Zscan4d, a two-cell specific gene involved in zygote genome activation. Overexpression of Zscan4 in the oocyte partially recapitulates the phenotypes of Hira mutants and Zscan4 knockdown in Cabin1 mutant oocytes partially restored their developmental potential, illustrating that temporal and spatial expression of Zscan4 is fine-tuned at the oocyte-to-embryo transition. Thus, the H3.3 chaperone Hira complex has a maternal effect function in oocyte developmental competence and embryogenesis, through modulating chromatin condensation and transcriptional quiescence.Successful reproduction requires an oocyte competent to sustain early embryo development. By the end of oogenesis, the oocyte has entered a transcriptionally silenced state, the mechanisms and significance of which remain poorly understood. Histone H3.3, a histone H3 variant, has unique cell cycle-independent functions in chromatin structure and gene expression. Here, we have characterised the H3.3 chaperone Hira/Cabin1/Ubn1 complex, showing that loss of function of any of these subunits causes early embryogenesis failure in mouse. Transcriptome and nascent RNA analyses revealed that transcription is aberrantly silenced in mutant oocytes. Histone marks, including H3K4me3 and H3K9me3, are reduced and chromatin accessibility is impaired in Hira/Cabin1 mutants. Misregulated genes in mutant oocytes include  Summary: The H3.3 chaperone Hira complex has a maternal effect function in oocyte developmental competence and embryogenesis by modulating chromatin condensation and transcriptional quiescence. Oocytes are key orchestrators of fertilisation, initiators of zygotic genome activation (ZGA) and pre-implantation development . This poOocytes enter a protracted meiotic arrest in prophase I but, remarkably, retain their competence and genomic integrity for a long time, for years in humans. It would then be logical to hypothesise that replication-independent mechanisms of chromatin regulation may be indispensable to maintaining the quality of oocytes throughout this prolonged meiotic arrest.Histones are the fundamental blocks of chromatin that regulate both chromatin compactness and gene transcriptional processes. In addition to canonical histones, histone variants provide additional layers of regulatory mechanisms in a replication-independent manner. H3.3 is the primary replication-independent histone variant and has been shown to play prominent roles during crucial stages of reproduction, including fertilisation  and earlThe key chaperone molecules required for H3.3 incorporation into chromatin form the Hira complex, which comprises Hira, Ubn1 and Cabin1 subunits . In thisFig. S1A). Conditional knockout mouse lines targeting Hira and Cabin1 were generated by crossing a transgenic Zp3-Cre mouse line  and a conditional allele of Cabin1 to deplete of exon 6 , respectively.To investigate the maternal role of the Hira complex during the oocyte-to-embryo transition , we appluse line  with a cin vitro maturation to the MII stage followed by parthenogenesis and pre-implantation development to the morula-to-blastocyst stage . Oocyte depletion of Ubn1 impaired maturation . Importantly, it also induced a significant decrease in cleavage to two-cell stage  as well as development to morula-to-blastocyst stage  with those injected with Ubn1 morpholino (Ubn1 MO). Microinjected GV oocytes then underwent P=0.02). In order to minimise the effect of variable genetic background, for all subsequent experiments we used littermates from heterozygous mating of ZH and Cabz mice.Both ZH and CabZ mutant mice are infertile, showing the similar phenotype as our previously reported Hira mutants . We havein vitro culture. CabZ KO embryos had significantly reduced ability to form morula-to-blastocyst stage embryos : the majority arrested at the two- to four-cell stages  and mutants (CabZ KO), then monitored their developmental outcomes and compared the rate of development to morula-to-blastocyst stage embryos after l stages C, which l stages . Second,P=5.7E-5; Fig. S1F) and later morula-to-blastocyst stage  embryos.The above genetic manipulations consistently show that loss of any of the components of the Hira complex produces a phenotype of disruption of early embryo development. This conclusion is further supported by the depletion of the target of the chaperone Hira complex: histone H3.3. Using the same approach used for Ubn1 knockdown, we interfered with H3.3 mRNA translation in wild-type GV oocytes. In agreement with the loss-of-function of the H3.3 chaperone Hira complex , H3.3 depletion in oocytes resulted in