Root development and function have central roles in plant adaptation to the environment. The modification of root traits has additionally been a major driver of crop performance since the green revolution; however, the molecular underpinnings and the regulatory programmes defining root development and response to environmental stress remain largely unknown. Single-cell reconstruction of gene regulatory programmes provides an important tool to understand the cellular phenotypic variation in complex tissues and their response to endogenous and environmental stimuli. While single-cell transcriptomes of several plant organs have been elucidated, the underlying chromatin landscapes associated with cell type-specific gene expression remain largely unexplored.To comprehensively delineate chromatin accessibility during root development of an important crop, we applied single-cell ATAC-seq (scATAC-seq) to 46,758 cells from rice root tips under normal and heat stress conditions. Our data revealed cell type-specific accessibility variance across most of the major cell types and allowed us to identify sets of transcription factors which associate with accessible chromatin regions (ACRs). Using root hair differentiation as a model, we demonstrate that chromatin and gene expression dynamics during cell type differentiation correlate in pseudotime analyses. In addition to developmental trajectories, we describe chromatin responses to heat and identify cell type-specific accessibility changes to this key environmental stimulus.We report chromatin landscapes during rice root development at single-cell resolution. Our work provides a framework for the integrative analysis of regulatory dynamics in this important crop organ at single-cell resolution.The online version contains supplementary material available at 10.1186/s12915-022-01473-2. Arabidopsis and rice and revealed the transcriptional programmes of major cell types, as well as the heterogeneity within a given population [Arabidopsis and maize [Recently, single-cell RNA sequencing (scRNA-seq) has been applied to root cells of pulation –9. Howevpulation . Recentlpulation –15, inclnd maize –18. ConsSimilar to maize, rice is one of the most important crop plants worldwide, and we have previously profiled the single-cell transcriptomes of rice root tips from two cultivars, which revealed species-specific expression programmes, as well as more conserved pathways . To elucJaponica group cultivar Nipponbare (Nip). High-quality nuclei from 120 root tips (5 mm in length of primary roots) were obtained from 3-day-old Nip seedlings using our improved nuclei isolation protocol -specific ACR, the promoter of the root cap marker gene LOC_Os01g73700 contains a cluster 2 (C2)-specific ACR, the promoter of the endodermis marker gene LOC_Os01g15610 contains a cluster 3 (C3)- and cluster 4 (C4)-specific ACR, the promoter of the epidermis marker gene LOC_Os08g02300 contains a cluster 5 (C5)-specific ACR, the promoter of the stele marker gene LOC_Os01g15830 contains a cluster 6 (C6)- and cluster 7 (C7)-specific ACR, and the promoter of the cortex marker gene LOC_Os01g68589 contains a cluster 8 (C8)- and cluster 9 (C9)-specific ACR  was performed on the whole tissue (cell), including the cytoplasm. The regulation of RNA decay, RNA transport, RNA methylation, etc. may contribute to the differences between chromatin accessibility and gene expression. On the other hand, it suggested that further experimental validation would still be required.Next, we compared the scATAC-seq with our recently reported scRNA-seq data from the protoplast of rice root tips . We embedatasets  and plotTo categorize the function of genes associated with cluster-specific ACRs, we performed Gene Ontology (GO) analyses and found converging terms between scATAC-seq and scRNA-seq for all cell types. For example, genes related to water transport were enriched among mRNAs of cortex cells in scRNA-seq , as wellWe have previously described cell type-specific transcriptomes for root tips of two rice cultivars , but theSince gene expression is dictated by the interplay of open chromatin with TF activity, we aimed to elucidate the regulatory networks responsible for cell type differentiation in rice roots. Our analyses were built on the notion that TF-binding elements in ACRs represent the substrate for expressed TFs, identified by scRNA-seq, since most TFs can only bind to open chromatin, which is readily identified by scATAC-seq . To estaLOC_Os10g42750, were identified among the top differentially accessible genes throughout root hair development. Consistent with the central role of this gene for root hair development [LOC_Os10g42750, and cross-referencing with our scRNA-seq data allowed us to identify the WRKY TF LOC_Os04g50920, which is only expressed in the root hair and root cap and thus may represent a potential upstream activator  in rice roots but were lacking cell type resolution . To explIn this study, we applied scATAC-seq and obtained chromatin profiles of more than 46,000 nuclei of rice root tips under normal and heat stress conditions. Single-cell chromatin landscapes allowed us to identify nine clusters of cells that covered the major cell types found in the root tip. This structure correlated well with scRNA-seq data and revealed cell type-specific regulatory modules. Importantly, our analysis also defined chromatin dynamics during cell type development and in response to heat stress. Taken together, our results represent a valuable resource of chromatin accessibility at single-cell resolution to study the development and function of rice root cell types.2, 1% BSA) and 0.2% Tween 20 . 0.5% 2-ME (v/v) were added, and then the roots were ground completely. The homogenate was filtered with a 20-μm mesh (Sysmex) following centrifuge at 480 rcf for 5 min at 4 °C. After removing the supernatant, 1% BSA buffer (10 mM Tris-HCl (pH7.4), 10 mM NaCl, 3 mM MgCl2, 1% BSA (v/v)) was added to resuspend the pellet. Then, the mixture was placed on 80% Percoll and following centrifuge at 300 rcf for 25 min at 4 °C. After removing 150 μl supernatant, the nuclei were transferred to a new Eppendorf tube and washed twice with 1% BSA buffer. The nuclei were resuspended in a chilled Diluted Nuclei Buffer . The nuclei were stained by DAPI and trypan to check the quality and quantity.Rice Nip seeds were soaked in water in the dark until germination and then cultured in Hoagland’s Complete Nutrient Solution for 3 days . Primary root tips 5 mm in length from the 3-day-old rice seedlings were harvested and fixed with cold paraformaldehyde solution (2%) for 30 min. Then, the root tips were transferred to a Dounce grinder (kimble), which was filled with cold lysis buffer . Briefly, 16,000 resuspended nuclei (concentration 3000–7000 nuclei/μl) were combined with ATAC Buffer and ATAC Tn5 transposase (10x Genomics) to form a transposition mix. After incubation for 30 min at 37 °C, barcoding reagent and enzyme (10x Genomics) were added, and the resulting mix was loaded onto a single-cell chip, which was subsequently placed into a Chromium Single Cell Controller instrument for library construction. Quantification of the DNA library was done by Agilent 2100 Bioanalyzer then sequenced with an Illumina Hiseq 2000 sequencer.Oryza sativa Nip genome by using Bowtie2 [M value) ≥ 1; M value is the log2 fold change of normalization chromatin accessibility signal between two normal and HS samples.Bulk ATAC-seq was performed as described previously . Qubit f Bowtie2  with “-N Bowtie2  by usingOryza sativa Nip genome to generate fragment and cell files. Next, we used createArrowFiles function in ArchR [FASTQ files of each sample were firstly processed by using cellranger-atac (v.1.2.0) count pipeline coupled with in ArchR  to filteIn view of smaller genome of rice than human genomes, we estimated the gene accessibility score by using addGeneScoreMatrix function with “exp(-abs(x)/2000) + exp(-1)” geneModel, “c” extendstreams and “2000” geneUpstream parameters. ArchR allows for the use of accessibility within the entire gene body and putative distal regulatory elements with complex user-supplied custom distance-weighted accessibility models contributes to the gene score.We got the “TileMatrix”, which is genome-wide 500-bp tiles in ArchRProject. log(TF-IDF) (Term frequency-inverse document frequency) normalization with TileMatrix, Latent Semantic Indexing (LSI) dimensionality reduction and harmony batch effect correction methods were chosen for the subsequent analysis. We used 0.1 resolution to define cell clusters and UMAP to visualize single cells. Nine clusters were identified and annotated cell types based on the promoter of cell type marker genes containing cluster-specific ACRs.MACS2 was used to call ATAC peaks. Specifically, we generated a reproducible peak set and called union peaks among clusters with addReproduciblePeakSet and addPeakMatrix functions, respectively. The getMarkerFeatures function was used to detect all kinds of differential chromatin accessibility in our analysis, in more detail, GeneScoreMatrix for defining cluster-specific marker genes and PeakMatrix for detecting cluster-specific ACRs among clusters. On the other hand, differential peaks and gene scores were also evaluated between the normal and HS groups in each cluster. Bias with TSS enrichment and log10(nFrags) were also accounted for in selecting a matched null group for marker feature identification, and the Wilcoxon test was used for statistical analysis.LOC_Os04g53640, and primers 5′-TAATACGACTCACTATAGGGGCTGATATCCTTGCTCTGGTAGC-3′ and 5′-ACCTGATCCTTTGCGTCAAGG-3′ were used to generate its sense probe.RNA in situ hybridization was performed as described previously , 