigma factors were cloned. Of them, 4 truncated sigma factors were successfully purified including three sigma factors of which full-length counterparts were also analysed by RIViT-seq  consisted of 12 sigma factors and 200 genes forming 209 sigma factor-target gene pairs or edges  were regulated by four sigma factors. Of the 18 sigma factors of which regulons are known including the previously identified target genes, SigH and SigI shared the greatest number of target genes in their regulons  activating the expression of bldG and (ii) directly initiating the transcription of some SigH, SigF and SigK regulons including sigJ and wblC 38, RIViT-seq overcomes several limitations ROMA has. Firstly, DNA microarray detects transcripts based on hybridisation between cDNA and probes and it is very difficult to rule out any non-specific hybridisation. Secondly, DNA microarray detects only transcripts that are complementary to probes arrayed on a chip. A high-density DNA microarray is required to detect multiple parts of a transcript and it’s still not sufficient to detect structures of transcripts in a single nucleotide resolution unlike RNA-sequencing. RNA-sequencing enables determining the 5′- and 3′-ends of transcripts by creating sequencing libraries appropriately. Lastly, and presumably most importantly, ROMA requires a DNA microarray for every organism of interest.Transcriptional regulation is a highly controlled process to ensure gene expression only under appropriate environmental conditions, and living organisms use a variety of transcription factors to activate or repress different sets of genes in response to environmental cues. Identifying target genes of a transcription factor is a laborious process, which typically includes transcriptomics analyses using knockout mutants and ChIP-seq, and is not scalable. Even a simple microorganism such as 39. In addition, transcriptional repressors and some nucleoid proteins block access of RNA polymerase to the promoter regions even if sigma factors are active until specific stimuli abrogate the DNA-binding activity of transcriptional repressors and nucleoid proteins. It is often a challenge to predict what kind of stimuli activate the sigma factor of interest and release the transcriptional repressor from its target promoter regions, and whether the activity is controlled by any anti-sigma factor and other transcription factors, which complicates its characterisation in vivo. In addition, indirect effects may exist when characterising a sigma factor and, even more broadly, any protein involved in transcriptional regulation in vivo. By contrast, in vitro transcription assays are a simpler method to characterise any proteins involved in transcriptional regulation. If the transcription factor of interest is predicted to undergo proteolysis, those modified transcription factors may be also characterised. In this study, we used truncated versions of four sigma factors which possess unusual N- or C-terminal extensions and observed the change in the transcription initiation activities. Sigma factor activity is sometimes further controlled by other factors such as RbpA and other types of posttranslational modifications such as acetylation25. The effect of such additional factors and posttranslational modifications may be unambiguously determined by this in vitro-based technology on the genome scale.In this study, RIViT-seq was successfully used to characterise sigma factors, determinants of promoter selectivity of RNA polymerase in bacteria, as a proof of concept. This technology is particularly useful if a transcription factor of interest undergoes negative regulation inside cells. For example, many sigma factors are sequestrated by their cognate anti-sigma factors from RNA polymerase and unable to express their regulons without specific stimuliE. coli. Purifying RNA polymerase core enzyme is tedious work and requires equipment that not all research groups have access to. E. coli RNA polymerase core enzyme, which is commercially available, was successfully used with sigma factors from diverse bacteria including streptomycetes when conducting in vitro transcription assays previously14. There, however, may be cases in which interaction between organism-specific residues of RNA polymerase core enzyme and the sigma factor or promoter sequence is crucial. Hence, it may be desirable to prepare RNA polymerase core enzyme from the organism of choice to minimise potential false negatives when possible. The other possible drawback of the current procedure is the use of digested genomic DNA. The topological state of DNA is known to affect DNA binding of some transcription factors, thus influencing gene expression. Our current