Asxl2 in mouse embryonic stem cells (ESCs), a pervasive gain of H2AK119ub1 is coincident with increased PRC1 sampling at chromatin. Accordingly, PRC1 is significantly lost from a subset of highly occupied promoters, leading to impaired silencing of associated genes before and after lineage differentiation of Asxl2‐null ESCs. Therefore, our study highlights the importance of genome‐wide H2AK119ub1 restriction by PR‐DUB in safeguarding robust PRC1 deposition and its roles in developmental regulation.Polycomb group (PcG) proteins are critical chromatin regulators for cell fate control. The mono‐ubiquitylation on histone H2AK119 (H2AK119ub1) is one of the well‐recognized mechanisms for Polycomb repressive complex 1 (PRC1)‐mediated transcription repression. Unexpectedly, the specific H2AK119 deubiquitylation complex composed by additional sex comb‐like proteins and BAP1 has also been genetically characterized as Polycomb repressive deubiquitnase (PR‐DUB) for unclear reasons. However, it remains a mystery whether and how PR‐DUB deficiency affects chromatin states and cell fates through impaired PcG silencing. Here through a careful epigenomic analysis, we demonstrate that a bulk of H2AK119ub1 is diffusely distributed away from promoter regions and their enrichment is positively correlated with PRC1 occupancy. Upon deletion of  A model for understanding why PR‐DUB acts as a PRC despite of an opposite biochemical activity against PRC1. PR‐DUB prevents H2AK119ub1 at the genome wide. Upon delimitation from PR‐DUB, increased H2AK119ub1 activity at non‐promoters is associated with favourable yet unstable RING1B occupancy. Accordingly, PRC1 is diluted from highly occupied promoters, leading to impaired PRC silencing. Epigenetic regulators are central players for the inheritance and flexibility of transcriptional programmes. Among them, Polycomb group (PcG) proteins are evolutionarily conserved chromatin repressors and critical for the maintenance of cell memory. The deregulation of PcG functions has been shown to cause aberrant differentiation and development and human diseases including cancers.Biochemically, PcG proteins usually form multi‐subunit transcription repressive complexes, known as Polycomb repressive complexes 1 and 2 (PRC1 and PRC2). PRCs are preferentially deposited at inactive promoters to maintain target gene silencing through either histone modifications or chromatin compaction.Drosophila.Drosophila.Ever since H2AK119ub1 was found to be catalysed by PRC1‐like complex or ncPRC1,Asxl2‐null cells leads to widespread re‐localization of PRC1 from dominantly repressed promoters to acquired weak occupancy sites and thereby undermines gene silencing. Taking advantage of lineage differentiation models, we show that ASXL2 loss causes aberrant lineage specification, a typical phenotype of PcG mutants. These findings provide a novel insight into how PR‐DUB restricts H2AK119ub1 and prevents PRC1 roaming so as to safeguard PcG functions.Here we generate PR‐DUB or PRC1 inactivation mESC models to re‐examine the roles of H2AK119ub1. Interestingly, we find that H2AK119ub1 is enriched far more than at promoters and its levels at non‐promoter regions are associated with low levels/frequencies of RING1B binding. The pervasive gain of non‐promoter H2AK119ub1 in 22.1Asxl2 KO ESCs through CRISPR/Cas9 technique were performed as previously described.l‐glutamine, 1× penicillin/streptomycin, 1× non‐essential amino acids, 0.5 mM β‐mercaptoethanol and 100 U/mL leukaemia inhibitory factor. To delete Asxl2, the specific sgRNA was designed to target Exon 5 of mouse Asxl2 and cloned into pX458 vector (Addgene #48138). Then the parental ESCs were transfected with 10 μg of the sgRNA vector with Lipofectamine 3000. The successfully transfected cells were sorted for GFP expression in 48 h after transfection. Around 500 GFP‐positive cells were seeded on 10 cm dishes. After 10 days culture, single colonies were picked and expanded for another 7 days before harvesting for genome DNA extraction. The positive clones were validated by sanger sequencing. As no animal experiments were performed in this study, ethical considerations were not required.Mouse ESC culture and the generation of 2.2The differentiation was performed as described.5 cells were seeded on 0.2% gelatin‐coated 10 cm plates and cultured with differentiation medium containing 10 ng/mL vEGF, 20 ng/mL a‐Activin A, 5 ng/mL BMP4 for another 3 days. Then cells were harvested for RNA extraction or chromatin preparation.For mesoderm precursor cells (MES) differentiation, EBs harvested from dish covers were dissociated after trypsinization. Around 5 × 102.3RpO using the ΔCt method. Primer sequences are listed in Table Total RNA was extracted with TRIZOL (Invitrogen). Reverse transcription and quantitative real‐time polymerase chain reaction (RT‐qPCR) were performed as described.2.47 cells were crosslinked with 1% formaldehyde for 10 min at room temperature (RT) and then quenched with 0.125 M glycine for another 5 min. Then cells were washed with ice cold PBS and lysed in SDS buffer . After spinning, nuceli were resuspended in appropriate volume of ice‐cold IP buffer  for sonication using a BioRuptor sonicator (Diagenode). After centrifugation at 16,000g for 20 min at 4°C, the fragmented chromatin was divided into different aliquots that were incubated overnight with primary antibodies  containing Triton X‐100 (0.5%) and ethylene glycol tetraacetic acid (1 mM) on ice for 5 min. The pre‐extracted cells were then proceeded with regular chromatin preparation. The IP buffer was dialyzed to lower SDS concentration to 0.01% followed by standard IP assays with H2AK119ub1 antibody (CST 8240S). After reversal of the crosslinking, ChIP DNA was purified for qPCR analysis.For H2AK119ub1 ChIP, pre‐extraction steps were performed before fixation.2.62, 1 mM CaCl2), followed by mixing with the cells at RT for 15 min. The supernatant was then removed and beads were resuspended in 100 μL antibody buffer . Then 1 μg H2AK119ub1 antibody was added and incubated overnight at 4°C. On the next morning, the supernant containing primary antibody was removed and the beads were incubated in 100 μL of dig‐wash buffer  containing the secondary antibody at RT for 1 h. Then the pellets were washed in 800 μL dig‐wash buffer for three times. Meanwhile 1:200 dilution of pA‐Tn5 adapter complex (~0.04 μM) was prepared in Dig‐300 Buffer . Then the beads were incubated with pA‐Tn5 at RT for another 1 h. After washing three times by Dig‐300 buffer, the pellets were resuspended in 50 μL tagmentation buffer (10 mM MgCl2 in Dig‐300 Buffer) and incubated at 37°C for 1 h. Then stop buffer  was added and incubated at 50°C for 1 h. To extract DNA from the reaction, 300 μL hydroxybenzene–chloroform–isoamyl alcohol were added, thoroughly mixed and centrifuged for 5 min at 16,000g. The aqueous phase was collected and mixed with 300 μL chloroform. After centrifuging for another 5 min at 16,000g, aqueous phase was then mixed with 750 μL ethanol overnight at 4°C. The samples were centrifuged for 15 min at 16,000g at 4°C. After being washed twice in 1 mL 80% ethanol, the DNA was resuspended in 22 μL TE buffer and used for library amplification (Vazyme).WT or KO cells were washed twice in wash buffer . Meanwhile Concanavalin A beads  were activated by washing twice in binding buffer  and CUT&Tag data according to standard pipelines.2.9M value, p‐value and read density for each sample were calculated. M‐Value indicates log‐transformed fold change of normalized read density between two samples and p‐value describes the statistical significance of read intensity difference between the two samples being compared. M‐Value was also used to generate boxplot visualization.To calculate peak intensity, the ChIP‐seq or CUT&Tag signals were extracted from RPGC‐normalized coverage track (bigWig) and averaged according to the top five signal values for each of peaks. To calculate read density in a given region, deepTools was used. Moreover, comparisons between paired ChIP‐seq peak signals at different conditions were performed by MAnorm,2‐transform to all the signals. Then we used pheatmap, an R package, to cluster the signals and plot the heatmap.To visualize and compare the signals across the genome, we segmented the genome into 2‐kb bins and used the binnedAverage function of GenomicRanges, an R package, to calculate the average density in each bin from the normalized coverage track (bigWig) files. For better visualization, we applied log2.102 fold change > 1.5 unless otherwise defined and adjusted p‐value < 0.05 were considered as differentially expressed ones. ComplexHeatmapRNA sequencing (RNA‐seq) datasets were performed using the TOPMed RNA‐seq pipeline.2.11t‐test or Wilcoxon rank sum test, p‐values <0.05 was taken as statistically significant.Statistical analyses were performed using the Student's 33.1Ring1a and Ring1b in mESCs,Mounting evidences by ChIP‐seq have shown that H2AK119ub1 is pretty abundant and widely distributed throughout the genome. In these assays, cells need to be pre‐extracted to expose the epitope before fixation for ChIP.In contrast to significant enrichment of H2AK119ub1 at non‐promoter regions as well as promoters, the occupancy of PRC core members RING1B and SUZ12 at non‐promoters is barely detectable Figure . Nonethe3.2Bap1‐knockout (KO) mESCs,Asxl2‐KO mESCs. The positive mESC clones of Asxl2 deletion were verified by targeted genome sequencing and Western blot (WB) assays , 1177 and 5292 unique H2AK119ub1 peaks emerge respectively from promoters and non‐promoters , where there exists low or no signals in WT mESCs ,s Figure . Accordis Figure . When cos Figure . To prevs Figure . Consists Figure . Furthers Figure . Though 3.3Asxl2 KO mESCs. As shown in Figure q‐value<0.1) showed that a large number of RING1B peaks are gained from non‐promoters while lost from promoters , while remain unchanged at regions without RING1B redistribution . Nevertheless, compared with the promoters with unchanged RING1B binding , the ones with strong decrease of RING1B enrichment  in Asxl2 KO cells are associated with mild but significant gene derepression Considering that PRCs play critical roles in lineage specification, we sought to examine how ASXL2 loss would affect ESC differentiation. Given that ASXL2 is expressed at high levels in heart and s Figure . Furthers Figure  than thene Ring1bI53A7 fAsxl2 loss‐of‐function, we performed RNA‐seq analysis at day 0 and day 5 of differentiation with both WT and Asxl2 KO groups. Based on the differentially expressed genes during differentiation of WT cells, we subcategorized them to three clusters: Cluster 1 defines upregulated genes in MES, Cluster 2 downregulated genes in MES and Cluster 3 unchanged  and Nkx2.5, respectively a mesoderm and cardiac lineage development regulator gene, is negatively affected by ASXL2 loss  in S Figure . GO analS Figure . RT‐qPCR1 Figure . Therefos Figure . It sugg4In the past decades, great efforts have been put into identification of writers and erasers for chromatin modifications and characterization of their functions. Biochemically these modifiers antagonize each other, however they exert more complexed regulatory roles than expected. Here we demonstrate that PR‐DUB and PRC1 coordinate for chromatin occupancy and H2AK119ub1 activity in transcription regulation.It is now well recognized that PcG engages with chromatin and stabilizes the repressive chromatin environment.Asxl2‐null mESCs, accompanied with diffusely gained chromatin occupancy of RING1B. Probably because of constant levels of PcG proteins, the increased occupancy of PRCs at cryptic regions is usually coincident with the decreased enrichment at strong target sites.ASXL1‐mutated leukaemia cellsBap1‐null mESCsBap1 deletion.ASXL1/2 and BAP1 are frequently mutated in human malignancies,Another interesting finding in our study is that RING1B is titrated away from canonical bivalent promoters in It is also worth noting that H2AK119ub1 has been recently found to be associated with transcription responsiveness.In sum, our study has demonstrated that PR‐DUB restricts PRC1‐mediated H2AK119ub1 diffusion on genome and prevents cryptic PRC1 deposition to safeguard PcG repression at promoters. In a broad sense, we provide a paradigm that biochemically antagonistic chromatin modifiers may functionally assist each other for transcription regulation. This study also provides mechanistic insights into derailed epigenetic regulatory network that may be targeted in relevant cancers.Xudong Wu and Mulin Jun Li conceived and designed the research. Rui Li and Yingying Zhao performed most of the experiments and part of the bioinformatic analysis. Dandan Huang and Ye Yuan performed computational analysis. Dawei Huo, Zhongye Dai, Xiaoyu Sun and Xiaozhi Liu assisted with experiments. Kristian Helin provided the ASXL2 antibody. All authors contributed to the writing of the manuscript, read and approved the final manuscript.The authors declare no conflict of interest.Appendix S1. Supporting Information.Click here for additional data file.