29. Brihttp://geneontology.org/). Enrichment terms were obtained with p.adjust < 0.05. p-value adjustment (FDR) is performed using the Benjamini–Hochberg method. Here, enrichment is implemented with the hypergeometric test (Fisher’s exact test).We used cutoff (FDR ≤ 0.01 and Log2FC ≥ 1) to define cluster-specific marker genes and peaks, and the nearest gene of a peak was regarded as its target gene for functional analysis. compareCluster function in the clusterProfiler package , 31 was We defined co-accessibility ACRs with a correlation of 0.5 threshold using addCoAccessibility and getCoAccessibility functions in ArchR across all cells. Co-accessibility ACRs will be shown as a loop when plotting a browser tracks with ArchRProject.http://planttfdb.gao-lab.org/download.php#bind_motif). First, we used MotifScan (http://bioinfo.sibs.ac.cn/shaolab/motifscan/index.php) to predict all TF motif-binding sites across union peak regions with cutoff p-value < 1e−4. “genomecompile” and “motifcompile” commands had been run to get reference index and background motif score cutoff under different p-value. Next, we used the addPeakAnnotations function to add our motif-binding site annotation and got a motif deviation score matrix with the addDeviationsMatrix function by ArchR.Rice TF motifs were downloaded from the PlantTFDB v5.0 database (https://www.archrproject.com/bookdown). The trajectory-associated figures were plotted by using plotTrajectoryHeatmap and plotTrajectory functions. Some cells were filtered in the final trajectory by preFilterQuantile with the default parameters, which resulted in these cells were not in the final trajectory.We performed trajectory analysis by using the addTrajectory function in the ArchR software  with defArabidopsis scRNA-seq and scATAC-seq datasets [We integrated our scRNA-seq  with scAdatasets . Firstlyhttp://glab.hzau.edu.cn/RiceENCODE/ [The ChIP-seq datasets, including H3K4me1, H3K4me3, H3K27me3, and H3K9me2 from 1-week-old rice Nip, were downloaded from eENCODE/ , 33. PytAdditional file 1: Figure S1. Isolation and purification of nuclei from rice root tips. Figure S2. Evaluation and quality control of rice scATAC-seq. Figure S3. Example of cluster-enriched chromatin accessibility and surrounding genes, and in situ hybridization of sense probe. Figure S4. Correlation between scATAC-seq and scRNA-seq. Figure S5. Heatmap showing enrichment of TF motifs. Figure S6. TFs and motif enrichment at ACRs in rice root. Figure S7. Pseudotime heatmap ordering from epidermis to root hair. Figure S8. Violin plot showing chromatin accessibility changes in genes related to “jasmonic acid biosynthetic process”. Table S1: Sequencing statistics.Additional file 2: Table S2: Marker genes of each cluster. Table S3: ACRs of each cluster for Normal and HS. Table S4: List of genes with open chromatin accessibility but low/no expression. Table S5: List of genes with close chromatin accessibility but high expression. Table S6: List of overlapped marker genes between scRNA-seq and scATAC-seq. Table S7: List of GO terms for genes associated with cluster specific ACRs. Table S8: ACRs and corresponding genes detected in the bulk ATAC-seq experiment for Normal. Table S9: ACRs and corresponding genes detected in the bulk ATAC-seq experiment for HS.Additional file 3: Table S10: Enriched TF motifs in differential ACRs upon heat stress for each cluster. (XLS 403 kb)


The jasmonic acid (JA) signaling pathway plays important roles in plant defenses, development, and the synthesis of specialized metabolites synthesis. Transcription factor MYC2 is a major regulator of the JA signaling pathway and is involved in the regulation of plant physiological processes and specialized metabolite synthesis. Based on our understanding of the mechanism underlying the regulation of specialized metabolite synthesis in plants by the transcription factor MYC2, the use of synthetic biology approaches to design MYC2-driven chassis cells for the synthesis of specialized metabolites with high medicinal value, such as paclitaxel, vincristine, and artemisinin, seems to be a promising strategy. In this review, the regulatory role of MYC2 in JA signal transduction of plants to biotic and abiotic stresses, plant growth, development and specialized metabolite synthesis is described in detail, which will provide valuable reference for the use of MYC2 molecular switches to regulate plant specialized metabolite biosynthesis. Phytohormones are important regulators of plant growth and development. In response to damage, plants generally integrate phytohormone signaling pathways to trigger immune defense and repair responses throughout the plant body . ParticuIn contrast to animals, plants are sessile and cannot flee from biotic or abiotic stress conditions . Plants Synthetic molecular switches are mostly based on protein–protein, protein–DNA, or protein–RNA interactions . Plant tCOI1, JAZ, and the transcription factor MYC2 . . Taxus cpression b . . Taxus cynthesis d, resultaceptive . GhMYC2 aceptive .Tripterygium wilfordii, TwMYC2a and TwMYC2b negatively regulate triptolide biosynthesis by inhibiting TwTPS27a and TwTPS27b in hairy roots [Psammosilene tunicoides by regulating the backbone-building enzymes β-amyrin synthase and squalene epoxidase in the triterpenoid saponin synthesis pathway [Hevea brasiliensis) latex. The specific JA signal transduction module COI1-JAZ3-MYC2 exists in rubber tree milk-duct cells, and MYC2 enhances secondary milk duct differentiation and rubber biosynthesis by upregulating the expression of farnesyl pyrophosphate synthase and small rubber granule-protein genes [In ry roots . MYC2 di pathway . In addi pathway . For exain genes .bryophytes [Escherichia Coli and Saccharomyces Cerevisiae cultures [Synthetic biology aims to redesign existing natural biological systems to achieve target functions . The conyophytes . JA was cultures . The JA-Saccharomyces cerevisiae, a series of regulatable promoters with a length of no more than 100 bases was constructed by modularizing the promoters [Taxus chinensis can be used to comprehensively elucidate the paclitaxel biosynthesis pathway [E. coli. In general, the biosynthesis of most natural products requires the interaction of cytochrome P450 and its reductase for electron transfer; however, it is difficult to express P450 in E. coli [S. cerevisiae has a rich endomembrane system in which cytochrome P450 can be efficiently functionally expressed, E. coli and S. cerevisiae can be used to produce paclitaxel using a co-culture method [Plant specialized metabolites are of great value to medicine and industry, but they are difficult to extract, and yields are low . Researcromoters . Synthetromoters ,136. Tak pathway . In synt E. coli . As S. ce method .Dof2.1, ERF115, etc.), and then connected to the JA-JAZ-MYC2 molecular switch for co-expression. In the application of synthetic biology, transcription factors and promoters that naturally exist in plants have been developed as molecular switches and promoters for efficient synthesis of specialized metabolites. For example, in rice, scientists have produced a construction containing eight anthocyanidin-related genes , which are driven by endosperm-specific promoters, to produce a new bio-enhanced germplasm “purple endosperm rice”  with high anthocyanin content and antioxidant activity [ZmLc (Leaf color) and ZmPl (Purple leaf), which encode the bHLH-type and MYB-type transcription factors, respectively, to activate the anthocyanin biosynthesis genes [The cis elements recognized by MYC2 are used as promoters to drive all genes necessary for the synthesis of a natural product, and they are connected with JA-JAZ-MYC2 conditional molecular switches to form artificial chromosomes . Becauseactivity . Researcis genes ,142.E. coli and S. cerevisiae as typical hosts. E. coli is the most widely prokaryotic host used to produce heterogenous metabolites. As a chassis cell, it has the characteristics of rapid/easy growth, high product yield, and high cost efficiency. Further, the availability of various expression vectors and strains, the operation technology, and the relative ease of product purification make it an attractive host for industrial applications. However, the lack of cell intima as well as post-translational modification limit its use as a selection chassis for many plant natural products [Nicotiana benthamiana, and various natural products, including alkaloid terpenoids, paclitaxel, and artemisinin, have transiently been expressed in N. benthamiana [The chassis cells produced using plant metabolites include plant chassis and microbial cell chassis. Microbial cell chassis development utilizes products . The useproducts ,144,145.products . The comthamiana ,147,148.thamiana ,150,151.CaMV35S, Nos, and Ocs, which are always active, the inducible gene expression system constructed by MYC2 can more dynamically and precisely regulate gene expression for optimal production of valuable chemicals [The JA signal in plants is an important signal pathway in response to external stimuli. The inducibility and controllability of the JA-JAZ-MYC2 regulatory pathway endows it with the potential to be applied as a synthetic biological molecular switch. As a transcription factor, MYC2 itself can directly regulate the synthesis of a variety of plant specialized metabolites, and the promoter of its target gene can also be directly applied to the construction of artificial chromosomes regulated by the JA-JAZ-MYC2 molecular switch. Transgene expression only needs to occur at a certain point or time period in order to minimize the metabolic burden on the host cell, or to control the timing of gene expression. For this reason, unlike constitutive promoters such as hemicals . An ideahemicals ,154,155.