procedure of using relaxed DNA may overlook gene expression that requires a specific state of topology. Indeed, elevated chromosome supercoiling caused by topoisomerase I depletion changes global gene expression in S. coelicolor A3(2)40. In certain cases, it may be important or sometimes necessary to use undigested genomic DNA and add topoisomerase or gyrase to the in vitro transcription reaction.There are, nevertheless, a few drawbacks of RIViT-seq and the procedure we used in this study. Most notable one is that all the components should be available for the in vitro transcription assay including the transcription factor and RNA polymerase. Not all the transcription factors are easily overproduced and purified as only 16 sigma factors were successfully purified in this study. The advancement in the in vitro transcription and translation technology and high throughput protein purification technology is expected to improve the success rate of the protein purification and enable the characterisation of a greater number of transcription factors by RIViT-seq. In the current procedure, we used RNA polymerase core enzyme from S. coelicolor A3(2)  encodes 10 sigma factors belonging to the group 3 based on their domain organisations and nine of them including SigH, SigI, SigF and SigK are considered homologues of the general stress response sigma factor, SigB, in B. subtilis . It is still unknown what kind of stimuli directly control the activity of the anti-anti-sigma factors, BldG and ArsI, and how the sigI transcription is controlled. In B. subtilis, nine proteins are known to control the activity of the general stress response sigma factor, SigB43. Similarly, these SigB-like sigma factors in S. coelicolor A3(2) may also be controlled by multiple factors. Further investigation into the regulation of SigH, SigI, SigF and SigK should unveil this complex regulatory network that involves multiple sigma factors.Our data expanded the transcriptional regulatory network in (2) Fig. . StreptoS. coelicolor M145, derivative of S. coelicolor A3(2) lacking the plasmids SCP1 and SCP2, was used to isolate the genomic DNA44. E. coli TOP10 used for DNA cloning and E. coli BL21(DE3) used for protein overproduction were routinely cultivated in LB medium at 30 °C unless otherwise specified. Media were supplemented with kanamycin (25 mg/L) as appropriate.E value of 0.146. Proteins predicted to possess both Pfam domains Sigma70_r2 (region 2) and Sigma70_r4 (region 4) were considered sigma factors. PhyML was used to estimate the phylogeny by maximum likelihood47. MEME was used to find consensus motifs48. Motifs that consisted of 22 to 35 nucleotides and present in at least 10 sequences with the E values < 10–5 were retrieved. The motif with the smallest E value was used as the consensus sequence.Pfam domain search of each predicted protein was performed using hpc_hmmsearch, modified hmmsearch from HMMER3 for efficient use of CPU cores on the Cori supercomputer, with a threshold of independent NdeI and XhoI.Sigma factor genes were amplified by PCR using KOD Hot Start DNA Polymerase (MilliporeSigma) and primer pairs listed in Supplementary Table E. coli possessing the pET29b(+)-derived plasmid was cultivated in 2 ml LB medium containing 25 µg/ml kanamycin overnight at 30 °C. To a fresh 50 ml LB medium containing 25 µg/ml kanamycin, 1 ml of the preculture was inoculated. The cells were grown at 30 °C for 2 h and the temperature was changed to 15 °C. IPTG was added to the final concentration of 0.1 mM for SCO5243 or 1 mM for all other sigma factors and the cultivation was continued overnight. Cells were harvested by centrifugation and stored at –80 °C until the use. Cell pellets were resuspended in a buffer containing 20 mM HEPES (pH 7.5), 50 mM sodium chloride, >0.25 units/µl Benzonase Nuclease (MilliporeSigma), 1 mM magnesium sulphate and 1 × BugBuster (MilliporeSigma), and lysed for 30 min at room temperature with continuous agitation. Insoluble materials were removed by centrifugation and imidazole was added to the soluble fraction at 20 mM. The soluble fraction was mixed with HisPur Cobalt (Thermo Scientific) and incubated for 2 h with continuous agitation. The unbound materials were removed and the resin was washed with a buffer containing 20 mM HEPES (pH 7.5), 50 mM sodium chloride and 30 mM imidazole. The bound protein was eluted with a buffer containing 20 mM HEPES (pH 7.5), 50 mM sodium chloride and 150 mM imidazole. Imidazole was removed by using Microcon-10kDa Centrifugal Filter Unite (MilliporeSigma). The protein concentration was measured using Bio-Rad Protein Assay with BSA as the titration standard (Bio-Rad).S. coelicolor A3(2) was isolated by using GenElute Bacterial