the developmental arrest of parthenogenetic embryos with a significantly impaired formation of both two-cell stage  in Hira and Cabin1 mutants compared with heterozygotes, respectively (P<1.7E-70) overlap with upregulated genes in ZH mutants , indicating that the overall dysregulation of the genes of ZH and CabZ mutants is not due to a developmental arrest at an immature oocyte stage. In addition, we did not detect a significant change in the NSN/SN ratio in either ZH or CabZ oocytes after DNA dye staining . The morphological score indicated that the transition of NSN to SN in the ZH and CabZ GV oocytes appears to be normal.To address the possibility that the dysregulated genes were inherited from growing oocytes, we compared our datasets with a dataset generated by Zscan4c, Zscan4d and Zscan4f) . This latter finding suggests that Hira inactivation may cause premature activation of transcription required for early embryo development. Although Zscan4 is regulated by Dux in early embryos . The possibility that Dux regulates Zscan4 and other ZGA-related genes before early oocyte maturation seems unlikely given the very low-to-undetectable levels in GV oocytes . This analysis indicates that the depletion of Hira complex (i.e. Hira and Cabin1) in oocytes results in the ‘derepression’ of embryo-associated genes at earlier stages of development. In addition, our findings raise the possibility that the Hira complex may exert a repressive role to prevent precocious embryonic gene expression at the time of oocyte development that coincides with global transcription repression.We noted that, in general, both ZH (888 versus 574) and CabZ (154 vs 53) inactivation causes more of an increase than a decrease in transcription in GV oocytes A. This fZscan4f) C. As ZscZscan4f)  and consZscan4f) , we furt embryos , we did Zscan4 and other genes observed in the ZH and CabZ mutant oocytes reflects an aberrant transcriptional status. To test this hypothesis, we used global or candidate approaches to confirm an increase in transcription.Recently, P=0.0056; P=0.0036; To monitor the global transcription status in Hira complex mutants (i.e. Hira and Cabin1), we performed immunofluorescence (IF) analysis of Pol II PS2, a marker of active transcription elongation, on ZH GV oocytes. Significant upregulation was observed in the ZH KO oocytes compared with ZH Het oocytes  persistently showed higher expression in both ZH or CabZ mutant MII stage oocytes . This result is in accordance with previously published datasets . These combined results support our hypothesis and demonstrate that the Hira complex is essential for the silencing of global transcription, one of the hallmark features of developmental competence in oocytes.Using a candidate approach to confirm these aberrant transcriptions, we performed IF analysis to determine whether Zscan4 protein is indeed increased in ZH and CabZ oocytes. This strategy confirmed a significantly higher level of Zscan4 expression in both ZH KO  and CabZ mutant oocytes . These data suggest that methylation of H3K4 is under the control of Hira-mediated H3.3 incorporation.Immunofluorescence of H3K4me3 shows decreased levels in ZH KO oocytes  and CabZ KO oocytes .We next examined another panel of repressive histone modifications: those affecting methylation of H3K9. The level of H3K9me3 was reduced in both ZH KO  was observed in both ZH  and CabZ KO oocytes . These results strongly indicate that the loss of either Hira or Cabin1 in oocytes leads to reduced levels of repressive histone marks. Moreover, changes in the panH3 level  and H3K27me3  but not H3K27ac  suggest that histone marks may be more broadly altered in the CabZ mutant oocytes .As shown in P=0.0003; The loss of repressive histone marks in Hira and Cabin1 oocytes prompted us to further investigate the presence of possible alterations of chromatin structure in the CabZ mice. First, we examined the overall chromatin accessibility using a DNaseI-TUNEL assay  CabZ KO Fig. S5A-D). The majority of ATAC-seq peaks in oocytes were detected in the intergenic and intron regions . Dynamic changes were also seen in close vicinity to the TSS sites . Biological replicates of ATAC-seq showed highly reproducible results in CabZ Het and KO GV oocytes . We performed integrated analysis using the ATAC-seq and the RNA-seq datasets, and identified 249 genes with consistent changes in their accessibilities and expression levels (Table S3). Genes with consistent change were involved in regulation of transcription factor binding, in cell functions that determine cellular components, and in differentiation