HSV-1 DNA replication is a key point in the infectious cycle, as it enables γ2 and amplifies γ1 transcription [1/γ2) gene transcription. Although the HSV-1 gene expression cascade was identified over 40 years ago, high-throughput sequencing approaches continue to reveal new insight into how each gene class is regulated [Herpes simplex virus type-1 (HSV-1) is an alpha herpesvirus that infects over 60% of the human population ,3, whichcription ,10. Beloegulated –15.Fig 1). Early studies demonstrated that α and β polypeptide levels peak between 3 to 4 and 5 to 7 hours post infection (hpi), respectively [1 mRNA is expressed around 2 hpi, and expression is amplified by viral DNA replication. Additionally, γ2 mRNA is detected following the onset of DNA replication, with increasing levels observed through 16 hpi. The exact timing of the virus life cycle may vary depending on the cell type.HSV-1 genes are temporally expressed during lytic infection. Taking advantage of synchronous infection during high multiplicity infection, the temporal expression of viral genes was previously characterized  or negligible (γ2) expression during infection with the UL30 mutant compared to the lab strain  mutant that is defective for viral DNA synthesis . Twenty-b strain . These ra β gene . In gene2 mRNAs were not expressed. However, if acyclovir was added at 3 or 4 hpi, allowing for 1 to 2 rounds of viral DNA replication as measured by real-time PCR to quantify viral genome number, γ2 mRNA levels observed at 12 hpi were similar to an untreated control. These data may indicate that DNA replication is not continuously required for γ2 gene expression, and that the alterations that enable their expression occur during initial rounds of replication. It is possible that alterations in viral chromatin or the architecture of the viral genome enable this switch. However, it was recently demonstrated that although chromatin dynamics dictate the transcriptional competency during the onset of lytic infection, it does not appear to play a role in regulating the temporal expression of individual classes of viral genes [An important question is whether ongoing DNA replication is continuously required for γ genes to be expressed. To address this, viral DNA replication was inhibited with acyclovir at 0, 2, 3, 4, or 6 hpi, and the effects on viral gene expression were determined by RNA-seq at 12 hpi . If acycal genes ,14.Experiments conducted to identify proteins that interact with the HSV-1 genome during viral replication reveal insight into the potential mechanism through which γ gene expression is regulated. Using an adaptation of iPOND (isolation of proteins on nascent DNA), replicating viral DNA was pulse labeled with the nucleoside analog 5-ethynyl-2′-deoxycytidine (EdC) to enable subsequent tagging and purification of replicated viral DNA, followed by the identification of associated proteins by mass spectrometry . In addiiPOND was also used to compare the relative enrichment of individual proteins at viral replication forks with that of nascent viral DNA post replication . For thi2 gene promoters that are necessary for replication-dependent transcription . The region immediately upstream from the transcription start site and another region downstream in the 5′ untranslated region of the gene are responsible for replication-dependent expression of representative γ2 genes [2 gene promoters in an ICP4-dependent manner [1 genes are less well understood, but representative promoters contain SP1 binding sites, a TATA box, and an Inr element [cis elements of γ1 and γ2 promoters contributes to the differences in their dependence on DNA replication.Transcription reporters have been used to map key regions of HSV-1 γγ2 genes –26. Thist manner ,13,27–29 element . It is l2 promoters, was enabled by viral DNA replication. TBP binds to the TATA box sequence and TAF1 was enriched near the Inr element of γ2 viral genes after the onset of viral DNA replication. In the absence of DNA replication, Pol II was deficient on the promoters and bodies of γ2 genes [2 genes[2 gene promoters to general transcription factors resulting in robust transcription.To better understand the mechanisms behind HSV-1 gene expression, chromatin immunoprecipitation followed by sequencing (ChIP-seq) was used to map TFIID, TBP, and Pol II binding to viral DNA before and after replication . Acyclovγ2 genes ,15. A si [2 genes, consist [2 genes. Additio [2 genes. These d2 gene transcription is not completely understood. One possibility is that ICP4 recruits Mediator to γ2 genes before the onset of viral DNA replication in a form that may inhibit transcription . In support of this model, Mediator containing the kinase domain has been found to copurify with ICP4 [Using ChIP-Seq, it was found that prior to DNA replication, ICP4 coats the HSV-1 genome at a high density . Followiith ICP4 . In addiith ICP4 . These s2 gene expression to DNA replication is an intriguing concept with several remaining questions. Interestingly, other viruses such as the T4 bacteriophage also couple the expression of late genes to DNA replication [2 genes and what specific alterations to the viral genome allow this to occur. As mentioned above, there is likely an alteration to the genome architecture following viral DNA replication that enables a distinct change in the transcriptional competence of the genome. Understaninding the details of this change will further define how γ2 gene expression is enabled. It remains to be determined how the abundance of ICP4 or other forms of viral chromatin on the genome contribute to this switch or if other modifications of the genome, such as the repair of nicks and gaps or the formation of recombination intermediates, are involved. While 2 genes are regulated, it does not role out the involvement of additional factors or alternate mechanisms. Another interesting observation is that during reactivation from latency, γ2 genes can be expressed independent of both prerequisite viral proteins and DNA replication [2 genes. While there is significant progress made toward understanding the coupling of HSV-1 γ gene expression with viral DNA replication, there are several remaining paths for future investigation.The coupling of HSV-1 γlication . Althouglication ,34. It i


Recent mechanistic explorations have revealed important roles for TERT promoter mutations and aberrant methylation in activation of TERT transcription and telomerase in UCs. Moreover, these TERT-featured genomic and epigenetic alterations have been evaluated for their usefulness in non-invasive UC diagnostics, recurrence monitoring, outcome prediction and response to treatments such as immunotherapy. Importantly, the detection of the mutated TERT promoter and TERT mRNA as urinary biomarkers holds great promise for urine-based UC liquid biopsy. In the present article, we review recent mechanistic insights into altered TERT promoter-mediated telomerase activation in UCs and discuss potential clinical implications. Specifically, we compare differences in senescence and transformation between NHUCs and other types of epithelial cells, address the interaction between TERT promoter mutations and other factors to affect UC progression and outcomes, evaluate the impact of TERT promoter mutations and TERT-mediated activation of human endogenous retrovirus genes on UC immunotherapy including Bacillus Calmette-Guérin therapy and immune checkpoint inhibitors. Finally, we suggest the standardization of a TERT assay and evaluation system for UC clinical practice.Telomerase, an RNA-dependent DNA polymerase synthesizing telomeric TTAGGG sequences, is primarily silent in normal human urothelial cells (NHUCs), but widely activated in urothelial cell-derived carcinomas or urothelial carcinomas (UCs) including UC of the bladder (UCB) and upper track UC (UTUC). Telomerase activation for telomere maintenance is required for the UC development and progression, and the key underlying mechanism is the transcriptional de-repression of the  Human linear chromosomes terminate with TTAGGG repetitive sequences lasting up to 20 kilobases, and these DNA repeats together their binding factors (a six protein-containing shelterin) form special DNA-protein structures so-called telomeres –4. TelomTelomere shortening-mediated senescence is believed as an evolutionary trade-off to protect against cancer . Indeed,TERT gene is stringently repressed in most normal human cells, which acts as the key mechanism to silence telomerase , however, its core holyenzyme is only composed of telomerase reverse transcriptase (TERT), the subunit catalyzing telomeric DNA synthesis, and internal template telomerase RNA component (TERC) –11. TERClomerase . It has  process , 7. Greavia TERT induction and telomerase activation. Moreover, in vitro experiments even showed that TERT alone was sufficient to immortalize and/or transform normal urothelial cells  arise from the urothelium in the urinary track including renal pelvis, ureter and bladder, among which the UC of the bladder (UCB) is commonest, accounting for approximately 90% of all UCs, while the rest 10% are UC of renal pelvis and ureter (UCRP and UCU), collectively called upper track UC (UTUC) . The accal cells –15. The in vivo NHUC senescence, but in vitro cultured NHUCs have been well demonstrated to undergo 20 to 30 population doublings before entering senescence  to the mutant TERT promoter for TERT transcription in UCB cells . TRIM28 ion site . By doinion site .TERT induction and telomerase activation take place in general at the late stage of a stepwise oncogenesis process . HoweverFGFR3, BRAF, and RAS in UCBs, melanoma and TCs, respectively  spanning approximately 4 kbs from -1 800 to +2 200 bp relative to the ATG site , 53, 63. blocked , 53. In  blocked  analyzed blocked . The samthylated , 53. ThuTERT transcription, leading to biallelic or monoallelic expression (BAE or MAE) of TERT  , 79. TAPCystoscopy and urinary cytology are routinely applied for UCB and/or UTUC diagnostics , 82. In Many investigations have determined the usefulness of TERT promoter mutations as urinary biomarkers in UCs. Both cellular DNA and cell-free DNA (cfDNA) extracted from patient urine specimens have been evaluated. Because UCBs are the predominant type of UC tumors and they have the highest frequency of TERT promoter mutations up to 85%), most related data are obtained from analyses of UCB patients. For C228T/C250T mutations as urinary biomarkers, reported specificity is consistently high, however, sensitivity varies significantly, mainly dependent on detection methods. Sanger sequencing is specific (97% - 100% specificity) but can detect the mutated sequences only when mutation-containing tumor DNA is beyond 10% in the total bulk DNA , 84. For%, most rThe next generation sequencing was applied for urinary detection of mutated TERT promoters in UCB patients with satisfied sensitivity and specificity, too , 93. HowUC patients typically present with hematuria, however, hematuria is not specific to UCs and can occur in up to 9–18% of the population . TherefoAs described above, frequent recurrence occurs in UCBs, and a life-long follow-up is recommended. The urinary assessment of the mutated TERT promoter has demonstrated its value in monitoring UC recurrence. In most UCB patients, the mutated TERT C228T/C250T disappears rapidly in urine after tumors are resected, whereas the persistence of the mutation in urine is observed in a small fraction of patients and strongly indicates a recurrence risk , 87, 90.Urinary TERT promoter mutations as early detection or screening biomarkers for UCB have been evaluated, too. Urine samples from 38 individuals who late developed primary UCB and 152 matched controls were analyzed for TERT promoter mutations . The mutTERT promoter hypermethylation as the urinary biomarker for UCs has also been evaluated and it is usually combined with other methylated genes for UC diagnosis. Vinci et al.  examinedThe prevalence of TERT promoter mutations in UCBs can reach up to 85% in western countries but less than 50% in Asian populations , 47, 102The evaluation of TERT promoter mutations as a prognostic factor for UC survival gives rise to conflicting results . The assIt is well established that non-muscle invasive bladder cancer (NMIBC), although recurs frequently, is in general non-lethal, while muscle-invasive BC (MIBC) is more aggressive with poor outcomes. It was shown that TERT promoter mutation-bearing NMIBC tumors progressed into MIBCs more frequently than their wt counterparts. Leão et al. combined the TERT promoter mutation with methylation to predict T1 stage NMIBC progression. Less 10% of tumors with wt and low methylated UTSS region of the TERT promoter exhibited disease progression, whereas progressive disease occurred in 52% of tumors with the mutated promoter and hypermethylated UTSS . MoreoveTERT promoter mutation, present in 61% of those UCBs, served as an independent predictor of improved PFS and OS  therapy and modern immune checkpoint inhibitors (ICIs) as well . de KoucS and OS . AnotherS and OS . FurtherS and OS . It is uS and OS . Furtherhuman endogenous retrovirus (HERV) genes, recently identified by Mao et al.  response , 120. InTERT transcription. The mutated or methylated TERT promoter and TERT transcripts are useful biomarkers for non-invasive urinary diagnosis and surveillance of UCs, however, it is important to standardize assay and evaluation system for clinical practice. The impact of the TERT promoter mutation on UC outcomes may be affected by TERT SNPs, promoter methylation status and other variables, which are required for further investigations to achieve TERT-based precision UC management. Finally, TERT promoter mutations and gene expression as predictors for response to UC immunotherapy, the association between TERT-mediated HERV activation and immunotherapy efficacy, and TERT vaccine for UC treatment are all important and worthy of detailed investigations in future. For all these purposes, the standardization of a TERT assay and evaluation system is required.TERT induction and telomerase activation play essential roles in immortalization and malignant transformation of NHUCs, while the TERT promoter mutation is a predominant mechanism to activate telomerase in UCs, especially UCBs. In addition, the aberrant TERT promoter hypermethylation occurs widely in UCs and interacts with the mutated promoter to robustly augment TL, CX and DX conceived and designed the study. TL, SL, CX and DX participated in the data process, analysis and interpretation. TL, CX and DX wrote and revised the manuscript. All authors contributed to the article and approved the submitted version.