Genomic DNA kit (MilliporeSigma) and digested by EcoRI, HindIII, BamHI or XhoI. Equal quantities of the genomic DNA solutions treated by different restriction enzymes were combined. In vitro transcription assays were performed using Echo® 525 LIQUID HANDLER (Labcyte). Two µl of 8 µM sigma factor, 1 µl of one unit/µl E. coli RNA polymerase core enzyme (New England BioLabs) and 2 µl of 5X E. coli RNA polymerase reaction buffer were mixed and incubated at 30 °C for 15 min. To this mixture, 1 µl of 200 ng/µl digested genomic DNA mixture was added and the mixture was incubated at 30 °C for 15 min. The in vitro transcription reaction was initiated by adding 2 µl of 2.5 mM NTP mixture (Invitrogen) and the mixture was incubated at 30 °C for 20 min. To the reaction was the DNase solution consisting of 2 µl TURBO DNase , 1.5 µl of 10X TURBO DNase buffer and 1 µl of ERCC RNA Spike-in Mix (Invitrogen) diluted by 100 times added. The reaction was incubated at 37 °C for 30 min and the RNAs were purified using RNeasy kit (Qiagen). RNA concentrations were quantified using Qubit™ RNA HS Assay Kit (Invitrogen). The cDNA synthesis was performed using the SuperScript IV First-Strand Synthesis System (Invitrogen) and the quantitative RT-PCR was performed using SsoAdvanced Universal SYBR Green Supermix (Bio-Rad Laboratories) and primer pairs listed in Supplementary Table The genomic DNA of Stranded cDNA libraries were generated using TruSeq Stranded RNA Library Prep Kit (Illumina) and the low sample protocol. Libraries were quantified using KAPA Library Quantification Kit (Roche) and LightCycler 480 Instrument (Roche), and sequenced on NovaSeq 6000 Sequencing System (Illumina) by paired-end 2 × 150 bp sequencing.S. coelicolor A3(2) chromosome and ERCC92 sequences using HISAT2 with the “no-spliced-alignment” option and the “maxins” option of 1,00049. The number of fragments overlapping each gene was counted using featureCounts50. Fragment counts were normalised by ERCC fragment counts using the R package RUVSeq and differential expression was analysed using the R package DESeq252. The fold change of ≥2 and the adjusted P value of <0.01 were used to determine the significantly overexpressed genes.Raw reads were scanned from 3′ to 5′ and those with a quality score value below 20 were trimmed and reads consisting of fewer than 35 nucleotides were discarded using BBDuk (sourceforge.net/projects/bbmap/). Trimmed reads were aligned to the The triphosphates at the 5′-end of 6 µg RNA samples were converted to monophosphates by using 3.75 units of RNA 5′ pyrophosphohydrolase  at 30 °C for 1 h. The 5′-ends of the transcripts were ligated by the adaptor (GUUCAGAGUUCUACAGUCCGACGAUC) using 15 units of T4 RNA ligase 1  at 25 °C for 2 h followed by incubation at 17 °C for 18 h. Ligated RNA samples were purified by using RNeasy Kits and RNeasy MinElute Cleanup Kits (QIAGEN). cDNA was synthesised by using a random hexamer with an adaptor sequence (GCCTTGGCACCCGAGAATTCCANNNNNN) and SuperScript IV First-Strand Synthesis System (Invitrogen). The cDNA was amplified by using KAPA Library Amplification Kit (Roche) and index primers from TruSeq Small RNA Library Preparation Kit (Illumina). Libraries were purified by using the equal volume of AMPure XP (Beckman Coulter) twice. The quality of the libraries was verified by using Bioanalyzer High Sensitivity DNA Kit (Agilent). The libraries were sequenced on MiSeq System (Illumina) by paired-end 2 × 150 bp sequencing.S. coelicolor A3(2) chromosome and ERCC92 sequences using HISAT2 with the “no-spliced-alignment” option and the “maxins” option of 100049. The number of 5′-end of forward reads that aligned each genomic position was counted using Samtools53. Transcriptional start sites (TSSs) were determined using the procedure reported previously . Raw reads were scanned from 3′ to 5′ and those with a quality score value below 20 were trimmed and reads consisting of fewer than 35 nucleotides were discarded using BBDuk (sourceforge.net/projects/bbmap/). Trimmed reads were aligned to the The significantly overexpressed genes in the whole transcriptomics data were further analysed for the presence of the TSSs. Overexpressed genes that had a TSS within 300 bp upstream from their initiation codon were determined the target genes of the sigma factor. If an overexpressed gene with no TSS was located within 50 bp downstream from a target gene, it was also determined a target gene.Further information on research design is available in the Supplementary informationPeer Review FileReporting Summary