A multitude of epigenetic modifications and genetic mutations have been found to play pivotal roles in the development and progression of prostate cancer (PCa). The review article of Kukkonen et al.  providesTo further determine the importance of epigenetic modification in PCa malignancy, it is essential to view DNA methylation as a critical variable. As previously discussed, epigenetic suppression in PCa patients was observed following the promoter hypermethylation of GSTP1. Understanding this mutation allows clinicians to further analyze disease progression, using GSTP1 hypermethylation as a biomarker for PCa’s detection and for determining its suspected development path .Along with DNA methylation, it was found that histone modifications serve as another method regulating PCa gene expression and chromatin structure. Specifically, variations in histone methylation and acetylation lead to epigenetic dysregulation, which contributes to differences in PCa malignancy across patients . Non-codChanges in nucleosome positioning are another essential aspect of PCa evolution. Nucleosomes are largely known for their function as a fundamental structural unit of chromatin in eukaryotic cells. Along with their structural role, nucleosomes notably alter the genes involved in PCa. Nucleosome-remodeling complexes, such as switch/sucrose nonfermenting (SWI//SNF), shift the state of chromatin to enhance or inhibit gene expression. Through the SWI/SNF reading complex, chromatin accessibility is altered so as to shift the structure to a more relaxed state. The subsequent changes in gene expression allow for PCa to be classified as early-stage or late-stage CRPC ,7.The interaction between the aforementioned nucleosome-remodeling complex and androgen receptors (AR) is another crucial aspect of PCa malignancy. Interactions with androgen receptors activate key transcriptional factors that have been associated with the reprogramming of chromatin and progression to CRPC . PreviouWhile new treatments are emerging, there are many aspects to consider when developing cancer therapies, especially the stage of the disease. The transcription of a myriad of critical genes is altered through differences in chromatin accessibility and remodeling complexes, which leads to the advancement of PCa. Variation in the levels of suppressed and accessible chromatin directly affects the balance of transcriptional factor activity. FOXA1 is one critical transcriptional regulator. FOXA1 functions to provide remodeling machinery and other advantageous components in order to suppress chromatin and, consequently, to encourage transcriptional factor binding. As more chromatin is altered to improve accessibility, the disease continues to progress to later, more severe stages ,11.From benign prostatic hyperplasia to development of CRPC, the patterns of chromatin accessibility are vastly different. The disparity in accessible chromatin across the different stages of PCa can be explained by the various enhancers in the expressed genes . FOXA1, The androgen receptor cistrome is also considerably altered during the development of PCa. The androgen receptor cistrome has been known to play an essential role in PCa’s initiation, as well as the evolution toCRPC. The changes in this structure have been associated with modified chromatin configuration, which leads to an enhanced availability of androgen receptor binding sites. The literature suggests that these modifications in structural states are a potential explanation for cells bypassing the effects of cancer treatment .In addition to the importance of structural changes in nucleosome complexes and chromatin, the three-dimensional chromatin organization is another vital factor in PCa. In particular, topologically associated domains (TADs) and chromatin loops are noteworthy examples of 3D chromatin organization that affect gene regulation. Chromatin loops induce the organization of topologically associated domains while also bringing enhancers and promoters closer together so as to enable interaction in the chromatin space. TADs were also found to facilitate the constriction of chromatin loop movement .Studies investigating structure have shown that 3D chromatin structure varies between normal and prostate-cancer-infected cells. For example, the copy number of topologically associated domains was significantly higher in patients diagnosed with PCa. This further drives the development of tumor growth and cancer stage progression, since the topologically associated domains have a multitude of regulatory features to drive cancer-related gene expression, such as increased numbers of androgen receptors, enhancers, and CCCTC-binding factors (CTCF) .Likewise, chromatin loops can potentially regulate the presence of the androgen receptor cistrome. Protein–chromatin interactions, such as those between FOXA1, CTCF, and the androgen receptor, were investigated in a meta-analysis that emphasized the relationship between the expression of prostate-tissue-specific genes and chromatin loop structures. The essential function of loops in gene expression was further demonstrated through studies where the structure was disrupted, for example, through CTCF knockdown .Detailed information about the effects of epigenetic and chromatin dysregulation provide researchers with the opportunity to gain a precise understanding of the differences between PCa stages. Evidence that can be used to classify the specific gene mutations and alterations has allowed clinicians to develop individualized treatment courses. One example can be found in the plausible therapeutic interventions discussed by researchers who investigated the role of SPOP mutations and the NSD gene family in PCa .Epitranscriptomics, such as abnormal N6-methyladenosine regulation, are another essential aspect for understanding the influence of epigenetics on PCa progression . ComprehCurrent trials are ongoing to test medications known as epidrugs, highlighting the need for a more comprehensive understanding of PCa biomarkers. The use of RNA-based assays, such as BROMO-10, can help to classify molecular differences between disease progression stages . By delvThe significant role of chromatin and epigenetic dysregulation in the progression of PCa from benign prostatic hyperplasia to CRPC is highlighted in the literature review of Kukkonen et al. . Alterat


Anabaena sp. PCC 7120  is a master regulator engaged in the modulation of relevant processes including the response to oxidative stress, photosynthesis and nitrogen fixation. Previous differential gene expression analysis of a furC-overexpressing strain (EB2770FurC) allowed the inference of a putative FurC DNA-binding consensus sequence. In the present work, more data concerning the regulon of the FurC protein were obtained through the searching of the putative FurC-box in the whole Anabaena sp. PCC 7120 genome. The total amount of novel FurC-DNA binding sites found in the promoter regions of genes with known function was validated by electrophoretic mobility shift assays (EMSA) identifying 22 new FurC targets. Some of these identified targets display relevant roles in nitrogen fixation (hetR and hgdC) and carbon assimilation processes , suggesting that FurC could be an additional player for the harmonization of carbon and nitrogen metabolisms. Moreover, differential gene expression of a selection of newly identified FurC targets was measured by Real Time RT-PCR in the furC-overexpressing strain (EB2770FurC) comparing to Anabaena sp. PCC 7120 revealing that in most of these cases FurC could act as a transcriptional activator.FurC  from  Ferric Uptake Regulator) proteins are prokaryotic metalloregulators mainly involved in the control of metal homeostasis and the concerted response to oxidative stress [Anabaena sp. PCC 7120 genome holds three paralogs belonging to the FUR family that are called FurA, FurB and FurC. FurC was firstly identified as a member of the family because it showed the distinctive features of FUR proteins [Anabaena sp. PCC 7120 [in vitro the canonical derepression mechanism of PerR proteins which is based on the metal catalyzed oxidation (MCO) process. In this process, FurC was inactivated by oxidation with Fe2+ under aerobic conditions hampering its DNA binding activity. Such inactivation can be prevented by previous incubation with excess of manganese. Later on it was demonstrated that the MCO performed by FurC happened in vivo in Anabaena sp. PCC 7120 cells allowing the derepression of antioxidant enzymes to face oxidative stress situations [2+ in aerobic conditions goes along with the incorporation of an oxygen atom into its structure as its observed for other PerR orthologs [Anabaena sp. PCC 7120 such as the maintenance of the photosynthetic metabolism [Anabaena sp. PCC 7120 led to changes in the composition and efficiency of the photosynthetic machinery and novel FurC targets were described such as the major thylakoid membrane protease FtsH which degrades D1 proteins in photoinhibition processes involved in PSII recycling [FUR  transcriptional profile with that of the wild type strain (Anabaena sp. PCC 7120) under standard and diazotrophic growth conditions. These analyses evidenced that FurC was a global regulator involved in the control of a wide variety of processes including photosynthesis, iron homeostasis, energy metabolism, heterocyst development and nitrogen fixation [hetZ, asr1734, hepC, alr4973-75, nifH2, nifHDK, xisHI and rbrA [furC-overexpressing strain showed an impairment of heterocyst differentiation under combined nitrogen deficient conditions and serious difficulties to grow under diazotrophic conditions [CAAAATCATAACGACTTTG-3´ [Subsequently, differential gene expression analyses were carried out comparing the train EB270FurC trAnabaena sp. PCC 7120. In the present work, we try to expand the direct regulatory network exerted by FurC and decipher new metabolic pathways modulated by this protein. To go further in the knowledge of the FurC regulon, an in silico identification of novel FurC-DNA binding sites was performed scanning the total Anabaena sp. PCC 7120 genome sequence with a more restrictive version of the putative FurC-box defined previously [furC overexpressing strain EB2770FurC and the wild-type Anabaena to study the potential effect of the FurC regulation. Among others, this study unveiled several FurC direct targets displaying important roles in nitrogen and carbon metabolisms.Our previous