During transcription, DNA replication and repair, chromatin structure is constantly modified to reveal specific genetic regions and allow access to DNA-interacting enzymes. ATP-dependent chromatin remodelling complexes use the energy of ATP hydrolysis to modify chromatin architecture by repositioning and rearranging nucleosomes. These complexes are defined by a conserved SNF2-like, catalytic ATPase subunit and are divided into four families: CHD, SWI/SNF, ISWI and INO80. ATP-dependent chromatin remodellers are crucial in regulating development and stem cell biology in numerous organs, including the inner ear. In addition, mutations in genes coding for proteins that are part of chromatin remodellers have been implicated in numerous cases of neurosensory deafness. In this review, we describe the composition, structure and functional activity of these complexes and discuss how they contribute to hearing and neurosensory deafness. Eukaryotic chromatin is densely compacted in the nucleus through nucleosomes, an assembly of DNA wrapped around an octamer of two copies of the four histone proteins H2A, H2B, H3 and H4 . ChromatInner ear development is a heavily controlled process governed by dynamic epigenetic regulation, consisting of several mechanisms that ensure the spatiotemporal control of gene expression—one of the fundamental mechanisms to ensure chromatin remodelling. This ATP-dependent mechanism is carried out by a highly evolutionarily conserved set of enzymes belonging to the SNF2 superfamily called chromatin remodellers which are involved in many cellular processes such as transcription, recombination, DNA repair and replication . They arThe inner ear is a multifunctional sensory organ responsible for hearing (cochlea), balance and orientation in space (vestibular system). Following a thickening on the ectoderm surface, the pre-placodal region will give rise to the otic placode at the end of the third week of human gestation. A series of signalling molecules such as FGFs highly regulate this process. The otic placode then invaginates to form the otocyst that goes on to morph into different structures of the inner ear through the modulation of gradients of morphogenic factors. An opposing gradient of Wnt and sonic hedgehog (Shh) defines the dorsoventral axis, a gradient of retinoic acid (RA) defines the anteroposterior axis and at least in part, FGF3 regulates the specification of the mediolateral axis . The aduThe CHD family consists of nine members (CHD1–CHD9). Their structure is characterised by two consecutive chromodomains in the N-terminal region and an SNF2-like ATP-dependent helicase domain positioned in the central region. They recognise and bind nucleosomes to contribute, in many cases, to the formation of heterochromatin typically marked by the presence of methylated histones and other repressive chromatin markers. CHD proteins can bind to methylated histones through their chromodomains and use their helicase activity to remodel the chromatin and contribute to the formation of heterochromatin, a fundamental feature of chromosomes that ensures genomic stability .CHD proteins are classified into three subfamilies (Class I–III) , definedRegardless of overall protein domain structure, the function of CHD superfamily proteins is directly connected to regulating gene expression by controlling chromatin states. They are mainly translational repressors . Here, wCHD3 and CDH4 share 71.6% of their amino acid sequences. Both proteins form distinct nucleosome remodelling deacetylase (NuRD) complexes with different but overlapping functionalities . Mass spCHD3, characterised by intellectual disability, developmental delay  and several dysmorphic features . Th. ThSMARCEach of the two ATPase units SNF2L and SNF2H form heterodimers with either a BAZ-family transcription factor or a larger protein  capable of interacting with acetylated histones . In mammCerc2 have been shown to cause inner ear developmental defects with smaller and wider cochlea and stereocilia disorganisation in hair cells in the organ of Corti [Among these ISWI complexes, only CERF (Cecr2-containing remodelling factor complex) has been shown to play a role in inner ear development and neural tube closure ,100. CERCecr2 on the PCP pathway. Surprisingly, microarray analysis of PCP genes shows that Cecr2 exencephaly is unlikely to directly impact the PCP pathway [The fact that these defects are reminiscent of the misregulation of planar cell polarity (PCP) mutants suggests a possible influence of  pathway . HoweverIt has been shown time and again that ATP-dependent chromatin remodellers are of paramount importance in developmental processes and their involvement in disease, and increasing evidence suggests their implication in the inner ear. Among others, new omics, biophysics and bioinformatics technologies are providing valuable tools to study epigenetic modulation via chromatin remodellers. However, this subject needs to be further investigated in the context of human disease—notably using organoid models, which are rapidly developing, to realistically recapitulate the developmental pathways involved in the emergence of a bona fide inner ear organ, although some challenges remain to be overcome, namely generating actual cochlear-identity hair cells. This would ultimately allow the high-throughput screening of molecules, gene and cell-based therapies, which would accelerate the drug discovery process for diseases involving chromatin remodeller defects.


Brassica napus, resynthesized allopolyploid B. napus, and diploid progenitors (B. rapa and B. oleracea). “Chromatin accessibility shock” occurred in both allopolyploidization and natural evolutionary processes, and genic accessible chromatin regions (ACRs) increased after allopolyploidization. ACRs associated with H3K27me3 modifications were more accessible than those with H3K27ac or H3K4me3. Although overall chromatin accessibility may be defined by H3K27me3, the enrichment of H3K4me3 and H3K27ac and depletion of DNA methylation around transcriptional start sites up-regulated gene expression. Moreover, we found that subgenome Cn exhibited higher chromatin accessibility than An, which depended on the higher chromatin accessibility of Cn-unique genes but not homologous genes.Although asymmetric subgenomic epigenetic modification and gene expression have been revealed in the successful establishment of allopolyploids, the changes in chromatin accessibility and their relationship with epigenetic modifications and gene expression are poorly understood. Here, we synthetically analyzed chromatin accessibility, four epigenetic modifications and gene expression in natural allopolyploid  Brassica napus are analysed using ATAC and ChIPseq, with differences in asymmetric chromatin accessibility between subgenomes of B. napus investigated.Changes in chromatin accessibility occuring during the process of allopolyploidization of  Polyploidization brings two or more sets of identical or distinct genomes into a nucleus, producing either autopolyploids or allopolyploids3, which is accompanied by dramatic and dynamic genetic and epigenetic changes5, and allopolyploids have long been thought to play a more critical role in plant divergence due to unique hybridization during their formation4. Allopolyploids undergo more rapid and drastic transcriptional changes due to the sudden appearance of diverged subgenomes in the same cells6. Genomic expression dominance has been demonstrated to be a typical feature of many allopolyploids8, and a large amount of data has demonstrated that genomic expression dominance is associated with asymmetric epigenetic features, such as DNA methylation9, histone modification8 and chromatin compactness10. However, how chromatin accessibility shapes transcriptome patterns during allopolyploidization and subsequent evolutionary processes remains poorly understood.Polyploidization events have been found in the evolutionary history in more than 70% of angiospermscis-regulatory elements (CREs)12. Active CREs are generally located in accessible chromatin regions (ACRs) that can be accessed by nucleases through evicting or unraveling nucleosomes13. Identification of ACRs helps decipher CREs in the genome, which is critical for understanding the complex transcriptional regulatory networks underlying gene expression. The accessibility of chromatin can be assayed by several established methods, including DNase-Seq based on DNase I14, MNase-Seq based on micrococcal nuclease15, and ATAC-Seq based on transposase Tn517. Compared with other methods, ATAC-Seq has some advantages, such as significantly less experimental materials and easier library construction18. This method has been applied in plant genomic studies, such as delineating ACRs of multiple plant species20, revealing cell type-specific transcriptional regulatory networks22, and identifying altered chromatin accessibility in mutant plants18 and plants under stress23. However, there are scarce studies on how chromatin accessibility changes after polyploidization.Regulation of the transcription of genes is governed by interactions between regulatory proteins and 25. As one of the most characterized chromatin modifications, histone acetylation is associated with the open chromatin structure and active transcription26. Because lysine can be monomethylated, demethylated or trimethylated, histone methylation has more complex forms and functions27. Repressive histone methylation  is located in heterochromatin and inhibits gene expression28, whereas active histone methylation  is located in euchromatin and promotes gene expression29. Surprisingly, several studies revealed bivalent chromatin with active (H3K4me3) and repressive (H3K27me3) histone methylation31, and these modifications may represent a more accessible chromatin environment that promotes the binding of regulatory proteins to regulate gene expression30. As a conserved epigenetic modification, DNA methylation can be located in the promoter or gene body and play profound roles in gene expression34. A recent study found that DNA methylation in CG, CHG and CHH contents impacts the chromatin accessibility of heterochromatin25. The relationships among histone modifications, DNA methylation and chromatin accessibility during the formation and evolutionary process of allopolyploids are worth exploring.The chromatin regulatory landscape is related to histone modifications and DNA methylationBrassica napus , an allopolyploid plant, is one of the most important oil crops widely cultivated in the world35. Natural B. napus originated from interspecific hybridization and subsequent whole genome duplication (WGD) of B. rapa  and B. oleracea  approximately 7500 years ago in the Mediterranean region35. With the whole genomes of these three species sequenced, they became a model system for studying allopolyploidization37. Although the asymmetric gene distribution35, asymmetric epigenetic modification38 and bias gene expression39 of subgenomes of B. napus have been revealed gradually, the differences in chromatin accessibility between subgenomes and the evolutionary changes of ACRs have not been reported in the allopolyploid B. napus. In this study, we generated genome-wide chromatin accessibility of natural B. napus, resynthesized B. napus and in silico ‘hybrid’ constructed by two progenitors. Genotype-specific motifs and transcription factor (TF) regulatory networks were illuminated. We comprehensively analyzed differences in chromatin accessibility between subgenomes and further compared the chromatin accessibility of biased expressed homeologous gene pairs. In addition, we comprehensively analyzed the chromatin accessibility and its relationships with three histone epigenetic modifications , DNA methylation and gene expression of natural B. napus, resynthesized B. napus and in silico ‘hybrid’ constructed by two progenitors.B. napus and their progenitors, we constructed genome-wide maps of ACRs of leaves through ATAC-Seq, with three biological replicates for all the genotypes. High Spearman correlations were observed between biological replicates  to 102 million  raw reads were obtained from ATAC-Seq, more than 96% of which were clean reads in all samples , which can fuse well with parental data for the convenience of subsequent studies, by mixing the reads of B. rapa and B. oleracea in equal proportions. As shown in Table B. rapa, B. oleracea, resynthesized B. napus, and natural B. napus were mapped to the genome of B. napus35, and the GC content of each sample was higher than 40%.To ascertain the chromatin regulatory landscape of