CDKN2A/B genes that code for p16INK4a, p15INK4b, and p14ARF proteins, and it also harbors a long gene desert adjacent to these genes. The polymorphisms that are associated with several diseases and cancers are present in these genes and the gene desert region. These proteins are critical cell cycle regulators whose transcriptional dysregulation is strongly linked with cellular regeneration, stemness, aging, and cancers. Given the importance of this locus, intense scientific efforts on understanding the regulation of these genes via promoter-driven mechanisms and recently, via the distal regulatory mechanism have provided major insights. In this review, we describe these mechanisms and propose the ways by which this locus can be targeted in pathologies and aging.9p21 locus is one of the most reproducible regions in genome-wide association studies (GWAS). The region harbors  ARF, p16INK4a, and p15INK4b. These proteins are coded by two genes; CDKN2A and CDKN2B. p14ARF and p16INK4a are transcribed from the CDKN2A gene, whereas p15INK4b is transcribed from the CDKN2B gene (ARF (exon1β) and p16INK4a (exon1α) are different, but the second and third exons are identical. While the mRNA sequences of p14ARF and p16INK4a are relatively similar, the resultant proteins do not share any sequence similarity due to the alternative reading frames; thus, these proteins are not isoforms. On the other hand, p15INK4b and p16INK4a have a high degree of amino acid similarity (about 80%) and are thought to have emerged from a gene duplication event  in this locus are associated with several aging-related disorders, including coronary artery disease (CAD), type 2 diabetes, and atherosclerosis. The majority of the SNPs in this locus are located within the genes and the ∼0.3 Mb long adjacent gene desert region, but the mechanisms of their action are largely unknown. Thus, the identification of molecular pathways that regulate this locus in different diseases is of great therapeutic relevance.The INK4/ARF locus functions are attributed to three distinct but related proteins, namely, p14N2B gene . The inion event . AdditioINK4/ARF genes  present in the RING domain (RD), leading to sequestration of the MDM2-p14ARF complex in the nucleolus  pathway. These proteins activate Rb, a tumor suppressor protein that blocks the cell cycle at the G1 phase , and the release of senescence-associated secretory phenotype (SASP), etc., . This irnescence . Studiesll types . For exanescence . In summnescence .INK4/ARF genes are cell cycle regulators that arrest the cell cycle at various stages in response to stress signals such as DNA damage. These tumor suppressor genes must be silenced for cancer to progress. Thus, INK4/ARF locus harbors homozygous deletions in several malignancies, silencing the expression of all three cell cycle regulator genes  proteins are epigenetic modifiers that play a crucial role in transcriptional repression and therefore regulate cell proliferation, differentiation, embryonic development, cellular memory, and other vital cellular functions . PcGs fon others . Ectopicnescence . In contnescence .INK4/ARF promoters; for example, Zfp277, a zinc finger protein, interacts with the Bm1 subunit of PRC1 to recruit PRC1 to these promoters in MEFs  between these promoters   . In maturomoters .INK4/ARF during the onset of cellular senescence , MEFs, etc., which results in INK4a-mediated growth arrest in these cells  is a lysine-specific histone demethylase. Its role in development, cancer progression, infectious diseases, immune disorders, and other conditions has been extensively studied . JMJD3 bnescence . Many cese cells . By actise cells . Under tisturbed . As mentisturbed . JMJD3 igramming . Therefogramming .INK4/ARF genes and demethylates histones H3K36me2 and H3K4me3. Demethylation results in a decrease in PolII binding and an increase in H3K27me3. KDM2B suppresses this locus by epigenetic modifications of histones and also by preventing the downregulation of Ezh2  and dimethylated lysine 36 of histone H3 (H3K36me2) . It regu of Ezh2 . Consequof INK4b .INK4/ARF genes. DNA methylation is catalyzed by DNA methyltransferases (Dnmts), which transfer the methyl group from S-adenosyl methionine (SAM) to carbon 5 of cytosine to generate 5-methylcytosine (5mC)  . CpG islne (5mC) . Notablyhylation . Numerouof INK4a . Aberranan INK4a . Numerouan INK4a .INK4a/Rb pathway, as the re-expression of hSNF5 in MRT cells activated INK4b and INK4a, but not ARF , a ubiquitin recognition domain-containing transcription factor, promotes the expression of PRC1-repressed genes during differentiation by competing for H2AK119Ub with PRC1  is a transcription factor that binds to JDP2 response regions and prevents histone acetylation and methylation  is an ATP-dependent chromatin remodeler that plays a critical role in Ras-mediated senescence. It is essential for