studies suggested that FurC could be acting as a global player in prxA, ftsH, furC, srxA, nifH2 and ahpC genes [http://meme-suite.org/tools/fimo) [Anabaena sp. PCC 7120 genome (Nostoc sp. PCC 7120 = FACHB-418) using a p-value <1x10-5 as cut-off. Predicted FurC boxes were mapped to annotated CoDing Sequences (CDS) from GenBank assembly . Genes with predicted FurC boxes within -1000 bp upstream (intergenic regions) and +50 bp downstream with respect to its start codon were selected as potential FurC targets. In the cases where occurrences were found in the intergenic region of divergently transcribed genes, the gene with closer CDS to the putative FurC-box was chosen as the potential regulated gene. Gene symbol and protein function of the associated genes of the predicted FurC binding sites were annotated according to the databases KEGG (https://www.genome.jp/kegg/) and the information available in literature.A FurC position-weight-matrix was generated by MEME (Multiple Em for Motif Elicitation) using the six FurC-DNA binding sequences previously identified in the tested promoter regions of pC genes  using thls/fimo) , to idenAnabaena sp. PCC 7120 genome as template and the primers included in 2 and 5% (v/v) glycerol. To assess the specificity of the assay 50 ng of a 150 bp-internal fragment of the gene pkn22 was used as a non-specific competitor The resulting mixture was incubated for 30 min at room temperature. Afterwards DNA fragments were added to the mixture and held for 30 min at room temperature. In all cases the incubated mixtures were loaded into a non-denaturing 6% polyacrylamide gel. Both gel and running buffer included 100 °M MnCl2. Gels were stained with SYBR ® Safe (Invitrogen) and visualized in a GelDoc 2000 device (Bio-Rad). In all assays, the specific binding to the previously recognized FurC target, hetZ, was used as a positive control.Promoter regions used in the analyses consisted of 250–350 bp DNA fragments containing the predicted FurC binding sites and were obtained by PCR, using the Anabaena sp. PCC 7120 and EB2770FurC strains. The EB2770FurC strain is a furC-overexpressing strain that contains the pAM2770FurC plasmid harboring the furC gene downstream the copper-inducible petE (plastocyanin) promoter [-2·s-1 and samples were collected after 48 hours (OD750 = 0.6–0.7). RNA was extracted and purified from 25 ml of each culture following the method described in Sarasa-Buisan et al. 2022 [hetR expression overtime, the RNA samples used were extracted from cultures set up as stated above and collecting the samples at 1, 6, 11, 24 and 48 hours after the beginning of the experiment. To study differential expression under oxidative stress conditions, RNA samples were obtained from cultures set up as stated above but incubating the cell suspensions at an OD750 of 0.4 in the presence and absence of 250 μM H2O2. The samples were collected after 1 hour of H2O2 treatment. RNA extraction and purification of all experiments were performed from 25 ml of each culture following the method described in Sarasa-Buisan et al. 2022 [The RNA samples used for the most of the comparative gene expression experiments performed in this work were extracted and purified as in Sarasa-Buisan et al. 2022 . Brieflypromoter . Three irnpB measured with the same samples [The pool of cDNA was synthesized by reverse-transcription of 2 °g of total RNA using SuperScript retrotranscriptase (Invitrogen) following the manufacturer’s conditions. Real time PCR was performed using the ViiA™ 7 Real-Time PCR System (Applied Biosystems). Each reaction was set up by mixing 12.5 °l of SYBR Green PCR Master Mix with 0.4 μl of 25 °M primer mixture and 10 ng of cDNA template in a final volume of 30 °l. Amplification was performed at 60°C. Negative controls with no cDNA were included. The sequences of specific primers of selected genes are defined in  samples . RelativAnabaena sp. PCC 7120 was scanned by a program trained on previously identified sites. The program, FIMO, compares the sequence of a candidate binding site against the nucleotide tendencies at each position of sequences within the training set. Searching of FurC binding sites was performed with a 19-bp FurC-matrix built through MEME software using as input the six sequences closest to a motif found in promoter regions of genes putatively regulated by FurC  [furC overexpression, and their promoter sequences bound FurC in gel shift experiments [Anabaena sp. PCC 7120  (Anabaena sp. PCC 7120 genome defined as -1000 upstream (intergenic region) and +50 bp downstream the translation start site including two motif occurrences with the closest CDSs corresponding to pseudogenes, whereas interestingly 155 motif occurrences were found outside this region, being 151 located inside the coding regions of genes and 4 located in intergenic convergent regions. The location with respect to the translation start sites of closest CDS is shown in Anabaena sp. PCC 7120 with a p-value lower than a 10−5 threshold are listed in Anabaena sp. PCC 7120, namely asr7140 and asr7090 both encoding both hypothetical proteins. In addition, all the potential FurC targets presented a single predicted FurC binding site in their promoter regions with the exception of all2761 which codes for a hypothetical protein that presents two overlapping predicted FurC boxes. To locate the predicted FurC binding-sites in the promoter regions, the relative position of FurC boxes to the translational start codon (ATG) is shown in In order to identify potential FurC binding sites, the whole genome of eriments , 4, 7. T 1x10-5) . From thpsbZ (asr3992) encoding a PSII structural subunit, fas1 , an ortholog of fas1 from Anabaena sp. strain L31 that seems to be involved in the response of this cyanobacterium to UV-B radiation stress [all1123, one of the paralogs to the N-terminal domain of the Orange Carotenoid Protein (OCP) present in Anabaena sp. PCC 7120 [alr5164 promoter  encoding the NADPH-tiorredoxin reductase C that plays a fundamental role in oxidative stress management and participates in the thermotolerance and regulation of N metabolism [The potential binding of FurC to the predicted sites was addressed by performing EMSA assays with all the promoter regions of novel potential FurC targets that presented a predicted FurC-box listed in n stress  and all1PCC 7120 . HoweverPCC 7120 . Finallypromoter  that corPCC 7120 . In Synethe PSII . Anothertabolism , 19.hetR promoter. HetR is a key regulator in the heterocyst development and it is required for a suitable pattern formation [ancrpB  is a direct target of FurC. Anabaena sp. PCC 7120 possesses two cAMP receptor proteins called AnCrpA and AnCrpB [nifB, hglE or coxBII [Regarding to the “Nitrogen metabolism and heterocyst differentiation” category, FurC was capable of binding to the promoter regions of genes encoding proteins with fundamental roles in the regulation of heterocyst development and nitrogen fixation such as the heterocyst specific ABC transporter, HgdC and, remarkably, the master regulator of the heterocyst differentiation HetR . HgdC taormation –23. EMSAd AnCrpB . AnCrpA r coxBII . HoweverrpB alr23 is a dirrpB alr23 is a dirglgP1  the glycogen phosphorylase involved in glycogen degradation processes, opcA, the enzyme that activates the glucose 6-phosphate dehydrogenase (G6PDH) in the heterocyst and provides reducing power for the nitrogenase and cmpR , encoding a LysR type transcriptional regulator that activates the Cmp bicarbonate transport systems in response to low carbon conditions (see below). Another FurC putative binding sites corroborated in vitro were upstream of genes displaying regulatory functions such as the putative transcriptional regulators Asr2041 and Alr3281 and the Alr2137 sensor kinase   . This genditions , 27. Oth protein .furC-overexpressing strain (EB2770FurC) versus the wild type strain Anabaena sp. PCC 7120. The furC-overexpressing strain was used instead of a furC knockout mutant because previous attempts to obtain the knockout strain performed by our group and other groups were unsuccessful [glgP1, cmpR, opcA, hetR, ancrpB, hgdC, ntrC, degQ3, psbZ, fas1, pheA, dnaENI and zupT). All the tested genes except for ntrC showed altered expression in the furC-overexpressing strain thus confirming their direct regulation by FurC  sit directly on the start codon of the genes. In these cases, although they are found upregulated in the furC-overexpressing strain, the mechanism exerted by FurC on these genes is still unknown.Transcriptional analyses were conducted to compare the expression levels of the selected novel FurC direct targets in a ccessful , 4, 7. T by FurC . Interesg strain . In the  all3914 . This cafurC- overexpressing strain. In one previous work we demonstrated that when FurC acts as transcriptional repressor, this protein follows the classical MCO mechanism of PerR proteins in vivo [ancrpB, glgP1, cmpR and opcA FurC activated genes and prxA as a control of FurC repressed gene was analyzed after the culture exposure to the presence of 250 μM of hydrogen peroxide for 1 hour. The results are included in prxA is repressed under standard conditions whereas in the presence of hydrogen peroxide the expression is derepressed because FurC was released from the prxA promoter  seem to be activated by FurC since their expression increases in the  in vivo . This fapromoter . In the tivation . Howevernditions . This phxidation .hetR suggesting a potential regulation mediated by this transcriptional regulator (hetR upstream region (S1), this was the region firstly analyzed in EMSA assays, yielding a positive result. Afterwards other regions upstream of hetR were also analyzed by EMSA assays with FurC (hetR promoter (S3)  in BG11 medium comparing the EB2770FurC strain with the wild type strain Anabaena sp. PCC 7120  . If the ion Figs  and 4C. PCC 7120 . We foun . If theAnabaena sp. PCC 7120 is essential for our understanding of the scope of the regulation exerted by this protein. Previous work led to the discovery of novel roles of the Peroxide response Regulator beyond the control of oxidative stress management, including the regulation of the photosynthetic metabolism and the heterocyst differentiation [furC overexpressing strain. In the present work an in silico approach has allowed us to obtain a global vision of the extent of the FurC regulon. The bioinformatic search for novel FurC binding sites predicted 210 FurC boxes in the whole genome of Anabaena sp PCC 