two types of es Table . Accordi41 were referred to as accessible chromatin regions (ACRs). In total, 36,161, 40,913, and 27,965 ACRs were identified in in silico ‘hybrid’, resynthesized B. napus and natural B. napus  in all genotypes  of ACRs were distributed in the promoter region, especially promoters within 1 kb (37.24%), followed by the distal intergenic region (34.09%), whereas only 2.3% and 2.06% of ACRs were distributed in the gene body (exons and introns) and within 300 bp downstream of gene end in the in silico ‘hybrid’  in a genotype were categorized as different enriched ACRs (DEAs) in that genotype and we identified 320 genes that had more accessible DEAs and 500 genes that had fewer accessible DEAs in in silico ‘hybrid’ than in resynthesized B. napus  and DEGs. In each comparison, the highly expressed DEGs in a genotype were referred to as genotype-enriched DEGs. As shown in Fig. B. napus-enriched DEGs were associated with genotype-enriched ACRs. In the comparison of two types of B. napus, 15.5% (101) of the resynthesized B. napus-enriched DEGs and 14.3% (95) of the natural B. napus-enriched DEGs were regulated by ACRs. Although most DEGs were found in comparison of in silico ‘hybrid’ and natural B. napus, the proportion of genotype-enriched ACR-associated DEGs was similar to that in the previous comparisons. These results indicated that the changes in chromatin accessibility regulated the differential expression of a part of DEGs, which was similar in maize22.To determine the relationship between chromatin accessibility and gene expression levels, we explored the chromatin accessibility of four groups of genes divided by gene expression levels: highly expressed genes  greater than 10), moderately expressed genes , lowly expressed genes , and silenced genes . As shown in Fig. pus Fig. , which mcis-regulatory elements (CREs) are generally embedded in ACRs that can be integrated by trans-regulatory proteins to regulate gene expression, we identified over-represented motifs from ACRs of each genotype. In total, 82, 84, and 71 motifs and corresponding transcription factor (TF) families  but also repressive histone modification (H3K27me3) were found to be highly enriched around the peak center of ACRs  ACRs was significantly lower than that of Cn  and no biased expression genes (no-BEGs). The distribution of gene expression levels of homeologous gene pairs is shown in Fig. n genes had higher H3K4me3 and H3K27ac levels between 100 bp upstream and downstream of TSS in A-BEGs, whereas Cn genes had higher H3K4me3 and H3K27ac levels between 100 bp upstream and downstream of TSS in C-BEGs, and An genes and Cn genes had similar H3K4me3 and H3K27ac levels in no-BEGs in all genotypes , WGD-derived genes (genes derived from WGD), TD-derived genes (genes derived from tandem duplication), TRD-derived genes (genes derived from transposed duplication), DSD-derived genes (genes derived from dispersed duplication), and PD-derived genes . The TD-, TRD-, DSD-, and PD- derived genes were referred to as small-scale duplicated genes43. As shown in Fig. Allopolyploid 4. Newly formed allopolyploids need to reorganize distinct genomes from different parental species44, which disrupts genetic and epigenomic features5 and results in altered DNA methylation38, histone markers38, chromatin compactness10, sRNA production45, and gene expression38. These whole genome-wide changes contribute to the survival and successful establishment of newly formed allopolyploids46, which are related to novel phenotypic variation48. Investigating the consequences of allopolyploidization across both recent and deep time scales is more conducive to studying the evolutionary processes of polyploidy. In this study, we selected resynthesized B. napus, natural B. napus and their progenitors B. rapa and B. oleracea to explore the evolutionary processes across two different time scales . The genome-wide chromatin accessibility and the potential relationship between chromatin accessibility and gene expression during the new formation and natural evolution process of B. napus were comprehensively analyzed.Allopolyploids have long been thought to be more likely to establish and have a greater contribution to plant divergence due to WGD coupled with interspecific hybridization51. However, there are few studies on the changes in chromatin accessibility and its relationship with gene expression during allopolyploidization. With advances in technologies, genome-wide chromatin accessibility regions can be obtained. In this study, we used the assay for transposase-accessible using sequencing (ATAC-Seq) to detect genome-wide ACRs in natural B. napus, resynthesized B. napus and in silico ‘hybrid’ constructed with their progenitors. A total of 27,965 to 40,913 ACRs were identified in the three genotypes, which is comparable to the number of ACRs in several plant species52. Surprisingly, the ATAC-Seq signal of ACRs in resynthesized B. napus was significantly higher than that in in silico ‘hybrid’ but was significantly lower than that in natural B. napus, which indicated that both allopolyploidization and subsequent evolution increased chromatin accessibility of B. napus. The gACRs increased, whereas iACRs decreased in both synthesized B. napus and natural B. napus compared with the in silico ‘hybrid’. These observations indicated that allopolyploid B. napus with more complex genomes may require closer cis-regulatory elements embedded in gACRs to regulate gene transcription than diploid progenitors. Unlike the majority of identified common ACRs in different cell types of Arabidopsis21, more than half of ACRs were genotype-specific ACRs in our study , resynthesized allotetraploid B. napus L. (HC-2) and its parents B. rapa L. , B. oleracea L. , were obtained from the Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, China. The resynthesized B. napus was generated by embryo rescue and genome doubling of hybrid of B. rapa and B.oleracea. Seeds of the four plant materials were germinated on culture dishes with two layers of moist filter paper in light incubators . Young seedlings with fully unfolded cotyledons were transferred into mixed soil  moistened with 1/2 Hoagland’s nutrient solution (pH: 5.8). The transferred seedlings continued to grow in light incubators and were regularly watered with 1/2 Hoagland’s nutrient solution (pH: 5.8). Young leaves of five-week-old plants were harvested with three biological replicates and frozen immediately in liquid nitrogen.Seeds of natural allotetraploid 63. Briefly, plant leaf tissue was ground in liquid nitrogen, and the grinded powder was washed with PBS and treated with lysis buffer. The nuclei were obtained by density gradient centrifugation for 30 min at 120,000 g in 60% Percoll and 2.5 M sucrose solution. Purified nuclei were resuspended in 50 μl transposase integration reaction and then incubated for 30 min at 37 °C. Tagmented DNA was purified by 2× DNA clean beads and then amplified 15 cycles with i5 and i7 index primers , and then deduplicated reads were aligned to the reference B. napus genome using bowtie2 software (v 2.2.6)65 with default parameters. Samtools (v.0.1.19)66 was used to convert the mapped reads in .sam format to .bam format. Peak calling was carried out by MACS2 software to identify ATAC-Seq peaks41. ATAC-Seq peaks with fold enrichment greater than 3.4 remained for further analysis, and peaks called in this method were referred to as accessible chromatin regions (ACRs). The quantitative difference in common ACRs was calculated by a Python script, and ACRs with |log2 fold change | ≥ 1 and P value < 0.05 were identified differentially enriched ACRs (DEAs). HOMER (v.4.1.0)67 was used to identify the motifs of ACRs. Bedtools (v.2.25.0)68 was used for peak annotation. The genomic distribution of ACRs was identified by ‘annotatePeak’ of ChIPseeker69. For visualization of ATAC-Seq data, the bam files from three biological replicates were merged and sorted by Samtools (v 0.1.19)66. The sorted bam files were converted to bigWig (bw) files by ‘bamcoverage’ in deepTools42. Heatmaps and average plots were generated by the ‘computeMatrix’ followed by ‘plotHeatmap’ and ‘plotProfile’ in the deepTools 2.0.Raw ATAC-Seq data were first trimmed 3’ adaptor, and low-quality reads were removed by Trimmomatic software (v.0.36)6. Raw RNA-Seq data were filtered  by NanoFilt (v.2.5.0) to generate clean data. Pinfish (v.1.0) process was used to analyze clean reads. Firstly, full-length reads were identified by Pychopper (https://hpc.nih.gov/apps/pychopper). Secondly, the full-length reads were aligned to the reference B. napus genome v.5 (http://www.genoscope.cns.fr/brassicanapus/data/) by Minimap2. Then the clustered alignment results were aligned to the reference genome again by Minimap2 to obtain consensus reads. The gene expression levels were normalized by the transcripts per million reads (TPM). DEGs were identified by the DESeq2 method70, and the thresholds were |log2 fold change | ≥ 1 and adjusted P value (padj) ≤ 0.001. GO analysis for genes was conducted by KOBAS software (v 2.1.1), and the terms with corrected P values ≤ 0.05 were inferred to be significantly enrichment GO terms.Third-generation sequencing libraries were constructed by using the same plant materials used for ATAC-Seq with three biological replicates. The process of constructing RNA-Seq libraries can be found in our previous study38. Trimmomatic software (v.0.36) was used to trim the 3’ adaptor and remove low-quality reads from the raw data of ChIP-Seq. The clean data eliminated by FastUniq (v.1.1) were aligned to the reference B. napus genome using Bowtie2 software (v 2.2.6) with default parameters. The ChIP-Seq peaks were identified by MACS2 software. For visualization of ChIP-Seq data, three bam files were merged and sorted by Samtools (v 0.1.19) and then the sorted bam files were converted to bigWig (bw) files by ‘bamcoverage’ in deepTools. Heatmaps and average plots were performed by the ‘computeMatrix’ followed by ‘plotHeatmap’ and ‘plotProfile’ in the deepTools 2.0.The ChIP-Seq libraries were constructed by using the same plant materials used for ATAC-Seq with three biological replicates. The process of constructing ChIP-Seq libraries can be found in our previous studyB. napus genome using BatMeth271. Batmeth2 calculates regional DNA methylation level by weighting the sequencing depth of a region72. The methylation level of each cytosine site is calculated by dividing the methylation reads by the coverage of that site. Locations with coverage of less than 3 were considered missing data. The methylation level of a genomic region is determined by dividing the sum of the methylated reads in that region by the sum of the echo cytosine site coverage.The DNA methylation libraries were constructed by using the same plant materials used for ATAC-Seq with three biological replicates. Genomic DNA was extracted from 12 samples by cetyl trimethylammonium bromide (CTAB) method. The lambda DNA spike-in was used to correct for non-conversion rates of uracil by adding 1 ng of methyl-free lambda DNA to 1 μg genomic DNA as an internal reference for the conversion test. The EZ DNA Methylation Gold Kit  was used to conduct bisulfite conversion of DNA. The Acegen Bisulfite-Seq Library Prep Kit  was used to construct whole genome sulfite sequencing (WGBS) libraries and sequenced on Illumina HiSeq X10 (30-fold sequencing depth). FastQC was used to evaluate WGBS data and Trimmomatic (v.0.36) was used to filter raw reads. The clean reads were mapped to the B. rapa and B. oleracea at a ratio of 1:1, respectively. Data of DNA methylation were mixed in proportion to the genome size of B. rapa and B. oleracea to construct in silico ‘hybrid’38. Three in silico ‘hybrid’ were constructed according to three biological replicates of all sequencing data in each genotype.The in silico ‘hybrid’ was constructed by mixing ATAC-Seq, ChIP-Seq, and RNA-Seq data of https://r-project.org). The wilcox.test function and chisq.test function in the R package were used to implement the Wilcoxon rank sum test and χ2 test.The statistical significance in our study was determined by R (Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplemantary Data 1Supplemantary Data 2Supplemantary Data 3Supplemantary Data 4Supplemantary Data 5Reporting Summary