the activation of INK4a following Ras overexpression (INK4a for its upregulation (pression . Transcrgulation .HBP1. HMG box-containing protein 1 (HBP1) transcription factor is a downstream effector protein in the Ras signaling pathway. INK4a promoter contains a putative binding motif for this transcription factor between positions −426 and −433. Its binding to this motif triggers cellular senescence (INK4a promoter by assisting in the recruitment of histone acetyltransferase p300 and CREB-binding protein (CBP)  . Furtherenotypes .SP1.INK4a promoter has numerous GC-rich regions that are required for its induction upon senescence onset  interval resulted in a substantial decrease in the cardiac expression of CDKN2A/B genes, significantly increased mortality upon high cholesterol diet and ARF-dependent developmental abnormalities , but not INK4b  are a subclass of RNAs that are longer than 200 nucleotides and do not code for any protein product. They play critical roles in gene regulation, chromatin organization, translational regulation, etc. Several lncRNAs have been reported to influence the INK4/ARF locus expression . Most ofINK4/ARF silencing in growing cells, as its expression in these cells is inversely correlated to gene expression (INK4a promoter by nascently transcribing ANRIL RNA (INK4b promoter (INK4/ARF gene silencing (INK4b, but not INK4a (INK4a/ARF expression, in cervical cancers. In a recent study, we report that the PRC2 complex can bind to the INK4/ARF promoters independent of ANRIL levels in cervical cancer cell lines (INK4a promoter (INK4a promoter, resulting in transcriptional activation of INK4a (INK4a transcription by loading Bmi1 to its promoter. PANDAR silencing reduces cell proliferation and colony formation in MCF7 cells and causes G1/S arrest in a p16INK4a-dependent manner (INK4b and INK4a, suppressing their expression in gastric cancer (INK4a gene, and its silencing results in overexpression of all three genes, indicating that ANROC is a repressive RNA (INK4/ARF locus contains a lncRNA, ANRIL, which is transcribed antisense to the genes. ANRIL is ∼3.8 kb and has over 20 different splice variants. These splice variants of ANRIL play a differential protective role depending on the presence or absence of CAD risk interval . ANRIL ipression . This reNRIL RNA . Anotherpromoter . Therefoilencing . Subsequot INK4a . In contll lines . Anotherpromoter . Interesof INK4a . PANDAR t manner . PVT1 isc cancer . ANROC, sive RNA .INK4a and p15INK4b- dependent manner. This lncRNA regulates INK4/ARF expression by interacting with and directing the histone demethylase JMJD3 to the promoters for removal of the repressing H3K27me3 mark (CDKN2A exon1β. P14AS binds to AUF1, preventing ANRIL/INK4a RNA from interacting with AUF1. This competitive interaction between P14AS and AUF1 promotes ARF, INK4b, and INK4a gene expression (ARF, INK4b, and INK4a. VAD promotes the expression of these genes by removing H2A.Z from their promoters. H2A.Z deposition represses these genes by promoting the recruitment of the PRC complex to the promoters (INK4/ARF genes rather than inhibiting them. They switch from repressors to activators of these genes during RAF1-mediated senescence. These circular isoforms engage with Polycomb subunits and displace EZH2 from the INK4b and INK4a promoters, stimulating transcription of these genes. As a result of the PRC2 dislocation, H3K27me3 levels at these promoters drop (INK4a and INK4b (LncRNA ARHGAP27P1 is downregulated in gastric cancer cells, and when overexpressed, it inhibits gastric cancer cell proliferation, migration, and other functions in a p16me3 mark . AUF1 ispression . During romoters . Severalers drop . Similarnd INK4b . The preINK4/ARF genes are implicated in a wide range of cancers and age-related diseases, they hold immense promise for treating or mitigating the consequences of these diseases. Regulation of the INK4/ARF locus is multi-layered, with a plethora of factors involved. As a result, the greatest challenge in harnessing this locus for therapeutic purposes is identifying the critical regulatory elements that can be targeted in a particular disease. Targeting transcription factors or epigenetic modifiers involved in its regulation has very broad effects, affecting not just this locus but others as well. We recently uncovered a few enhancers in the upstream enhancer cluster that regulate these genes. These DNA regulatory elements can be altered to provide a more precise and targeted effect. Since this enhancer cluster contains multiple enhancers, these enhancers may act in a tissue type-specific manner. Thus, determining which enhancers regulate these genes under various physiological conditions is critical for the therapeutic use of enhancers or enhancer products like eRNAs. Additionally, SNPs in upstream enhancer regions have been associated with several diseases. These SNPs can facilitate the identification of regulatory enhancers in various cell types. Thus, a functional genomics approach is required to decipher how these SNPs result in changes in gene regulation.Since the products of the