and development .In summary, we propose that Cabin1 (and Hira as an extension) modulates chromatin architecture by controlling the deposition of key repressive histone signatures and by maintenance of a globally condensed chromatin architecture. This is a hallmark feature of developmental competence in GV oocytes. Depletion of Cabin1 causes the reduction of repressive histone marks (i.e. H3K4me3 and H3K9me3) coupled with abnormal openness of accessible chromatin loci that leads to misregulation of maternal transcripts ; in treatment (2), the level of H3K4me3 was reduced in the MM-102 treated group ; and the combined treatment (3) successfully induced a reduction in the levels of H3K9me2  and H3K9me3 , and also reduced the level of H3K4me3  BIX-01294, an inhibitor of G9a histone lysine methyltransferase , which din vitro maturation, selection of MII oocytes for parthenogenetic activation and subsequent in vitro culture . This last finding suggests that the alterations of key repressive histones in both ZH and CabZ mutants are not triggered by the upregulation of Zscan4. The mechanism of Zscan4 expression is more likely mediated by upstream pathways that rely on histone modifications. These results also provide evidence that timely expression of Zscan4 is crucial for embryogenesis.To further determine whether misregulation of Zscan4 in the oocyte directly contributes to consequent developmental arrest, we forced the expression of Zscan4 in wild-type oocytes. We used the same strategy for Zscan4d RNA injection in wild-type GV oocytes as for our MO injections, followed by  culture B. SuccesP<0.0001; Knockdown/knockout of maternal genes that are crucial for zygotic genome activation and early embryogenesis  often induces an overall reduction of initiation of translation . Indeed,P<0.0221; Intriguingly, comparison of RNA-seq data from the CabZ KO and CabZ Het 2-cells revealed that top-ranked GO terms of DE downregulated genes appeared to be classified as translation, including rRNA processing, ribosome assembly and ribosome biogenesis E. HPG inFig. S6E). Above all, Rps19, an essential ribosomal protein that is crucial for blastocyst development . Therefore, likely failure to begin ZGA associated with the decline of overall protein production in the CabZ KO two-cell embryos is likely due to the derepression of Zscan4 in oocytes. This, in turn, hampers embryonic development.Moreover, RNA-seq analysis of Zscan4-overexpressing two-cell embryos revealed that transcripts involved in ‘regulation of transcription’, ‘blastocyst development’ and ‘ribosome small subunit assembly’ were overrepresented among the downregulated GO terms . Zscan4 MO and control (Ctrl) MO were microinjected into CabZ KO GV oocytes and the phenotypes were compared with uninjected and Ctrl MO injected CabZ Het GV oocytes. Following maturation to MII, oocytes were parthenogenetically activated and their developmental progression monitored. We observed that CabZ Het oocytes (both uninjected and Ctrl MO injected) can successfully develop to morula-to-blastocyst stage. By contrast, as stated above, CabZ KO GV oocytes (injected with Ctrl MO) revealed impaired developmental potential by showing a very low propensity of embryos reaching two cells and/or developing beyond the two-cell stage. Importantly, with downregulation of Zscan4 on a CabZ KO background, embryo development is partially restored . This rescue experiment further supports the observation that repression of Zscan4 in the oocyte is crucial for oocyte-to-embryo transition.To address whether the abnormally elevated level of Zscan4 in oocytes A,B in HiZscan4). Conversely, incompetent oocytes, such as those resulting from maternal disruption of Hira or Cabin1, fail to establish histone marks and H3.3 incorporation, as well as K4me3 and K9me3 modifications. As a consequence, an aberrant chromatin landscape results in premature activation of gene expression (e.g. derepression of Zscan4 and other embryonic two-cell genes) eventually leading to a developmental arrest.Taken together, our findings can be accommodated in a model F wherebyZscan4, Ddit3 and Gm5039, genes with crucial functions later in embryonic development. Failure to repress these genes causes delayed effects after fertilisation/parthenogenesis in the embryo. Consistent with this conclusion, overexpression of Zscan4 prevents the proper initiation of zygotic genome activation and causes a developmental arrest that recapitulates the key phenotypes of loss-of-function of Hira-complex mutants. A rescue of the Cabin1 phenotype by downregulation of Zscan4 on a