An analysis at the whole-genome scale in Escherichia coli then demonstrates a significant effect of the spacer length on the genomic expression after transient or inheritable superhelical variations, validating the model’s predictions. Altogether, this study shows an example of mechanical constraints associated to promoter binding by RNA Polymerase underpinning a basal and global regulatory mechanism.DNA supercoiling acts as a global transcriptional regulator in bacteria, but the promoter sequence or structural determinants controlling its effect remain unclear. It was previously proposed to modulate the torsional angle between the −10 and −35 hexamers, and thereby regulate the formation of the closed-complex depending on the length of the ‘spacer’ between them. Here, we develop a thermodynamic model of this notion based on DNA elasticity, providing quantitative and parameter-free predictions of the relative activation of promoters containing a short versus long spacer when the DNA supercoiling level is varied. The model is tested through an analysis of  DNA supercoiling (SC), the level of over- or underwinding of the double-helix, is a fundamental property of DNA. In bacterial cells, the chromosome is maintained at a negative SC level by a finely controlled balance between the relaxing activity of topoisomerase I (and IV), and the introduction of negative supercoils by the DNA gyrase ,2. This At the mechanistic level, SC affects the transcription process at multiple steps, both indirectly through regulatory proteins, and directly by modulating the interaction of RNA Polymerase (RNAP) with DNA . A stronThe latter step involves the binding of RNAP to gene promoters, through specific recognition of the −35 and −10 elements by the 2.4 and 4.2 regions of the σ factor, respectively . The efflac promoter is untwisted prior to open-complex formation  demonstrate the genome-scale relevance of this mechanism by a statistical analysis of high-throughput expression data, which were not available when the previous qualitative models were developed but are particularly suited to this global regulation mode. In spite of the complicating factors mentioned above, these results consistently show that the variability of spacer lengths underpins a global selectivity of promoter activity depending on the cellular SC level, varying either transiently due to topoisomerase inhibitors, or inheritably in the longest-running evolution experiment. Since this regulatory mechanism affects the basal interaction between promoter and RNAP, independently of promoter-specific TFs, it might play a widespread role in the prokaryotic kingdom.In this study, we wish to (i) translate the proposed qualitative notion into a quantitative regulatory model, (ii) develop a rigorous validation of its predictions, based on n and average superhelical level σ:kθ = 71.4 kBT.rad−2 is the DNA sequence-averaged twist stiffness ) to the angle imposed by RNAP (θP/n).We assume that the formation of the closed-complex is limited by an intermediate state where the spacer DNA must be (un)twisted to a favourable relative orientation of the −10 and −35 elements allowing RNAP binding Figure . This detiffness ,32, α0 =leotides , kBT is P = 17 × α0 × (1 − 0.06) = 543°, but most key predictions are independent of its value (see upcoming paragraphs).To illustrate the model predictions Figure  and subsP, its flexibility is neglected in the calculation.In this model, we assume that the total superhelicity σ can be utilised by RNAP for the twist deformation of spacer DNA . This unidimensional approximation of DNA is frequently used in analyses of the regulatory effect of SC ,34, and The total free energy associated to the transcription process is assumed to contain three contributions related, respectively, to the effects of SC, of the spacer element, or of both simultaneously:Gor is the orientational deformation energy  represents all other mechanisms of regulation by SC , which are assumed to be independent of spacer length n, and depend on the specific promoter sequence s (and thus even on elements distant from the spacer). This contribution explains the strong global promoter activation by negative SC in Figures ΔGsp represents all other mechanisms of modulation of transcriptional activity by the spacer DNA, which depend on its sequence as well as its length , but are assumed to be independent of σ. In particular, we assume that the longitudinal distance between −35 and −10 elements may vary depending on the spacer length and sequence (possibly requiring the stretching of the spacer for RNAP binding), but with no SC-dependence, that is, neglecting the twist-stretch coupling of DNA.Δk is the transcription rate, k0 is the basal rate , and kBT is the Boltzmann factor. To simplify the notations, we use the latter as the energy unit in the following. Based on the equations above, the model does not predict the general SC-dependence of a promoter nor the effect of the spacer on the absolute expression level (since both depend on unpredictable terms in Eq. Transcription rates are then computed using a thermodynamic framework :(3)\docuentclass1pt{minimain vitro expression data of mutant promoters , thereby eliminating any other regulatory effect of SC:Qsp. Using a linear expansion in Δn/n0 = (n − n0)/n0 in the first term, the relative expression level of each spacer length simplifies to a linear dependence in σ (Supplementary Eq. S1), as visible in Figure slope of each line is defined without any adjustable parameter, and is proportional to the torsional stiffness of DNA and to Δn = n − 17. The intercept depends on the global parameter θP, and may also depend on the spacer sequence and length due to Qsp.From s Figure , we isolentclass1pt{minimain vivo data (from mutant promoters or transcriptomics data) involve relative expression levels (fold-changes) induced by a global superhelical variation σ0 → σ0 + Δσ (induced by antibiotics or mutations). The predicted value is given in Supplementary Eq. (S2), where the spacer length-dependent term does not depend on any unknown parameter. After linear expansion in Δσ, the relative effect of the superhelical variation on spacer length mutants of the same promoter s is entirely predictable and independent of σ0 :n but differ by their overall sequence s, and the resulting term (Rsc in Supp. Eq. S2) remains in the form of strong statistical noise , and individually cloned into pUCTer-luc plasmids upstream of a luciferase reporter gene (luc) (E. coli strain MG1655 cells were then transformed with these plasmids using a standard electroporation procedure. The measurement protocol is described elsewhere (E. coli cells carrying the plasmids with the different promoters were grown at 37°C in LB medium in a microplate reader (Tecan Spark). The OD600nm and luminescence were measured every 5 min to follow bacterial growth and promoter expression, respectively. DNA relaxation was induced by injecting 5 μl of novobiocin , whereas an increase in negative SC was induced by injecting 2 μl of seconeolitsine  (E. coli (230 bp sequences upstream of the ne (luc) . E. colilsewhere . Briefly tested) . The res. The 19-nt spacer data of Aoyama et al.  = 1.1 kBT (Supplementary Eq. S1), corresponding to a factor 3 in expression. A putative interpretation of this additional cost is the elastic  energy required in the spacer to match the distance between RNAP binding sites (contained in ΔGsp in Eq. 2).In Figure a et al.  were fitpheP-derived promoters were reproduced , was estimated from the repression (novobiocin) and activation (seconeolitsine) level observed with the 17-nt spacer, with values Rsc = 0.4 kBT and Rsc = −0.97 kBT corresponding to activation factors of 0.67 and 2.1, respectively . For transcriptomes of E. coli evolved strains, a less stringent P-value threshold (0.1) was applied to have enough statistical power for the analysis , we assume these other regulatory effects to be independent of the spacer length. Similarly, all other mechanisms by which the spacer length and sequence modulate transcriptional activity  are assumed to be independent of the superhelical state of the promoter preceding RNAP binding. Based on these simplifying assumptions, the modulation of the torsional angle between the −35 and −10 hexamers is the only mechanism of The first prediction is the quantitative magnitude of this regulatory contribution. Geometrically, the large size of the spacer around 17 nt) compared to that of many dimeric TFs  implies that physiologically relevant superhelical variations (of around ±0.06) are sufficient to induce a quantitative regulatory effect . In turn, this regulatory effect is tuned by the mechanical cost of aligning an ill-oriented spacer , where n is the spacer length. In particular, the slope of the 19-nt spacer line is twice that of the 18-nt one (both activated by negative SC), and similarly for 15- and 16-nt spacers with negative values (repression by negative SC). Remarkably, the datapoints from two independent datasets obtained with different promoters (with 18- and 19-nt spacers) align along the predicted slopes without any adjustment. Since these slopes reflect the torsional elasticity of DNA, this observation gives a strong support to our hypothesis that this elasticity is indeed the key regulatory parameter in this process .In order to rigorously test the model, we developed an analysis of previously obtained romoters  and PSC-romoters  were preromoters  exhibit romoters  and posset al. , 15-nt (two deletions) or 19-nt spacer  the maximal expression peak of pheP, in order to obtain reproducible (opposite) fold-change values with the two drugs. As a result, the growth stages of the cells might differ slightly between the two experiments, with only minor effect expected . For all other spacer lengths, since the proposed mechanism relies on the basal interaction between RNAP and promoter elements, we then wished to enlarge the analysis to the entire genome of E. coli, in order to test its validity and relevance at the global scale.The native n Figure , in agren Figure , and wasn Figure ; both efn Figure , as in tE. coli, based on an available curated promoter map . Accordingly, classifying the promoters based on their spacer length . The relatively high level of noise is due to the heterogeneity of promoter sequences within each group, and also likely to a fraction of inaccurately annotated promoters, since a single-nucleotide resolution in the definition of −10 and −35 hexamers is required for an accurate analysis but not always achieved, especially since the −35 element is not always well-defined  was fixed before 2000 generations, and a second mutation (in fis) before 20 000 generations, both leading to an inheritable increase of negative SC  and 20 000 generations . The signal is significant but slightly weaker than that observed with antibiotics  could be decoupled from both (i) further regulatory effects of SC (assumed to be independent of the spacer length) and (ii) further modulating effects of the spacer length and sequence (assumed to be independent of SC). These hypotheses, already supported by a collection of qualitative observations on individual promoters , are val Figures  and 4B.  Figures ,13,59.E. coli, subject to stringent control . These experience a strong repression by ppGpp as well as DNA relaxation occurring in the cell upon transition to stationary phase (P < 0.001), suggesting a tight relation between both properties, and defining a subclass of promoters containing 16-nt long spacers and G/C-rich discriminators. It is conceivable that this subclass experiences a specific pathway in transcription initiation, responsible for its peculiar SC-sensitivity beyond the range of our model. Indeed, increasing the spacer from 16- to 17-nt enables the formation of an intermediate state with untwisted -10 element (but no opening of the promoter), which might then provide torsional energy facilitating the melting of the downstream region during open-complex formation  operon encoding components of the mercury (Hg) resistance system  causes a conformational change in MerR and, in turn, the untwisting of DNA and reorientation of -35/-10 sites for effective open-complex formation twisting of the spacer has been proposed as the mechanistic basis for the regulatory action of several TFs, including MerR, which regulates the , or both. Imposing a sequence-averaged value to either of these two parameters (Apart from the limitations mentioned above, we only considered how SC modulates the relative torsional orientation of −10 and −35 elements depending on the spacer length, and neglected any effect of its base sequence. However, the latter has been shown to affect the transcriptional activity of various promoters . The torE. coli , confirmrameters  showed trameters . The seqgkac579_Supplemental_FileClick here for additional data file.