Zbtb1 (zinc finger and BTB domain containing 1) is a member of mammalian zbtb gene family. A series of bioinformatics analysis was carried out for the EL4 cell and the Zbtb1-deficient EL4 cell by Hi-C, ATAC-seq and RNA-seq techniques. Finally, Hi-C results showed that the intensity of chromatin interaction in the deletion group decreased with distance, the degree of chromosome interaction decreased significantly, the AB division region changed significantly, and the compactness of TAD structure decreased; The results of ATAC-seq showed that the open area and degree of chromatin in the deletion group decreased; 7778 differentially expressed mRNAs were found by RNA-seq. Our experimental results for the first time expounded the significance of Zbtb1 gene for T cell development, lymphocyte production and apoptosis from the aspects of chromosome spatial structure and chromatin opening degree, and provided relevant theoretical basis and data support for the in-depth study of related Zbtb1 genes in the future. Zbtb1 plays a key role in T cell development and lymphocyte development, mRNA encoding Zbtb1 is most highly expressed in hematopoietic stem cells, thymocytes and pre-B cells, In addition to its role in T cell development, it was also demonstrated to be involved in the differentiation of B cells and NK cells, homozygous knockout of the Zbtb1 gene leads to severe combined immune deficiency in mice . In otheHi-C technology, derived from (Chromosome Conformation Capture—3C) technology, uses high-throughput sequencing technology, using proximity ligation combined with high-throughput sequencing, to study the interaction of the entire chromatin DNA on a genome-wide scale, taking the entire cell nucleus as the object of study . The forATAC-seq (Assay for Transposase-Accessible Chromatin with high-throughput sequencing) uses the preference for of open region chromatin to transposase for open region identification, and uses modified Tn5 transposase to directly introduce sequencing junctions into the open chromatin region by transposition reaction, and amplifies and sequences the open chromatin to finally obtain a genome-wide open chromatin map .Hi-C interaction data were analyzed jointly with ATAC-seq and transcriptome data, which can elucidate the mechanisms involved in organismal trait formation in terms of gene regulatory networks and epigenetic networks.Our sequencing analysis of Hi-C, ATAC-seq and RNA-seq was performed with the assistance of Annoroad Gene Technology , and the related experimental methods are shown in , the preThe results of the Hi-C experiment showed that the interaction ratio of CIS and trans chromosomes in the Zbtb1-deficient EL4 cell (KO group) and the EL4 cell (WT group) was approximately 75:25 . ChromatATAC-seq results showed that the open peak regions in the deletion group cells were seriously reduced, and the openness of many regions was weakened. The chromatin open region map at the chromosome level in the whole genome is shown in The RNA-seq results showed that 3185 differentially expressed mRNAs were upregulated and 4593 were downregulated. The volcanic map of the differentially expressed genes is shown in Previous studies have shown that Zbtb1 is a key determinant of T cell development and lymphocyte production and it affects cell apoptosis . ThroughOur results showed that the deletion of the Zbtb1 gene in EL4 cells led to the downregulation of the expression of many genes and great changes in the spatial structure of the chromatin. As a transcriptional repressor gene, Zbtb1 deletion also led to the upregulation of some genes. However, the ATAC results showed that the open chromatin region of many upregulated genes did not change significantly, which may be due to the restriction of gene expression due to transcriptional inhibition. After the deletion of the Zbtb1 gene, the inhibition was relieved, resulting in the upregulation of related gene expression, but it is difficult to say whether it is direct or indirect regulation.Our experimental results for the first time explained the important effects of the Zbtb1 gene on T cell development, lymphocyte production and apoptosis from the aspects of chromosome structure and chromatin spatial changes, which provided a relevant theoretical basis and data support for a future in-depth study of Zbtb1.