7120. Interestingly, although it could be considered striking, a considerable number (151) of them were located in internal positions of the CDSs  of NtcA binding regions inside or even downstream of coding regions [B. subtilis [furC-overexpressing strain. Some of these targets displayed key roles in carbon and nitrogen metabolism, photosynthesis and light protection, zinc homeostasis or amino acid metabolism. Carbon and nitrogen metabolisms are tightly coupled in organisms because of a suitable balance of carbon and nitrogen is necessary for optimal growth and proper functioning of the cells [Anabaena sp. PCC 7120, many aspects related to the regulation and control of carbon and nitrogen homeostasis are not yet well defined. The engagement of FurC in the regulatory network of heterocyst development and nitrogen fixation was previously suggested. However, in the present work we found that another three genes involved in nitrogen metabolism and heterocyst differentiation  are also direct targets of FurC. Firstly, hgdC encodes a component of Tol-HgdBC transporter which participates in the formation of HGL layer in heterocyst envelopment [ancrpB encodes a transcriptional regulator that has been suggested to control the expression of genes related to nitrogen depletion [hetR promoter, hierarchically one of the most important regulators in the process of heterocyst development. Despite of its importance, the transcriptional regulation of HetR is barely understood. Until now, NrrA had been described as a direct positive transcriptional regulator of the HetR expression [Anabaena sp. PCC 7120) was also able to bind to the hetR promoter [hetR expression.An accurate prediction of the FurC/PerR regulon in ntiation , 7. Thesthe CDSs . However regions . More re regions . Several regions . Moreovesubtilis  could alhe cells . In cyanhe cells –41. In Aepletion . Surprispression , 43. Bespromoter . In addipromoter  and the promoter , 47. In in vitro to the promoters of three important genes comprised in this functional category named glgP1, cmpR and opcA. In addition, the expression of these genes is upregulated in the EB2770FurC strain. These genes display functions that link both carbon and nitrogen metabolisms which are closely intertwined. GlgP1 is a glycogen phosphorylase which catalyzes the generation of glucose-1-phosphate monomers from the glycogen polymer. Anabaena sp. PCC 7120 vegetative cells store carbon belonging to photosynthesis in form of glycogen which is utilized as source of carbon and energy by cyanobacteria during the night. The heterocyst is able to perform photosynthesis (based on PSI) and generate ATP by cyclic photophosphorylation. On the other hand, it has been suggested that vegetative cells could supply carbohydrates (sucrose) to the heterocyst. Some of these carbohydrates derive from glycogen catabolism, indeed NrrA, a nitrogen-regulated response regulator protein, binds to the glgP1 promoter, controlling glycogen metabolism [alr2877-alr2880 gene cluster encoding a Cmp bicarbonate transporter under carbon starvation conditions [2 allowing the efficient actuation of Rubisco in carbon fixation [rbcl operon (encoding Rubisco) [Anabaena sp. PCC 7120 and is essential for nitrogen fixation because this pathway provides NADPH required for the generation of the reducing power for the nitrogenase in heterocysts [Regarding to carbon metabolism, our results showed that FurC binds tabolism , 49. On nditions . The Cmpfixation . On the Rubisco) . CmpR exRubisco) . FinallyRubisco) , 53. G6Perocysts , 55.furC-overexpressing strain in the presence and absence of hydrogen peroxide revealed a potential activation mechanism that could be performed by FurC  [hetR, the master regulator of heterocyst development  as a master regulator in Anabaena sp. PCC 7120.Therefore, this work is another piece of evidence that FurC (PerR) is participating in the regulation of the global metabolism of S1 Figp-values indicating the degree of similarity with FurC consensus sequence are shown. The logo of the FurC-matrix built by MEME software is included.The genes holding these sequences as well as the (TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Tablea Previously described FurC-DNA binding sites in Sarasa-Buisan et al., 2022 are shown in blue. b Motif cooccurrences found downstream coding regions are indicated with (-).CoDing Sequence (CDS) annotation according to GenBank assembly . Rows with predicted FurC boxes within promoter region defined as -1000 bp upstream (intergenic regions) and +50 bp downstream with respect to the start codon are highlighted in green and the putatively regulated gene is depicted. In case when the FurC box was predicted in the promoter region of two divergently transcribed genes, the two genes are shown. Rows with predicted FurC boxes outside promoter regions are colored in grey and location is indicated. Distant to ATG is defined as number of nucleotides from the translational start site to the closest end position of the predicted FurC box.(XLSX)Click here for additional data file.S1 Raw images(PDF)Click here for additional data file.


The packaging of the genetic material into chromatin imposes the remodeling of this barrier to allow efficient transcription. RNA polymerase II activity is coupled with several histone modification complexes that enforce remodeling. How RNA polymerase III (Pol III) counteracts the inhibitory effect of chromatin is unknown. We report here a mechanism where RNA Polymerase II (Pol II) transcription is required to prime and maintain nucleosome depletion at Pol III loci and contributes to efficient Pol III recruitment upon re-initiation of growth from stationary phase in Fission yeast. The Pcr1 transcription factor participates in the recruitment of Pol II, which affects local histone occupancy through the associated SAGA complex and a Pol II phospho-S2 CTD / Mst2 pathway. These data expand the central role of Pol II in gene expression beyond mRNA synthesis. Transcription of RNA polymerase II is coupled with remodeling of chromatin. This study reports that transcription of RNA polymerase II is also required to prime and maintain nucleosome depletion at RNA polymerase III loci. These “built-in” factors participate in all steps of the transcription cycle and partly explain the lower number of independent actors in the Pol III system. In addition, they also allow efficient recycling of the polymerase at a given locus2. At tRNA genes, Pol III initiates transcription at internal promoters and is recruited by TFIIIB, which itself is recruited by TFIIIC bound to A and B DNA boxes. These two elements overlap with distinctive features of the mature tRNAs. Other Pol III promoters show variations on that theme2. Maf1 was isolated in yeast as a global repressor of the Pol III machinery and is regulated by several signaling pathways, notably during starvation5.RNA polymerase III (Pol III) is the largest of the three usual eukaryotic RNA polymerases and is specialized in the synthesis of abundant and mostly short ncRNAs named class III genes, which includes the entire repertoire of cytosolic tRNAs. The increased size of Pol III results from the fact that it contains stable integral subunits that are homologs of transcription factors in the RNA polymerase II (Pol II) system6, in response to stresses7 and in pathologies8. In fission yeast, the expression level of the tRNA-ome is a key determinant of the activation of the TORC1 pathway and links nutrient availability to growth10.The idea that Pol III is a constitutive polymerase has been challenged by the finding that the relative abundance of tRNA vary across tissues11, which suggests that the remodeling of chromatin may be independent of the high level of Pol III.The high chromatin occupancy of Pol III was proposed to be sufficient to compete out the installation of a nucleosome at the target loci but the still expanding range of exquisite regulations of Pol III turns down this hypothesis and raises the question of how Pol III handles chromatin remodeling, especially upon de novo initiation seen during exit from starvation. In addition, repressing Pol III by nutritional starvation does not result in a local gain of nucleosome14. In addition, Pol III occupancy scales with the levels of nearby Pol II but not with the levels of Pol II transcript12, suggesting a regulatory relationship between both polymerases. This was consistent with a previous observation that Pol II facilitates Pol III transcription at the U6 gene15. More recently, however, another study reported that the presence of Pol II in the close proximity of class III genes is inhibitory through transcriptional interference16, which was found to be essential for Maf1-mediated repression of a majority of tRNA genes during starvation. This repression is however limited to a small number of loci in rich media.About 10 years ago, three independent studies reported the presence of several typical Pol II-associated histone marks near human Pol III-transcribed genes, and Pol II was found to be enriched at class III loci17, which was correlated with high RSC (Remodels Structure of Chromatin) occupancy and a gain of nucleosome density in the absence of RSC18. These data support that RSC is required to maintain class III genes in a low nucleosome density favorable to Pol III transcription. How RSC is targeted to these loci remains generally unclear although a physical interaction between Rsc4 C-terminus and Rpb5, a shared subunit of the three polymerases, was reported19. Apart from RSC, the ISW complexes were also implicated in the establishment of a NDR (nucleosome-depleted region) at tRNAs genes20. In addition, the acetylation of histone H3, typically found at class II genes, was shown to expand to tRNA genes during exponential growth21 and two histone deacetylases, Hda1 and Hos2, are found at these loci22, challenging the idea that tRNA genes are refractory to chromatin-based regulations. Besides the case of c-Myc recruiting TRRAP and the histone acetyl transferase GCN5 to activate Pol III in human cells23, very little is known about how chromatin modifications and consequent remodeling occurs at class III genes.Early genome-wide studies indicated that tRNA genes are largely devoid of nucleosomesWe report here that Pol II transcription, mostly antisense, is critical to recruit the associated Gcn5 and Mst2 histone acetyltransferases to tRNAs genes respectively though SAGA and the Pol II phospho-S2 