Catsper2 gene are associated with the deafness‐infertility syndrome (DIS) and non‐syndromic male infertility. However, the mechanisms by which Catsper2 is regulated are unknown. Here, we report the characterization of the promoter region of murine Catsper2 and the role of CTCF and CREMτ in its transcription. We report that the promoter region has transcriptional activity in both directions, as determined by observing luciferase activity in mouse Sertoli and GC‐1 spg transfected cells. WGBS data analysis indicated that a CpG island identified in silico is non‐methylated; Chromatin immunoprecipitation (ChIP)‐seq data analysis revealed that histone marks H3K4me3 and H3K36me3 are present in the promoter and body of the Catsper2 gene respectively, indicating that Catsper2 is subject to epigenetic regulation. In addition, the murine Catsper2 core promoter was delimited to a region between −54/+189 relative to the transcription start site (TSS), where three CTCF and one CRE binding site were predicted. The functionality of these sites was determined by mutation of the CTCF sites and deletion of the CRE site. Finally, ChIP assays confirmed that CREMτ and CTCF bind to the Catsper2 minimal promoter region. This study represents the first functional analysis of the murine Catsper2 promoter region and the mechanisms that regulate its expression.CATSPER2 (Cation channel sperm‐associated protein 2) protein, which is part of the calcium CATSPER channel located in the membrane of the flagellar principal piece of the sperm cell, is only expressed in the testis during spermatogenesis. Deletions or mutations in the  Catsper2 promoter region and identify a CpG island in silico. ChIP‐seq data analysis revealed that histone marks H3K4me3 and H3K36me3 are present in the promoter and body of the Catsper2 gene. Finally, CTCF and CREMτ bind to the Catsper2 core promoter and regulate its expression.CATSPER2 is necessary for sperm hyperactivation and male fertility. Here, we report the characterization of  CATSPERcation channel of spermCATSPER2cation channel sperm‐associated protein 2CREcAMP response elementCREMcAMP responsive element modulatorCREMτcAMP responsive element modulator isoform τCTCFCCCTC‐binding factorEPDeukaryotic promoter databaseWGBSwhole genome bisulfite sequencingMus musculus) 588 a.a. protein that shares 67% identity with human CATSPER2. Along with other three trans‐membrane subunits , five auxiliary subunits  and an EF‐hand calcium‐binding domain‐containing protein 9 (EFCAB9) compose the calcium channel located in the membrane of the flagellar principal piece of spermatozoid. Disruption of any CATSPER subunit produces male infertility by disturbing calcium concentration and preventing sperm hyperactivation [Catsper gene expression varies through spermatogenesis; while Catsper1,3 and 4 are expressed in spermatids at late stages, Catsper2 is found in primary spermatocytes at earlier stages, suggesting an essential role for Catsper2 in the regulation of the other Catsper members [Catsper2 gene have been associated with patients with the deafness‐infertility syndrome (DIS) or non‐syndromic male infertility, highlighting the importance of Catsper2 gene in human male fertility. [Catsper2 in male fertility is well established, the mechanism by which this gene is transcriptionally regulated is unknown. We previously reported that the cAMP Responsive Element Modulator τ isoform (CREMτ) regulates the CATSPER1 promoter activity in vitro [Crem gene that contains a basic region and leucine zipper domains for CRE site recognition and DNA binding, in addition to 3 activation domains  for transcriptional activation [Cremτ knockout mice exhibit male infertility due to post‐meiotic cell arrest and increased apoptotic germ cells [Cremτ knockout mice [Ctcf conditional knockout male mice are unable to procreate offspring, have smaller testes than wild‐type mice, and lots of genes, including Catsper2 were downregulated in these mice as shown by microarray assay [Catsper2. In this study, we report the functional analysis of the murine Catsper2 promoter region. The results indicate that CREMτ and CTCF transcription factors transactivate Catsper2 promoter through the binding to specific sites of the core promoter. Regulation of Catsper2 promoter by these factors may be crucial in mediating its specific expression in male germ cells.CATSPER2 (Cation channel sperm‐associated protein 2), which has a sperm‐specific expression, is a mouse  of the Center for Research and Advanced Studies (CINVESTAV), Mexico City, Mexico. Surgery was performed in accordance with the Ethical Guidelines and Procedures from the CICUAL. First, mice were euthanized by cervical dislocation, lower abdomen was then opened with surgical scissors and testes were exposed by pulling the epididymal fat. Later, testes were extracted, and tunica albuginea was removed with bistoury and finally washed with cold 1× PBS.All the animals used in this work were bred according to the animal protocol 0113‐14 approved by the Internal Committee for the Care and Use of Laboratory Animals (CICUAL). CD1 mice were kept in polysulfonate cages with male mice, maintained in a 12 h light/dark cycle and provided with food and water CREMτ transcription factor, RT‐PCR was performed from mouse testis; total RNA was extracted using the TRIzol® reagent , according to the manufacturer's instructions. The cDNA was prepared from total RNA using a High‐Capacity cDNA Reverse Transcription Kit . PCR reactions were conducted with 1 U Phusion DNA Polymerase , 1× buffer HF, 200 mm dNTPs, 0.2 μm primers (Table CREMτ open reading frame (ORF) was cloned into pjet 2.1 blunt vector and then subcloned into pcDNA3 expression vector (pcDNA3‐CREMτ).For cloning https://epd.epfl.ch//index.php) was used to predict the putative promoter region of the murine Catsper2 gene. The gene‐specific primers  including the transcriptional start site (+1). PCR amplification was performed using genomic DNA from CD1 mouse testis as a template and Phusion DNA Polymerase . The 1598‐bp fragment of the putative Catsper2 promoter was cloned into pjet 1.2 blunt vector. This region was used as a template for amplifying a 798‐bp fragment containing a shorter promoter region  were subcloned in sense (pCat2‐1598 and pCat2‐798) and antisense (pCat2‐1598AS and pCat2‐798AS) directions using two flanking HindIII sites into the Photinus luciferase reporter vector pGL4.10. The potential TF‐binding sites were identified using promo  and tf‐bind (https://tfbind.hgc.jp) and CpG islands were predicted with methprimer (http://www.urogene.org/methprimer/). Sequence alignment was performed using clustalx v2.1 .The Eukaryotic Promoter Database . The extracted sequences were mapped to the mouse reference genome (mm10) with bowtie2 (version 2.3.5.1) [macs2 [deeptools suite (version 3.3.2) [Catsper2 gene and promoter region were plotted. Only the run with a higher number of spots for the samples with duplicate experiments was analyzed.ChIP‐seq data collected from the NCBI GEO and the sequence read archive (SRA) databases Table  were ana2.3.5.1) . The ali) [macs2  with – nn 3.3.2) ; the norin silico, whole‐genome bisulfite sequencing (WGBS) data were collected from ENCODE project in BigWig format [Catsper2 promoter region in spermatogenic cells and control tissues were plotted.To analyze and compare the methylation status of the CpG island found g format , 31. TheCatsper2 promoter were constructed using primers: Cats2F/−509_Cats2R/+189, Cats2F/−215_Cats2/+289, Cats2F/−54_Cats2R/+289, Cats2 P4/Cats2 P‐Rev2 (−54/+189) and Cats2 P5/Cats2 P‐Rev (+3/+289). PCR fragments were generated using pCat2‐798 as a template, cloned into pjet 1.2 blunt vector, and subcloned in sense containing XhoI and HindIII sites into pGL4.10 vector. These plasmids were named pCat2‐698, pCat2‐504, pCat2‐343, pCat2‐243 and pCat2–287, respectively. The integrity and orientation of all constructions were confirmed by automatic DNA sequencing with RVPrimer3 and Luc2Rev primers  with the appropriate primers Table . PCR was−1) and Streptomycin  and incubated at 37 °C in a humidified atmosphere with 5% CO2. Cells grown to 80% confluency were seeded in 24 well plate (1 × 105 cells per well) 24 h before transfection. Cell transfections were performed with the K2® Transfection System  according to the manufacturer's protocol with 500 ng of Catsper2 reporter plasmids. Co‐transfections were made using 250 ng of Catsper2 promoter plasmids and 250 ng of CREMτ‐expressing (pcDNA3‐CREMτ) or CTCF‐expressing vector  and 0.4 ng of pRL‐CMV normalization vector. The pGL4.10‐CMV and empty pGL4.10 vectors were used as positive and negative controls, respectively.Type B spermatogonia GC‐1 spg and mouse Sertoli MSC‐1 cell lines were cultured in DMEM  supplemented with FBS 10%, Penicillin (5 U·mLTwo days (48 h) after transfections, cells were washed with sterile 1× PBS and lysed, and the transcriptional activity was quantified using the Dual‐GLO Luciferase Assay System  as described in the manufacturer's protocol. The relative luciferase activities were measured with a Fluoroskan Ascent reader . Luciferase activity was normalized to pRL–CMV activity and expressed as fold change relative to the activity of empty vector pGL4.10 (defined as 1). Data are presented as mean ± SEM of three independent experiments in triplicate.m PMSF and Complete 1× , and protein concentration were determined by Bradford method . Protein samples were separated by 10% SDS/PAGE and subsequently transferred to a Polyvinylidene difluoride membrane . Membranes were blocked with 5% ProPure milk  in TBS‐T buffer  1 h and then incubated overnight with antibody diluted in blocking buffer including Santa Cruz  antibodies anti‐CTCF (sc‐271474) anti‐CREM (sc‐39426), anti‐MYC (sc‐40), 1 : 500 dilution and anti‐GAPDH (sc‐365062), 1 : 1000 dilution. Finally, for CREMτ assay, membranes were incubated with a rabbit Anti‐Mouse IgG Polyclonal Antibody, Horseradish Peroxidase (HRP) conjugated  1 : 3000 dilution in blocking buffer for 1 h. The peroxidase was