Cabin1 null background reinforces this conclusion. Thus, enforcing a repression of transcription in quiescent GV oocytes is an indispensable step towards preparation for the programmed changes in gene expression in the zygote that are crucial for establishing totipotency.Using complementary approaches, we demonstrate that the Hira-complex plays an essential role in the development of oocyte competence to sustain embryo development. This complex is involved in shaping chromatin by promoting incorporation of H3.3 enriched with H3K4me3 and H3K9me3 marks in fully grown quiescent oocytes. The methylated H3.3 reduces chromatin accessibility and represses transcription of two-cell genes, including Our data provide insight into the molecular mechanism involved in this generalised repression of transcription enforced in the GV oocyte prior to resumption of meiosis. Cabin1 has been identified as a vertebrate-specific subunit of Hira complex (there is no Cabin1 homolog in fly). Here, we have identified Cabin1 as a new maternal factor that is crucial for fecundity. Cabin1 homozygous null mutants exhibiting embryonic lethality during organogenesis have been reported . Cabin1 Despite identification years ago of two distinctive features of competent oocytes, chromosomal condensation and formation of heterochromatin rims , as wellAlthough MLL2 (Kmt2d) has been reported as one of the important H3K4 methyltransferases in the oocyte , the rolThe Hira-complex plays an essential role in remodelling of chromatin at a crucial transition of oocyte development. The altered H3.3 methylation that follows disruption of the Hira complex is associated with aberrant chromatin composition, as indicated by ATAC-seq and altered transcription measured by RNA-seq, with most affected genes being upregulated. These observations strongly argue that the repressive H3.3 methylation marks are indispensable for inducing the transcription silencing observed at this stage. The overall aberrant chromatin landscape in Cabin1 mutant oocytes could also be a consequence of the failure of nucleosome replacement of H3.3 mediated by the Hira complex , which lFailure of incorporation of methylated H3.3 in the oocyte leads to an early embryo arrest, indicating a loss of competence to develop as embryos. Our data, as well as those of others, is inconsistent with the idea proposed by Zscan4, a unique two-cell-specific transcription factor, plays pivotal roles during development , cell faZscan4 and of lineage markers such as Sox2, Klf4, and Eomes, which are thought to be expressed in later embryonic stages , supporting the notion that it acts downstream of these histone modifications. All these findings taken together provide a strong link between the H3.3, the Hira complex and the mechanisms of gene silencing occurring at this stage of oocyte development.Intriguingly, embryonic Zscan4 expression is under tight control by chromatin regulators such as the PRC1 complex  and floxed Hira (Hirafl/fl) mouse lines were crossed with a Zp3-cre mouse line  and carried out under the authority of a UK Home Office Project Licence. C57BL/6 wild-type mice were purchased from Charles River Laboratories. The mouse lines used in this study carried conditional floxed alleles for Cabin1 and for Hira on C57BL/6 backgrounds . Floxed Cabin1  and 48 h later fully grown oocytes were isolated. Oocytes were cultured in M16 medium at 37°C, 6% COescribed , matured2 and 5% O2.For zygote collection, 48 h after PMSG administration 7.5 IU human chorionic gonadotrophin  was injected and the mice were mated with C57BL/6 males. The following day, zygotes were collected from the oviducts. Embryos were cultured in KSOM medium at 37°C, 6% COAddgene 61831) and GFP  in vitro transcription RNA were carried out using mMessage mMachine kit (Life Technologies) and a poly(A) tail was added (Applied Biosystems AM1350). Unincorporated nucleotides were then removed with a RNA clean up kit (Zymo R1015).Micromanipulation was performed as described previously , 2014. MTable S4.Immunofluorescence (IF) experiments were performed as previously reported , 2014. I/TTBS overnight. The membranes were incubated in peroxidase donkey anti-rabbit secondary antibody  for 1 h at room temperature. Proteins were visualised by chemiluminescence using ECL (Amersham), and imaged and quantified using an Azure 600 Imager.Oocytes were washed in PBS and frozen at −80°C. Thirty oocytes were lysed in Reducing SDS loading buffer and denatured for 5 min. Proteins were separated by gradient precast 4-12% SDS-PAGE gel (Thermo Fisher) and transferred to Immobilon P membrane (Millipore) by the semi-dry blotting system. Membranes were blocked by 5% skimmed milk for 1 h and incubated with H3K4me3 , H3 , Zscan4  and Gapdh  primary antibodies diluted in 1% milk2 and 5% O2, and supplemented with: BIX-10294 (Stratech) at final concentrations of 0.1 µM and 1 µM (GV oocytes from wild-type mice were cultured in M16 medium containing IBMX (both Sigma) at 37°C, 6% COand 1 µM ; MM-102 and 1 µM ; or a coFor nascent transcription assays, oocytes were incubated in M16 medium with IBMX supplemented with 1 mM EU (5-ethynyl uridine) for 2 h, fixed in methanol, then a Click-iT RNA Imaging kit (Thermo Fisher Scientific) was used and visualisation was by confocal microscopy. Changes in protein expression were monitored using a Click-iT Protein Synthesis Assay kit (Thermo Fisher Scientific). Oocytes and two-cell embryos were cultured in M16 medium with the methionine analogue HPG at a dilution of 1:500. Newly synthesised proteins incorporating the HPG were visualised by confocal microscopy.Table S5.RNA was extracted from oocytes/embryos using PicoPure RNA isolation kit (Arcturus) and cDNA made using iScript cDNA Synthesis kit (BioRad). Brilliant III SYBR green QPCR Master Mix (Agilent Technologies) was used for qRT-PCR and reactions run on a Roche LightCycler 96 real-time PCR system. mRNA levels of genes of interest were calculated by comparison with Hprt1 and H2A mRNA levels using REST software. Primers used are listed in Ten oocytes collected from each experimental treatment or control were pooled and cDNA was amplified using Smart-seq2 v4 kit with minor modifications from manufacturer's instructions . Briefly, oocytes were lysed, and mRNA was captured and amplified with the Smart-seq2 v4 kit (Clontech) following the manufacturer's instructions. RNA-seq libraries were constructed using Nextera XT DNA Library Preparation Kit (Illumina) and multiplexed using Nextera XT Indexes kit (Illumina) according to the manufacturer's instructions. Libraries were quantified by Qubit (Life Technologies) and Tapestation 4200 (Agilent). Pair-end 150 bp sequencing was performed on an Illumina HiSeq X sequencer.P<0.05 and fold change >2. Gene Ontology (GO) and pathways analysis was performed using IPA , with an FDR adjusted P≤0.05 deemed statistically significant.Multiplexed sequencing reads that passed filters were trimmed to remove low-quality reads and adaptors by TrimGalore-0.4.3. Clean reads were aligned to the mouse genome (GRCm38/mm10) by using STAR with default parameters. Approximately 30 million reads per individual cell were generated. Individual mapped reads were adjusted to provide FPKM (fragments per kilobase of exon model per million mapped fragments) values with RefSeq genes as reference. Differential gene expression analysis was performed by a Partek Flow GSA algorithm with default parameters. The genes were deemed differentially expressed if they provided a false discovery rate (FDR) adjusted 2 and NP-40 (0.5%)] for 15 min on ice to prepare the nuclei. Nuclei were then incubated with the Tn5 transposase  and tagmentation buffer at 37°C for 30 min with shaking on a thermomixer at 500 g. Tagmentated DNA was purified using MinElute Reaction Cleanup Kit (Qiagen). PCR was performed to amplify the ATAC-seq libraries using Illumina TrueSeq primers and multiplex by indexed primers under the following PCR conditions: 72°C for 3 min; 98°C for 30 s; 15 cycles of 98°C for 15 s, 60°C for 30 s and 72°C for 3 min; followed by 72°C for 5 min. The ATAC-seq libraries were purified twice with the 1.1× AMPure beads (Beckman) and quantified by Qubit (Life Technologies) and Tapestation 4200 (Agilent). ATAC-seq libraries were sequenced on the Illumina HiSeq X platform with 150 bp end reads.The ATAC-seq libraries of oocytes were prepared as previously described with minor modifications , 2018. Bhttps://bedtools.readthedocs.io/en/latest/). The annotations of genomic features, including transcription start sites , transcription end sites (TES), promoters, CDS, introns, 5′ UTR, 3′ UTR and intergenic regions were downloaded from UCSC genome browser. Promoters were defined as 500 bp upstream and downstream of the TSS for each annotated gene (TSS±500 bp). Intergenic regions were defined as genomic regions before the TSS of the first gene and after the TES of the last gene in each chromosome, and in between the TES and TSS of two consecutive genes.All quality assessed ATAC-seq reads were aligned to the mouse reference genome using Bowtie 2.3 with following options: --very-sensitive -X 2000 --no-mixed --no-discordant. Alignments resulted from PCR duplicates