CTD. This mechanism is especially important to initiate growth from the stationary phase.rpb1 CTD S2A mutant25, which revealed that the nucleosome-depleted region (NDR) found at the 171 tDNAs loci in wild-type was replaced by a distinctive peak of MNase resistance when CTD S2 phosphorylation was abolished  allele25 that allows the fast depletion of CTD S2 phosphorylation. Within 30 min of inhibition, the histone H3 ChIP signal increased at most Pol III target loci tested without affecting the class II act1 locus  ChIP-seq revealed that the level of Pol III associated with chromatin was strongly reduced in the ain Fig.  for 117 ain Fig. . The fasain Fig. . A hypot26. Strikingly, we found that the CTD-phosphorylated Pol II associates with virtually all tDNA loci and the Pol II peak is generally centered on the tRNA TSS , yet significant correlation between the level of S2P and the level of antisense transcription detected by NET-Seq  steady-state despite the fact that exponential growth is not affected in the rpb1 CTD S2A mutant32. RNA-seq revealed however that the level of most of the 171 mature tRNAs is not decreased in the rpb1 CTD S2A mutant while their precursors are slightly increased  is an evolutionarily conserved general transcriptional coactivator of Pol II notably containing a HAT (Histone acetylation) module harboring the Gcn5 acetylase39. ChIP experiments revealed that Gcn5 is enriched at class III genes and that its deletion locally affects histone H3 acetylation  and a CTD S2P-Set2 and a CTrpb1 CTD S2A mutant has a “slow start” phenotype upon germination of spores from an heterozygous diploid but then reached a midlogarithmic phase doubling time similar to that of wild-type32. These data suggested that the mutant has difficulties to re-establish growth upon exit from the stationary phase32. Exit from stationary phase correlates with a marked recruitment of Pol III at class III loci, which was reduced when Rpb1 CTD S2 cannot be phosphorylated  of a Pol II transcribed gene and are decorated by most of the active chromatin marks classically associated with Pol II transcription. Intriguingly, the class III genes that are not in the proximity of Pol II TSS also have histone modifications found at Pol II transcribed loci and are bound by Pol II, suggesting that Pol II transcription, sometimes referred to as “pervasive” occurs at these loci independently of a neighbor class II gene14. These data raised hypotheses about the putative regulatory role of Pol II transcription at class III loci.Contrary to Pol II, the Pol III system has no known gene-specific regulators, yet the relative abundance of individual tRNAs varies extensively across cell lines and conditions16.A recent study established that Pol II is a direct regulator of tRNA transcription by robustly interfering with Pol III function. The effect, which is limited to a small number of loci in rich media conditions becomes essential for MAF1-repression upon serum starvationWe report here that Pol II, clearly including tDNA antisense transcription, is required for chromatin remodeling at class III genes. We propose that Pol II transcription directly alters the chromatin template through at least two of its histone acetylation-associated activities, namely the Gcn5-containing SAGA complex and Mst2. We show that these two HATs synergize to maintain high acetylation and low histone occupancy at class III genes, therefore maintaining high level of chromatin-bound Pol III Fig. .Fig. 7A 38 by gene-specific transcription factors including Pcr1 in fission yeast37. The Mst2 HAT was shown to be sequestered at transcriptionally active genes by the H3K36me3 mark41. This mark is generated by the Set2 enzyme, which is itself recruited by the phospho-S2 CTD as a consequence of Pol II transcriptional activity45. Therefore, Mst2 is directly dependent upon the phosphorylated Pol II.SAGA is a conserved multi-subunit coactivator recruited at promotersThe requirement of Pol II for efficient Pol III transcription may be especially important upon exit from the stationary phase when cellular growth must be quickly reactivated.46. The experiments presented here brings a mechanistic framework for these early observations.We do not consider the above model and the one proposed by Gerber et al. contradictory or mutually exclusive because the latter is specifically relevant in starvation. Therefore, a possibility is that upon starvation, Pol II transcription is increased at class III loci and interferes with sense Pol III, which facilitates Maf1-dependent inhibition. Moreover, our data are in agreement of previous data reporting the close association of RNA polymerase II and several transcription factors with class III loci and their requirement for efficient expression of Pol III genes36. Other transcription factors, including Gaf1 that often occupy these regions, may participate in the recruitment of Pol II47. While a clear CRE binding motif is detected is detected within 1 kb of 44 tRNA genes, Pol II transcription may also originate from neighbor class II genes, which may explain the more disperse Pol II ChIP and NET-seq signals seen at some tDNA loci  or EMM (MP 4110-012) at 32 °C to OD595nm 0.5–0.8. For spot assays, strains were cultured in liquid YES media at 32 °C and harvested at exponential phase, spotted (tenfold dilutions) on YES agar plates, and incubated up to 3 days at 32 °C49.S. pombe, Expand High Fidelity-generated PCR products (Roche 19012322) were generated by amplification of a nucleotide sequence (consisting of a resistance cassette against an antibiotic or a tag sequence cloned in a pFA6A vector) with primers designed by the Pombe PCR Primer Program . Purified PCR products (Qiagen 28106) were transformed by following the lithium acetate procedure50. Gene deletions resulted in ATG-STOP replacement and gene tagging resulted in a C-terminal tagging by removal of the endogenous STOP codon and insertion of the tag sequence.For transgenesis in For the experiment of Fig. PRO.08 ura4T strain was constructed by integrating the strong ura4 terminator (defined in ref. 43) downstream of the SPBTRNAPRO.08 loci. The integration removes 452 bp next to the poly-T Pol III termination signal and deletes the TGACGTC CRE motif. Growth was determined based on optical densities measured at 595 nm on a BIOTEK Absorbance microplate reader Epoch2NS according to the instructions of the manufacturer. The yeast strains and primers for qPCR and ChIP described in this study are listed in Supplementary Data The 49. Briefly, cells were grown in YES medium at 32 °C until late/mid-exponential phase (OD600 ~0.8). Then 80 mL of cultures were incubated for 10 min at room temperature with 1% formaldehyde. After quenching the reaction with glycine, cells were washed in cold Tris-buffered saline  and snap-frozen. The pellet was thawed on ice and washed with FA/SDS/PI , resuspended in 1.6 ml of FA/SDS/PI and incubated 15 min on ice. The sample was sonicated with a BioRuptor (Diagenode) . After transfer to 1.5 ml microcentrifuge tube and centrifugation for 30 min, 14,000 × g, 4 °C, the supernatant was transferred to a new tube. Per IP, 50 μl of appropriate magnetic beads were washed four times with PBS BSA (1 mg/ml) and resuspended in PBS BSA (10 mg/ml) and then added to each 500 μL chromatin extract IP and incubated 2 h at 21 °C. The beads were washed three times with 1 ml of FA/SDS+NaCl 500 mM, one time with 500 μl of IP Buffer and one time with 500 μl of TE and resuspended in 125 μl of Pronase Buffer 1× and incubated 20 min at 65 °C. RNAse A was added 1 h at 37 °C and the DNA sample were purified on Rapace columns (Qiagen).Chromatin Immunoprecipitations were performed using a Bioruptor (Diagenode) and Dynabeads (Invitrogen)n). Primers are listed in Supplementary Data Antibodies used in ChIP were anti-Pol II (Covance #MMS-126R), anti-H3 (Abcam #1791), anti-H3 K14-ac (Millipore #07-353), anti-HA (Sigma #H6908), PAP (Sigma #P1291), anti-CTD S2P (Millipore #04-1571), anti-CTD S5P (Abcam ab5408), anti-flag (Sigma #F3165) and anti-Myc (Covance #MMS-150P). For all ChIP experiments, each column represents the mean percentage immunoprecipitation value ± standard deviation. The number of biological replicates is indicated in the legend  corresponding to the boundaries of each nucleosome. We used the smoothed signal generated by using the multilevel 1-D biorthogonal wavelet decomposition/reconstruction tool implemented in the Matlab “Wavelet Toolbox” to calculate the average spacing between boundary peaks for individual nucleosomes.The MNase-seq datasets and MNase-ChIP protocol were reported in refs. This parameter (which was estimated for every independent experiment) defined the distance that the individual profiles from each DNA strand had to be shifted to converge and define the midpoint position of each nucleosome. The resulting combined profile was wavelet-smoothed to generate the final nucleosome positioning profile. The sequencing coverage for every nucleotide was divided by the average genomic coverage to normalize the different experiments. We defined nucleosome-depleted regions (NDRs) as regions spanning at least 150 nucleotides (corresponding to the eviction of at least one nucleosome) with a normalized sequence coverage lower than 0.4.52. ChIP was performed as for the ChIP-qPCR experiments, with the exception that for the Rpc1-TAP ChIP-seq assays, an equal amount (10%) of S. cerevisiae Rpb3-TAP strain were mixed into the wild-type and mutant strains before the crosslink for spiked-in normalization. Similarly, for the Rpb3-HA ChIP-seq assays, an equal amount (10%) of S. cerevisiae Rpb3-HA strain were mixed in the S. pombe samples before the crosslink. High-throughput sequencing libraries were generated from 10 ng of the ChIP DNA using the Illumina TruSeq ChIP-seq library preparation protocol according to the manufacturer’s instructions. The libraries were sequenced on an Illumina HiSeq 2500 apparatus.ChIP-Seq was performed as described in our previous workS. pombe genome (version ASM294v2.26) with the S. cerevisaie reference genome using HISAT2 with option–no-splice-alignment. Normalization factors were computed based on the number of spike-in reads mapped to the S. cerevisiae genome. Based on these normalization factors, we used deepTools to normalized coverage files (.bigwig) with options bamCoverage --samFlagExclude 256 --maxFragmentLength --scaleFactor $size_factor -bs 1 -of bigwig. Raw reads and processed