developed using Immbilon Forte Western HRP substrate . For CTCF assay, membranes were incubated with AP‐Goat anti‐Mouse IgG  1 : 1000 dilution in blocking buffer for 1 h and the bands were developed with BCIP®/NBT Liquid Substrate System .Total protein was extracted from GC‐1 spg cells 48 h after transfection with RIPA buffer containing 1 mn = 3). The ChIP assay was performed according to the X‐ChIP protocol from the Abcam protocols book (https://docs.abcam.com/pdf/misc/abcam‐protocols‐book.pdf) with minor modifications. Briefly, the complexes were preserved by fixing the cells in 1% formaldehyde for 30 min at room temperature and neutralization with glycine. The cells were then washed, lysed, and sonicated to shear DNA into fragments of 200–1000 bp; 10% was saved as input. DNA‐protein complexes were immunoprecipitated with 2 μg CTCF , CREM , or irrelevant IgG MHC Class II  antibody overnight at 4 °C. The immune complexes were isolated with protein G agarose beads , eluted with salts, and finally, the crosslinking was reversed and digested with proteinase K. The DNA was then purified with the phenol‐chloroform method. The binding of transcription factors to the Catsper2 promoter was assessed by standard PCR using the primers listed in Table imagej software (https://imagej.nih.gov/ij/index.html), quantified as electronic density (pixels) and plotted as IgG relative expression. Data are presented as mean ± SEM of three independent experiments.Protein‐DNA complexes were prepared from the testis or liver of adult mice . One‐way ANOVA and paired Student's t‐test were used to determine significant differences. Data show mean ± SEM (n = 9) from three independent experiments performed in triplicate; P < 0.05 was considered statistically significant.Statistical analysis was performed using Catsper2 promoter region was analyzed using The Eukaryotic Promoter Database. Two putative promoters of 601 and 784 bp were found, between −1289 to −689 and −500 to +284 relative to +1 transcription start site, respectively. The putative Catsper2 promoter sequence containing the 1598 bp region (−1309 and +289) was obtained from the National Center for Biotechnology Information (NCBI) and further analyzed to search for regulatory elements. The promoter region near Catsper2 contained neither a TATA consensus box nor a CCAAT consensus box near the TSS. In addition, a CpG island from −536 to +189 was detected with the methprimer software  revealed a transcriptional activity of 11.7‐ and 100.2‐fold increase in GC‐1spg and MSC‐1, respectively  contains a functional promoter. In addition, pCat2‐1598AS and pCat2‐798AS constructs containing putative Catsper2 promoters in antisense also exhibited a transcriptional activity. The first construct showed an increase of 6.9 and 71.0 in GC‐1 spg cells and MSC‐1, and the second 17.2 and 103, respectively, suggesting that the divergent Pdia3 gene promoter overlaps with Catsper2 promoter or alternatively, Catsper2 promoter may be bidirectional.The fragments containing the putative promoters, the 1598 bp (from −1309 to +289) and 798 bp (−509 to +289) regions were cloned upstream of the luciferase reporter gene in pGL4.10 vector  generated a 2.3‐fold increase in transcriptional activity in GC‐1 spg cells compared to the pCat2‐798 construct, and no change was observed in MSC‐1 cells  indicates the presence of three CTCF sites  and one CRE binding site , and a CRE site (ΔCRE) was deleted in the core promoter of Catsper2 (pCat2‐243) by site‐directed mutagenesis  transcriptional activity, respectively Fig. , suggestite Fig. . Regardiite Fig. . These rCatsper2 promoter activity, possibly by binding to their specific sites in the core promoter. Therefore, ChIP assays were performed to assess the interaction of CTCF and CREMτ with Catsper2 core promoter in vivo. Fragmented DNA from testes or liver chromatin was precipitated with anti‐CTCF, anti‐CREM or irrelevant anti‐MHC Class II (IgG) and then subjected to PCR.The aforementioned results suggest that CTCF and CREMτ regulate Catsper2 core promoter for both transcription factors in the testis samples. No signal was detected with the control MHC Class II antibody  or non‐syndromic male infertility [Catsper2 promoter region and some of the mechanisms that may be involved in its tissue‐specific expression. We found in silico the putative promoter in a region of approximately 1600 bp that includes the transcriptional start site (TSS +1); although, the transcriptional functional proximal promoter was delimited to a region of about 800 bp. An interesting finding was the transcriptional activity of the promoter region of Catsper2 in antisense consistent with the head‐to‐head gene display of Pdia3 in the mouse genome assembly GRCm39, which unlike Catsper2 is a ubiquitous gene [Pdia3 gene is found in the same region. Alternatively, Catsper2 promoter may behave as a bidirectional promoter, as reported for some promoters whose genes are expressed in spermatogenesis [d humans , 15, 44;ertility , 14, 15;ous gene , 39. Theogenesis , 45, 46.Catsper2 promoter region in testis, late‐spermatocytes, and early spermatids was observed by ChIP‐seq data analysis. This evidence agrees with the reported Catsper2 expression pattern in these cells [Pdia3 gene. In contrast, Catsper2 transcription may be regulated by other epigenetic mechanisms as well as by specific transcription factors during spermatogenesis.H3K4me3 mark has been widely related to active promoter regions , 36, 37.se cells , 44; howCatsper2‐Pdia3, which appear to be regulated by the same promoter region since our luciferase assays showed that this region has transcriptional activity in both directions. According to ChIP‐seq data analysis, the presence of H3K36me3 on Catsper2, in contrast to Pdia3, is only found in testis, suggesting that H3K36me3 mark may be one of the factors contributing to the tissue‐specific expression of the Catsper2 gene.H3K36me3 is a histone mark, that has been related to transcription elongation and bidirectional promoters , 41. BidCatsper1, a CpG island was predicted by bioinformatic analysis in Catsper2 promoter [Catsper2 promoter. Additionally, the histone methylation marks in Catsper2 promoter region derived from ChIP‐seq data analysis are consistent with the genome‐wide studies that have associated promoter regions containing high CpG dinucleotide frequency with the H3K4me3 modification [Catsper2 promoter region.Unlike promoter . Most ofpromoter  and havefication . The samCatsper2 comprises a 243 bp region (−54 to +189), including part of exon 1. Previously, the minimal promoter of murine Catsper1 was found in a 394 bp region (−287 to +107), which also includes more than 100 bp of the first exon [Catsper1‐4 gene promoters. Transcription factors regulating a promoter are usually conserved in different species [Catsper2 minimal promoter region reveals that all four predicted TFs binding sites (one CRE and three CTCF) are conserved among mouse, rat and human species.Transcription factors also play a fundamental role in the regulation of gene expression ; and therst exon , suggest species . Indeed,Catsper2 promoter (+152).CRE sites are approximately 150 bp near the TSS in haploid germ cells, and 40% of these sites are known as half‐CRE since only half of the bases of the CRE consensus sites are found ; this isCatsper1; however, most are expressed in post‐meiotic stages [Catsper2 minimal promoter under CREMτ overexpression, where CREMτ surpasses the endogenous repressor isoforms to bind CRE site. As spermatogenesis progresses and the levels of CREM repressor isoforms decrease, Catsper2 transcription starts, and later, in the post‐meiosis stage, CREMτ can use the CRE site of the Catsper2 promoter to increase its expression levels; however, further investigation needs to be done to confirm this hypothesis.CREMτ activates various genes during spermatogenesis, including c stages , 58, 59.c stages ; so, delCatsper2 promoter activity, indicating that these sites are essential in regulating this promoter. According to the results of the mutant CTCF binding sites, CTCF2 is the most relevant site for Catsper2 minimal promoter since its mutation dramatically reduces the transcription and the specific factor fails to increase the activity to the levels of the wild‐type promoter sequence or mutant CTCF1 construct. Another interesting result to highlight is that CTCF3 site does not influence the basal activity of Catsper2 minimal promoter, but for an unknown reason it prevents a greater transcriptional activation by CTCF protein through the CTCF1‐2 sites, leading to an enhanced activity of Catsper2 promoter containing the mutant CTCF3.On the contrary, of all the CTCF sites in the genome, only 6% contain all four modules, 38% the core motif plus another module, and the rest only the core motif . MutatioCatsper2 expression.In addition, the presence of CTCF‐binding sites has also been associated with promoters containing the H3K4me3 mark , demonstCatsper2 since the binding of both transcription factors to the basal Catsper2 promoter only takes place in the testis according to the ChIP assay.Finally, the regulatory mechanisms described here may be part of tissue‐specific regulation of Catsper2 gene in the mouse model and spermatogonia cells. Our analysis suggests that the Catsper2 promoter is under epigenetic regulation through H3K4me3 and H3K36me3 histone marks and a CpG island. Finally, our results show that this promoter region is regulated by the transcription factors CTCF and CREMτ; however, the exact molecular pathway and cellular stages have yet to be elucidated.Here, we show the first evidence for transcriptional regulation of The authors declare no conflict of interest.All the authors were involved in the overall study design. JH‐S, NO, MLB‐H, APC‐M, and SFL‐G conceived the experiments; APC‐M and SFL‐G conducted the experiments, analyzed the results, and drafted the manuscript; JH‐S, NO, APC‐M and SFL‐G reviewed the manuscript. All the authors have read and agreed to the published version of the manuscript.