or locations in mitochondria were excluded. Only unique alignments within each sample were retained for subsequent analysis. Principal component analysis (PCA) was performed on pairwise correlation data in R with functions prcomp. ATAC-seq peaks were called separately for each sample by MACS2  with folP<0.05 and fold change >2). Gene ontology (GO) and pathways analysis was performed using IPA, with an FDR adjusted P≤0.05 deemed statistically significant.For downstream analysis, we normalised the read counts by computing counts scaled by the number of sequenced fragments multiplied by one million (CPM). Chromatin accessibility in each developmental stage was assessed by the number of ATAC-seq fragments (FPM) mapped to the defined gene region in all samples from that stage. Integrative analysis on the changes of chromatin accessibilities and their corresponding gene expression changes between treatment groups was conducted using the genes with differential accessibilities (two-fold change threshold) and the differential expressed genes  for 5 min before digesting with 0.2 U/ml of DNase I (Oocytes were permeabilised by 0.5% Triton X-100 in pre-extraction buffer (300 mM sucrose, 25 mM HEPES, 1 M CaCl DNase I . Embryos2 test was used as previously described (t-test with unequal variance was used. All error bars indicate s.d.For analyses of the percentage of oocyte maturation and embryonic development, the χescribed , 2014. F


Malignant colorectal cancers (CRCs) are characterized by enhanced migration and invasion thus acquiring the ability to metastasize. We have previously shown that the small GTPase TC10-like (TCL) contributes to aggressive migration and invasion in malignant CRC cells. TCL expression is differentially expressed in CRC cells and can be upregulated by hypoxia although the underlying epigenetic mechanism is not fully appreciated. Here, we report that differential TCL expression in CRC cells appeared to be associated with histone H3K9 methylation. RNAi screening revealed that the lysine demethylase KDM4B was essential for TCL transcription in CRC cells. KDM4B interacted with and was recruited by the sequence-specific transcription factor ETS-related gene 1 (ERG1) to the TCL promoter to activate transcription. Mechanistically, KDM4B mediated H3K9 demethylase facilitated the assembly of pre-initiation complex (PIC) on the TCL promoter. KDM4B knockdown attenuated migration and invasion of CRC cells. Importantly, KDM4B expression was upregulated in human CRC specimens of advanced stages compared to those of lower grades and associated with poor prognosis. Together, these data uncover a novel epigenetic mechanism underlying malignant transformation of CRC cells and suggest that KDM4B may be considered as a therapeutic target in CRC intervention. Colorectal cancer (CRC) ranks the third in terms of incidence and mortality rate in the United States regardless of gender . It is eTranscriptional events in mammalian cells are programmed by the coordinated actions between sequence-specific transcription factors and epigenetic co-factors. The epigenetic machinery, including histone and DNA modifying enzymes , chromatTC10-like (TCL), alternatively termed RHOJ, is a member of the RHO small GTPase superfamily. TCL was initially identified by screening the human and murine cDNA database for expressed sequence tags (ESTs) that share homology with the TC10 RHO GTPase . FurtherHuman CRC cells  were maintained in RPMI1640 medium supplemented with 10% FBS as previously described . FLAG-taRNA was extracted with the RNeasy RNA isolation kit (Qiagen) as previously described ,c,d. RevWhole cell lysates were obtained by re-suspending cell pellets in RIPA buffer  with freshly added protease inhibitor (Roche) as previously described . Specifi3), diluted with the re-ChIP buffer , and subject to immunoprecipitation with a second antibody of interest. Precipitated genomic DNA was amplified by real-time PCR with the following primers: TCL proximal promoter, 5'-AGTGGGACCCCTAGTGTTTTC-3' and 5'-AGGAAATCATGGGTTTCCTG-3'; TCL distal promoter, 5'-GGGTTCCTATAAATACGGACTGC-3' and 5'-CTGGCACTGCACAAGAAGA-3'. A total of 10% of the starting material is also included as the input. Data are then normalized to the input and expressed as percent recovery relative the input. All experiments were performed in triplicate wells and repeated three times.Chromatin Immunoprecipitation (ChIP) assays were performed essentially as described before . In brieWound healing assay was performed as previously described . Cells wTranswell assay was performed as previously described . Twenty-in