genome coverage files in bigWig format are provided and available on GEO.For the analysis, raw reads were trimmed using trimmomatic against the appropriate adapter sequences with options SE ILLUMINACLIP:$adapters:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36. Trimmed reads were then mapped on the concatenation of the rpb3-flag cells and sequenced as described in our previous work27. Shortly, Libraries were constructed starting from 1 L of exponentially growing cells. RNAPII was immunoprecipitated using anti-FLAG M2 affinity gel, then recovered upon two successive elution steps using FLAG peptide. Ligation of DNA 3′-linker was performed from 2–3 μg of purified nascent RNA  and total RNA (input samples). Ligated RNAs were then submitted to alkaline fragmentation for 20 min at 95 °C. Single-end sequencing (50 nt) of the libraries was performed on a HiSeq 2500 sequencer, giving between 20 and 50 million reads. After trimming of the 5′-adapter, reads were uniquely mapped to the reference genome (ASM294v2.30) with a tolerance of two mismatches, giving 7.1–9.8 million uniquely mapped reads.NET-Seq libraries were constructed from biological duplicates of Data were normalized on the total number of uniquely mapped reads, for each sample. As a reference for the absence of transcription, we used a set of 50 protein-coding genes, showing the lowest nascent transcription signals (IP samples) and low total RNA levels (input samples). These genes were selected after filtering out the genes for which the signal was equal or close to zero as no (or very few) reads could be uniquely mapped, due to the high content of repetitive sequences. This was manually checked using the NET-seq signals (IP and input) and also the ChIP-seq signals (IP) for histone H3.53. Briefly, 50 mL of S. pombe (OD595nm ~0.5) were harvested by centrifugation and washed in DEPC water. The cell pellets were resuspended in 750 μL of TES buffer  and the RNA was isolated by hot phenol extraction; equal volume of phenol:chloroform 5:1 was added (Sigma P1944), heated and shaken at 65 °C for 60 min, the upper phase was collected after centrifugation, mixed with an equal volume of phenol:chloroform:IAA 125:24:1 (Sigma 77619); the upper phase was then collected after centrifugation, mixed with an equal volume of chloroform:IAA 24:1 (Sigma 25666); the upper phase was collected again and the RNA was alcohol-precipitated with 2.5 volumes of 100% ethanol and 0.1 volume of 3 M sodium acetate pH 5.2 for minimum 30 min at −80 °C or overnight at −20 °C. After centrifugation, the pellet was washed with 70% ethanol, air-dried and resuspended in DEPC (Sigma D5758) water or pure water (Sigma 900682).RNA was extracted as previously reportedIn all, 0.5 μg of RNeasy-purified total RNA Qiagen 74104) was retro-transcribed with the High-Capacity cDNA Reverse Transcription Kit (Thermo 4368813) by following the manufacturer’s instructions. The real-time PCR amplification was performed with SYBR Green Supermix (Bio-Rad 172-5124) in a Bio-Rad CFX96TM Real-Time machine. The PCR program was 3 min at 95 °C and 40 cycles of (15 s at 95 °C and 30 s at 60 °C). Relative RNA quantification relied on the ∆∆CT method. Primer sequences can be found in Supplementary Data 04 was re54 from 10 mL of yeasts cultured in YES at 32 °C. Cells were pelleted, washed in water and disrupted with 0.3 M hydroxide sodium for 10 min at RT. The lysate was then centrifuged and the supernatant was discarded. The pellet was resuspended in 70 μL of alkaline extraction buffer  and boiled for 5 min at 95 °C. Overall, 10 μL of the samples were loaded on a 4–15% Mini-PROTEAN TGX Precast Protein Gel (Bio-Rad 456-1083), transferred on a nitrocellulose membrane (Bio-Rad 1704158) and blocked for 60 min at RT or overnight at 4 °C in 50:50 1× PBS:Odyssey Blocking Buffer PBS (Westburg LI 927-40100). The membrane was incubated with the primary antibody for 60 min at RT or overnight at 4 °C with Odyssey Buffer containing 0.05% Tween20 (Bio-Rad 161-0781) and a 1:500–1000 dilution of anti-α-tubulin (Sigma T5168) or anti-Histone H3 (Abcam ab1791) primary antibodies. After three washes in PBS-T, the membrane was incubated with a 1:10,000 dilution of anti-mouse (Westburg LI 925-32210) or anti-rabbit (Westburg LI 925-32211) secondary antibodies for 60 min at RT in Odyssey Buffer containing 0.05% Tween20. After three washes in PBS-T and three washes in PBS, the membrane was dried for 60 min at 37 °C and visualized on a LiCOR scanner on channel 800. The quantification was performed with ImageJ55.Proteins were extracted as previously reportedIn total, 1 μg of total RNA was ribodepleted as described in the Rho-seq section and analyzed by microchip electrophoresis as described above. Overall, 125 ng of ribodepleted samples were prepared for strand-specific NGS with the TruSeq Stranded Total RNA Sample Preparation Protocol (Illumina). The library was sequenced on Illumina HiSeq 2500 . Reads were mapped on the genome using TopHat2. The quantification was made with featureCounts function on R and the differential expression analysis was performed with DESeq2. The genes following these criteria were considered as differentially expressed; false discovery rate <10% and the absolute value of the fold change >1.5.t test, the obtained P value is indicated in the Source data file and represented in the figure as: *P < 0.05, **P < 0.01, ***P < 0.001; ns not significant. When normalized data are shown (For CTD S2P and H3K14ac level), the independent data and error bars are provided in the Source data file and the normalized data is shown in the figures.No statistical method was used to predetermine sample size. No data were excluded from the analyses. The experiments were not randomized. The Investigators were not blinded to allocation during experiments and outcome assessment. For all experiments with statistical analyses, the averaged value from three biological replicates is shown and error bars are the standard deviation. Upon paired Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Apoptosis is a vital cellular process that is critical for the maintenance of homeostasis in health and disease. The derailment of apoptotic mechanisms has severe consequences such as abnormal development, cancer, and neurodegenerative diseases. Thus, there exist complex regulatory mechanisms in eukaryotes to preserve the balance between cell growth and cell death. Initially, protein-coding genes were prioritized in the search for such regulatory macromolecules involved in the regulation of apoptosis. However, recent genome annotations and transcriptomics studies have uncovered a plethora of regulatory noncoding RNAs that have the ability to modulate not only apoptosis but also many other biochemical processes in eukaryotes. In this review article, we will cover a brief summary of apoptosis and detection methods followed by an extensive discussion on microRNAs, circular RNAs, and long noncoding RNAs in apoptosis. Historically, it was assumed by scientists that cell death is a natural consequence of life without any genetic basis. However, the accumulating evidence clearly indicates that cell death can be intervened both pharmacologically and genetically, paving the way for its use in health and disease . The NomThe first example of programmed cell death (PCD) was reported in 1965 in a study involving the development of muscle subsegments . The terIn this review, we will succinctly describe major apoptotic pathways followed by the coverage of three major types of noncoding RNAs (ncRNAs) that modulate apoptosis, namely microRNAs (miRNAs), circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs).Apoptosis is a type of programmed cell death performed by activation of a family of cysteine proteases known as caspases. Apoptosis takes place in an ordered chain reaction triggered by various intra- or extracellular stimuli such as ligation of cell surface receptors, treatment with cytotoxic drugs or irradiation . In respAs being committed in a fashion of a cascade of events, apoptosis proceeds through the phases of initiation, intracellular response, cell fragmentation, and phagocytosis . Based oA specific interaction between a ligand and transmembrane death receptors, such as tumour necrosis factor receptor 1 (TNFR1) and Fas receptor (FasR), which are members of the tumor necrosis factor (TNF) receptor gene superfamily, initiates apoptosis through the extrinsic signalling pathway. The ligand-receptor interaction activates the sequential events of recruitment of cytosolic adaptor proteins harboring death domains, death domain association with procaspase-8, formation of death-inducing signal complex (DISC) and activation of procaspase-8 to initiator caspase-8. Subsequently, executioner caspases  are activated to complete the process .The intrinsic pathway is initiated through stress stimuli such as direct DNA damage, hypoxia, and survival factor deprivation, and proceeds with the loss of mitochondrial membrane potential, resulting in an alteration in the permeability of mitochondria. Cytochrome c is then released from the intermembrane space into the cytosol and interacts with proapoptotic cytosolic factor Apaf-1 to form the apoptosome, which activates caspase-9 and -3, consecutively . SynchroThe perforin/granzyme pathway, which is specialized for infected cells, is executed by cytotoxic T-lymphocytes and natural killer cells . Immune Apoptotic features can be distinguished via various methods based on cell morphology, DNA structure, biochemical and electrochemical properties of apoptotic cells either real-time or at an end point . Recent Morphological features of apoptosis can be monitored by electron microscopy, either by scanning (SEM) or transmission electron microscopy (TEM). SEM provides topographic data depicting cell surface alterations by using a focused beam of high energy electrons . NonhazaAs one of the hallmarks of apoptosis, DNA fragmentation serves as a feasible tool for detection. DNA fragments (approximately 200 bp) generated by endonuclease cleavage during apoptosis can be visualized by agarose gel electrophoresis . This meEnd-labeling the resulting DNA fragments has led to the development of other derivations such as In Situ End Labeling (ISEL) and Terminal dUTP Nick End-Labeling (TUNEL). Both methods incorporate the labeled nucleotides at the site of DNA strand break either by DNA polymerase I in ISEL or terminal deoxynucleotidyl transferase in TUNEL assay. Digitoxigenin-tagged or biotinylated nucleotides used in ISEL as well as dUTP biotin nick end labeling in TUNEL can be monitored by fluorescent microscopy and flow cytometry following hybridization with appropriate probes . The difThe rate of apoptosis can be detected by monitoring the absorption and emission of light by the sample. This approach allows the use of different platforms ranging from microscopes and spectrophotometers, with or without fluorescent dyes, to flow cytometers based on laser excitation. DNA-fragmentation-based methods, ISEL and TUNEL, can be also categorized in this section due to the use of fluorescent-tagged nucleotides. Comet assay is another method for apoptosis detection, which is based on the analysis of DNA strand breaks . This asBeing one of the early indicators of apoptosis, phosphatidylserine exposure serves as another useful tool to detect apoptosis. Alterations in the mitochondrial membrane potential followed by the cytochrome c release into the cytosol are also considered an indication of early apoptosis . JC-1, rIn addition to fluorescence detection, light microscopy can also be exploited to distinguish apoptotic cells via a histochemical staining procedure. Hematoxylin and eosin as well as Giemsa stainings are employed to define the morphological hallmarks of apoptosis such as dense purple chromatin and darker cytoplasm containing round bodies because of DNA fragmentation .The protein components of apoptotic cascades, activated through extrinsic or intrinsic pathways, can be biochemically monitored by western blotting, flow cytometry or immunocytochemistry based on the availability of unlabeled or fluorochrome-labeled antibodies. Some of the common members of the protein network that are targeted for analysis include caspases, Bcl-2 and p53 proteins as the main regulators, cytochrome c as an indicator of the mitochondrial pathway and the truncated form of bid, t-bid, as the hallmark of the crosstalk between the intrinsic and extrinsic pathways . As thesHistorically, it was believed that the genetic information stored in the genome is first transcribed into messenger ribonucleic acids (mRNAs) followed by translation into proteins. This concept was embraced for a long time as proteins were considered as the structural and functional macromolecules in most, if not all, biochemical cellular processes. In fact, H19, the first functional regulatory ncRNA, was originally classified as a mRNA, which was later shown to not code for a protein . AlthougXist transcript was initially classified as a mRNA due to the presence of a 298-amino acid ORF . Then, reverse transcription is performed to convert the template RNA into a more stable complementary DNA (cDNA) while labeling each sample with one of the two distinct fluorescent markers, for instance, Cy3 and Cy5. If the amount of RNA sample is scarce to obtain enough signal, the cDNA may be amplified, prior to fluorescent labeling, to increase the template input. The dual-fluorescent-labeled cDNA pools are then mixed and loaded into a microarray chip, which harbours thousands of probes complementary to the genes of interest. A few methods have been developed to improve the efficiency of labeling as this step appears to be highly critical. Labeling involves the use of fluorescent or biotin-labeled nucleotides that are incorporated into cDNA or cRNA during synthesis. Finally, washing, fixing, and scanning of the hybridized arrays are performed to acquire the data .Although the protocols are highly optimized for the analysis of mRNAs, there are additional optimization steps that need to be considered while using microarray chips for the analysis of ncRNAs. For example, microarray-based detection of miRNAs has challenges in labeling probes and hybridization due to the shorter length and lower abundance of miRNAs. Firstly, Locked Nucleic Acid-modified (LNA) capture probes may be used to eliminate acquisition problems of TM-normalised probe sets . FurtherMicroarray-based profiling of lncRNAs and circRNAs resemble that of mRNAs. However, RNA isolation of high integrity from the control and test samples should be wellplanned. Regarding lncRNAs, rRNAs should be eliminated as a priori step to enrich the lncRNAs. Then, each sample should be amplified and transcribed into cRNAs without any 3′-bias utilizing a random priming method . The samOver the past decade, Next-Generation Sequencing (NGS)-based transcriptome analyses have dominated the field to search for novel noncoding transcripts that might be the long-sought answer to the existence of a big chunk of a genome without any protein-coding capacity. To this extent, NGS is a widely used, indispensable and versatile method to detect and quantify ncRNAs . In addiRNA sequencing (RNA-seq) begins with the preparation of an RNA sample of high integrity followed by rRNA depletion or poly(A)-plus transcript selection, cDNA synthesis, and library preparation . The seqTotal RNA isolation followed by size-fractionation is the preferable method for miRNA enrichment prior to the library construction . Reversede novo assembly is more suitable while working with novel organisms, whereas the mapping assembly approach is preferable in the presence of a reference genome  tail . IrrespeP-labeled probes  by RNA polymerase II . The firng event . The resng event . Dicer ing event . The polng event . The strng event . The resng event . The celng event .The noncanonical miRNA biogenesis pathway involves production of pri-miRNAs that do not go through Drosha- or Dicer-mediated cleavage. Perhaps the best-known example of such miRNAs are mirtrons, those that are generated from debranched introns that enter the biogenesis process as pre-miRNAs . A subsehttp://mcg.ustc.edu.cn/bsc/isomir/) that houses annotated isomiRs  on the other parts of target RNAs such as 5′-UTR, coding region or promoter regions . Target Drosophila embryos, some of which switch to non-polysomal fractions upon the maternal-to-zygotic transition  and AGO2 independently associate with mRNAs that possess AU-rich elements (AREs) in their 3′-UTRs and activate translation upon serum starvation . A similIt is important to note that miRNAs as micromanagers of post-transcriptional regulation are subject to intense genetic and epigenetic regulation as well. We refer the readers to other reviews on this topic due to space limitation . AdditioDrosophila 18 years ago  tail nor a 5′-cap . circRNAThe 2010s witnessed the discovery of several circRNAs in parallel to the development of high-throughput RNA sequencing methods and appropriate bioinformatics pipelines. In 2012, Salzman and his team provided convincing evidence that circRNAs are abundant RNA isoforms in human cells . Subsequcis- and trans-acting elements facilitate these sterically unfavorable reactions and regulate the competition between the back-splicing and the canonical splicing  tails, circRNAs should be degraded by an endoribonucleolytic attack owing to their ring structure . circRNADespite the concerns over the functionality of circRNAs, increasing evidence suggests that circRNAs modulate gene expression in a cell-specific manner . The bioNumerous studies report that circRNAs may sequester miRNAs by acting as competing endogenous RNAs or miRNA sponges . ConsideRBPs interact with and modulate the fate of RNAs by forming ribonucleoprotein complexes. Similar to sequestration of miRNAs, circRNAs may act as protein scaffolds, decoys, sponges, and recruiters. In recent years, a plenty of circRNAs have been shown to interact with proteins through specific binding sites. Apparently, the circRNA:RBP interactions are dictated by the primary sequence information and the unique tertiary structure of circRNAs . The cirIt is unquestionably vital to understand how circRNAs regulate apoptosis. Therefore, recent efforts have been geared towards the discovery and functional characterization of circRNAs that are involved in apoptosis and associated diseases such as cancer, neurodegenerative diseases, and cardiovascular diseases . One of There are 22 publicly available and comprehensive circRNA databases that are maintained up-to-date . Three olncRNAs are a class of ncRNAs longer than 300 nucleotides in length and lack the ability to encode a protein . SimilarH19   . Furtherct (HGP) .Earlier studies have questioned the functionality of lncRNAs, arguing that lncRNAs could be transcriptional noise . HoweverEven though the global features of lncRNAs and mRNAs suggest they have similar biochemical properties in common, lncRNAs contain fewer and longer exons than mRNAs. Additionally, they tend to localize primarily in the nucleus and show lower expression patterns . Recent In contrast to the lincRNAs targeted by nuclear surveillance process, chromatin-tethered lncRNAs may comprise a specifically high number of U1 small nuclear RNA binding sites . U1 smallncRNAs are found dispersed through nucleus, nucleolus, cytoplasm, and mitochondria. The enrichment of lncRNAs at specific cellular compartments may determine their mode of action. RNA-seq analysis of various human tissues showed the enrichment of lncRNAs in the nucleus, specifically associated with chromatin in several cell lines . SubsequlncRNAs can be classified based on their functions as molecular signals, decoys, guides, and scaffolds . lncRNAsCertain lncRNAs act as decoys by directly binding the transcriptional regulators and impairing their functions or hindering the binding of transcriptional factors to the genomic DNA  Figure . For exaGenome structure and organization is achieved by an intricate folding of the genomic DNA mediated by numerous DNA:protein interactions. As a third mechanism, lncRNAs can act as guiding molecules to recruit chromatin modifiers, ribonucleoprotein complexes and transcription factors to the target sites to modulate chromatin dynamics and gene expression  Figure . lncRNA Xist promotes the recruitment of components of PRC2 and induces heterochromatin formation by H3K27me3 deposition, lncPRESS1 interacts with SIRT6, a histone deacetyltransferase, and inhibits SIRT6 function, thereby causing activation of transcription at pluripotency gene promoters  is a lncRNA upregulated in bladder cancer cells. Studies showed that binding of Ets-2, a transcription factor that binds to the UCA1 promoter, modulates its transcription . Ets-2 tRegulation of the extrinsic apoptotic pathway can be mediated directly or indirectly by lncRNAs . For exalncRNAs may target tumour suppressor genes such as p53 and PTEN to control apoptosis . For exaAdvances in transcriptome-wide studies have led to the establishment of lncRNA databases to maintain the resulting massive data . The mosApoptosis is a complex cellular mechanism that plays a critical role in the maintenance of organismal homeostasis throughout development. Undoubtedly, apoptosis is regulated by epigenetic, transcriptional and post-transcriptional gene regulatory mechanisms mediated by protein coding genes. The accumulating evidence demonstrates that these regulatory proteins are regulated by a diverse biotype of ncRNAs, ranging from miRNAs to lncRNAs and circRNAs. It is important to underline the existence of other types of ncRNAs, such as piRNAs or tRNA-derived fragments (tRF) that are known to be involved in apoptotic processes . More ex