vitro HDM assay using a commercially available kit  per vendor recommendations. The assay was performed in triplicate wells and repeated three times. Data were normalized to the control group and expressed as relative HDM activity.DNA affinity pull-down assay was performed as previously described . Nucleart text was performed using an SPSS package. Unless otherwise specified, values of p smaller than 0.05 were considered statistically significant.Sample sizes reflected the minimal number needed for statistical significance based on power analysis and prior experience. Two-tailed Student’s TCL promoter. As shown in TCL promoter in the four CRC cells. On the other hand, when levels of repressive hisone modifications were examined by ChIP it was discovered that trimethylated H3K27 (First, we sought to determine whether TCL expression in different CRC cells could be accounted for by differential histone modifications surrounding the proximal ed H3K27  and trimed H3K27  were simed H3K27  and trimed H3K27  surroundBased on the observation that low H3K9 methylation levels correlated with high TCL expression in CRC cells, we hypothesized that a specific histone demethylase may be responsible for the regulation of differential TCL transcription. To verify this hypothesis, siRNAs targeting several individual KDMs were transfected into CRC cells. As shown in Being an epigenetic factor, KDM4 inherently lacks the ability to recognize specific DNA sequences . InsteadFirst, DNA affinity pull-down experiments were performed to verify whether ERG1 might be associated with an H3K9 demethylase activity. As shown in Next, we examined the possible mechanism whereby KDM4B may regulate differential TCL transcription in CRC cells. The assembly of a PIC on gene promoters represents a key step in transcriptional regulation . ChIP asBecause we have previously shown that TCL plays an important role in promoting CRC cell migration and invasion, we determined the functional relevance of KDM4B in this regard. As shown in TCL gene, which encodes a pro-metastatic small GTPase, in CRC cells. Although our analysis indicates that elevated KDM4B expression in CRC patients predicts poor survival (via activating TCL transcription. KDM4B is a member of the KDM4 lysine demethylase family with specificity toward di- and tri-methylated H3K9 . KDM4B hsurvival , we suspWe show here that KDM4B activates TCL transcription by interacting with ERG1. There are multiple reports that point to a functional interplay between ERG1 and the epigenetic machinery. via extensive crosstalk, the modulation of chromatin structure to facilitate PIC assembly. Whetstine and colleagues have recently reported KDM4B, in cooperation with the H3K4 methyltransferase MLL and the H3K4 demethylase KDM5B, controls site-specific DNA amplification (We propose that KDM4B activates TCL transcription by facilitating the assembly of the RNA polymerase II PIC. Two issues warrant further attention. First, although it is generally agreed that the recruitment of RNA polymerase II PIC is only possible on a compatible chromatin microenvironment defined by specific histone and DNA modifications , it is ufication . We havefication . WhetherIn summary, our data here unveil a novel epigenetic mechanism underlying malignant transformation of CRC cells. There are a few limitations regarding our study. First, TCL expression was not compared between normal intestinal epithelial cells and various CRC cells. Therefore, it remains unknown whether TCL could contribute to the malignant transformation of intestinal epithelial cells. Second, although we show that there appears to be an inverse correlation between KDM4B expression and survival rate of CRC patients, it cannot be concluded with certainty that KDM4B levels can be used as an independent marker for CRC prognosis due to the small sample size. Further analysis to include more patient data is needed to solidify the prognostic value of KDM4B. Small-molecule KDM4B inhibitors have been designed and demonstrated to be effective in cell culture . Our datThe original contributions presented in the study are included in the article/YF, BC, YZ, and JC designed and performed the experiments, and collected and analyzed the data. JC and YF provided the funding. YX wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