However, direct evidence for Eα physically mediating the interaction of Vα and Jα genes is still lacking. In this study, we utilized the 3C-HTGTS assay, a chromatin interaction technique based on 3C, to analyze the higher order chromatin structure of the Tcra locus. Our analysis revealed the presence of sufficient information in the 3C-HTGTS data to detect multiway contacts. Three-way contact analysis of the Tcra locus demonstrated the co-occurrence of the proximal Jα genes, Vα genes and Eα in CD4+CD8+ double-positive thymocytes. Notably, the INT2–TEAp loop emerged as a prominent structure likely to be responsible for bringing the proximal Jα genes and the Vα genes into proximity. Moreover, the enhancer Eα utilizes this loop to establish physical proximity with the proximal Vα gene region. This study provides insights into the higher order chromatin structure of the Tcra locus, shedding light on the spatial organization of chromatin and its impact on V(D)J recombination.The generation of highly diverse antigen receptors in T and B lymphocytes relies on V(D)J recombination. The enhancer E  Usuallys (TCRs) . Recentlangement ,10,12. TTcra) is a crucial event during T-cell development in the thymus , located between the V and DJδ segments, act as insulators. These insulators can reduce the usage of the proximal Trdv2-2 gene, thereby indirectly affecting Tcra rearrangement   , and seviversity .α, located downstream of the Tcra–Tcrd locus, plays a crucial role in regulating Tcra rearrangement by activating the upstream promoter TEAp of the Jα gene array and establishing a recombination center in CD4+CD8+ double-positive (DP) thymocytes  and high-throughput genome-wide translocation sequencing (HTGTS) . This meRag1−/− mice were kindly provided by Professor Wei Yang from the Department of Pathology, Southern Medical University, Guangzhou, China. EACBE−/− mice were generated from strain C57BL/6 by Beijing Vitalstar Biotechnology  at 3 weeks of age, and thymi were harvested and ground in MACS buffer 10 days after injection. Thymocytes were filtered through a 40 μm nylon mesh and then pelleted.To isolate DP thymocytes from 3C-HTGTS libraries were prepared with DP thymocytes ,20. In bhttp://hgdownload.cse.ucsc.edu/goldenPath/mm10/bigZips/chromFa.tar.gz); we extracted concordantly exact alignments using SAMtools (v1.9) (cis) normalization method and visualized them on the IGV genome browser. Differential pairwise interactions were identified by the R package R.4Cker  with the function nearBaitAnalysis called to define domains of interaction with the bait and DESeq2   . Trimmeds (v1.9) . Self-lis (v1.9) . The sig < 0.05) ,27. FinaPaired-end reads were obtained through quality filtering and adapter trimming using fastp (v0.20.0). The second restriction enzyme cut in 4C reads was removed. The first MboI fragment after the bait sequence was extracted and mapped to the enzyme-digested mm10 reference genome by Bowtie2  in the form of single-end reads, and we extracted concordantly exact alignments using SAMtools (v1.9). We filtered self-ligation reads and off-target reads. For visualization, we converted the final bam files into bedGraph files using Bedtools (v2.29.2). Read numbers were counted and normalized by the CPM normalization method, and then files were visualized on the IGV genome browser. The analysis of the correlation for experimental repetition used the R package corrplot (v.0.92).P < 0.001) . Trimmed reads were extracted from the file after quality control with Cutadapt (v1.18). Paired-end reads containing a nested primer or adapter primer were merged at restriction enzyme cut sites into single reads with Pear (v0.9.6), then fragments with multiple MboI-cut sites were split and each fragment was aligned to the enzyme-digested mm10 reference genome by Bowtie2 . We extracted concordantly exact alignments using SAMtools (v1.9). We converted the final bam files into bed files using Bedtools (v2.29.2). Self-ligation and off-targeted fragments were filtered. Subsequently, we put all fragments retrieved from the same read according to the unique ID of each read on one line, then removed the continuous fragments. To create contact matrices, we extracted the first two digested fragments after the bait fragment, or a variety of combinations of three fragments were obtained by arranging all fragments from the same read. Raw contact matrices were generated at 3, 5 and 10 kb resolutions. For correction of raw contact matrices, these interaction counts were normalized for a total of 1 000 000 interactions at the same resolutions. Similar to a Hi-C matrix, coverage was represented in a two-dimensional matrix where each point represented the number of interactions found between two bins meaning a specific resolution. Visualization of three-way contact matrices was done with the R package GENOVA (v1.0.0) then differential analysis and visualization of local interactions from three-way interactions were obtained using the Bioconductor package DESeq2  . Loops sFirst, adapter sequences were trimmed with fastp (v0.20.0). We retained reads that were separated by MboI-cut sites. In other words, only fragments with two or more MboI sites were considered for analysis of multiway interactions. MboI-cut fragments after the bait sequence were split and individually aligned to the enzyme-digested mm10 reference genome by Bowtie2 . We extracted alignments using SAMtools (v1.9). The final bam files were converted into bed files using Bedtools (v2.29.2). We filtered the self-ligation and off-target fragments after mapping. Subsequently, we put all fragments retrieved from the same read on one line, then removed continuous fragments. To create contact matrices, we extracted the first two fragments after the bait or a variety of combinations of three fragments were obtained by arranging fragments from the same read. Raw contact matrices were generated at 3, 5 and 10 kb resolutions. For raw contact matrices correction, these interaction counts were normalized for a total of 1 000 000 interactions at the same resolutions. Like a Hi-C matrix, coverage was represented in a two-dimensional matrix where each point represented the number of interactions found between two bins meaning a specific resolution. A heatmap of three-way contact matrices was produced with the R package GENOVA (v1.0.0), and the distributions for the frequencies of unique reads containing the pairwise and multiway chromatin interactions were counted after aligning and filtering, and they were visualized with the Bioconductor package ggplot2 (v3.3.6).et al. .Tcra–Tcrd locus in DP thymocytes, we performed a 3C-HTGTS assay using CD3-induced DP thymocytes of Rag1−/− mice, with the baits of Eα, the TEA promoter (TEAp), INT2 and a CBE upstream of the proximal Vα gene Trav17 (Trav17–CBE2). The 3C-HTGTS assay generated higher resolution interaction profiles compared with the 4C data from the same baits , as well as substantial interactions with INTs and several CBEs in the proximal V region   . A recenangement . The reaTcra–Tcrd locus in DP cells, we analyzed three-way contacts from the baits of Eα, TEAp, INT2 and Trav17–CBE2. The 3C-HTGTS data obtained from these four baits contained enough multiway contacts for higher order chromatin structure analysis . The. TheTcrae Figure . This res Figure . Eα also7 Figure . The mul7 Figure . CollectTrav17 heatmap is a broad chromatin contact stripe that extends from upstream of Trav17 to Eα  are disfavored  stage  , and there is a strongly disfavored region around Trdd2  Figure . The dis2 Figure . Both IN2 Figure . These rTrdd2 was used as the SOI, it was evident that INT2 had a strong signal and was favored in the bait–SOI contacts   oriented downstream, the same direction of most CBEs in the V region. On the other hand, Trav17–CBE2 is oriented upward, which is unique within the proximal V region. In the TEAp–Trav17 bait–SOI, the SOI contains the Trav17 gene body and CBE1 but not CBE2  Figure . To inveI Figure . HoweverI Figure , which c2 Figure , while tI Figure . A recenI Figure . The co-α and proximal Vα genes, thus impairing Tcra rearrangement J recombination and other genome metabolism processes. Several multiway contact techniques have been developed for investigating higher order chromatin structures  The Vδ–DJδ rearrangement of Tcrd in the DN stage can delete a partial sequence between the V region and the Jα region, including INTs. The deletion may promote the Vα–Jα rearrangement and increase the diversity of Tcra  Onractions . Our stuV region . Here, w Trdv2-2 . While t Jα gene .et al. reported that INT2 restricts the usage of Trdv2-2 in Tcrd rearrangement in DN thymocytes by forming a chromatin loop between INT2 and the CBE in the TEA promoter  it brings the proximal Vα genes closer to the recombination center formed by the proximal Jα genes and Eα; and (ii) the loop restricts the sequences in the loop interacting with sequences outside of the loop, potentially repressing Tcrd rearrangement in DP stages.Chen Tcra–Tcrd locus in DP thymocytes. Our findings provide compelling evidence for the co-occurrence contacts of Eα, the Vα genes and the proximal Jα genes, establishing a paradigm for the study of higher order chromatin structure.Here we developed a pipeline for analyzing multiway contacts in 3C-HTGTS data, which offers a cost-effective and straightforward approach for investigating the higher order chromatin structure of a specific genomic locus. By employing this pipeline, we conducted an analysis of the higher order chromatin conformation in the 3′ portion of the gkad641_Supplemental_FileClick here for additional data file.