TERT) at various levels which include transcriptional, post-transcriptional, and post-translational stages. The pathways and biological molecules involved in these processes are also being deciphered with the advent of enabling technologies such as next-generation sequencing (NGS), ribonucleic acid sequencing (RNA-Seq), liquid chromatography-mass spectrometry (LCMS/MS), and many others. It has also been established that TERT possess diagnostic value as most adult cells do not express high levels of telomerase. Indeed, studies have shown that prognosis is not favorable in patients who have leukemias expressing high levels of telomerase. Recent research has indicated that targeting of this gene is able to control the survival of malignant cells and therefore offers a potential treatment for TERT-dependent leukemias. Here we review the mechanisms of hTERT regulation and deliberate their association in malignant states of leukemic cells. Further, we also cover the clinical implications of this gene including its use in diagnostic, prognostic, and therapeutic discoveries.The proliferative capacity and continuous survival of cells are highly dependent on telomerase expression and the maintenance of telomere length. For this reason, elevated expression of telomerase has been identified in virtually all cancers, including leukemias; however, it should be noted that expression of telomerase is sometimes observed later in malignant development. This time point of activation is highly dependent on the type of leukemia and its causative factors. Many recent studies in this field have contributed to the elucidation of the mechanisms by which the various forms of leukemias increase telomerase activity. These include the dysregulation of telomerase reverse transcriptase ( However, this is compensated for by an initiator like CCTCTCC sequence. It also contains two E boxes for Myc binding, several GC boxes for Sp1 binding, and a CCAC box [The promoter of CCAC box . These mCCAC box ,6.TERT expression in adult humans are limited to stem cell, germline, and tissues with high turnover rates. It has been disclosed that the highest levels are found in testicular tissues which give rise to spermatocytes [TERT expression is not normally observed in adult somatic cells and their atypical occurrence is usually due to TERT promoter mutations leading to the abrogation of telomerase silencing [atocytes ,20, inteatocytes , and hepatocytes . TERT exilencing . This phTERT can either bind directly to the promoter or interact by forming complexes to downregulate TERT expression. Direct acting repressors include retinoblastoma (RB), myeloid-specific zinc finger protein (MZF2), activator protein 1 (AP1), Wilms tumor 1 (WT1), and menin [TERT expression by forming complexes and interacting with other proteins including Mad1, the HTLV-1 oncogene TAX, tumor suppressors BRCA1/Nmi and p53, interferon regulatory factor 1 (IRF1), and transforming growth factor β (TGFβ) [TERT expression [TERT expression by E-box binding [TERT via interactions with protein kinase C [TERT expression via tumor suppressor CDKN1B (p27) [TERT [Negative transcriptional regulators of nd menin ,24,25. Tβ (TGFβ) ,28,29,30pression ,31,32. S binding . Receptokinase C . In othekinase C ,35. IRF17) [TERT ,37.TERT expression. Positive regulators that act directly include human N-acetyltransferase like protein (hALP), transcriptional elements interacting factor (TEIF), signal transducer and activation of transcription 3 (STAT3), the oncoproteins Ews-ETS, hypoxia inducible factor 1 (HIF1α), and the transcription factor c-Jun [TERT expression by forming a complex with max (c-Myc/Max) and binding to the E-box region whilst survivin acts via SP1/c-Myc binding. The viral oncogene E6/NFX1 on the other hand induces TERT expression by p53 degradation, activation of c-Myc, and disruption of upstream stimulatory factor (USF) based repression [Positive transcriptional regulators also function via direct and indirect interactions with the promoter region to activate or c-Jun . Activatpression ,39,40.TERT expression depending on the condition. E2F acts as a TERT repressor in cancer cells; however, the condition is reversed in normal cells where it activates the expression of TERT. This transcription factor controls TERT regulation by binding to the GC box region on the promoter [TERT in cancer cells by forming a complex with Sp3, while in Kaposi sarcoma associated herpes virus (KSHV), Sp1 becomes an activator via interactions with latency-associated antigen—briefly known as LANA [TERT while activation of TERT is mediated by p73β expression [There are some regulators, such as transcription factors E2F and specificity protein 1 (Sp1), upstream stimulatory factors (USF1/2), and tumor suppressor p73, which act as both repressors and activators of promoter ,42. USF1promoter ,44. Sp1  as LANA ,46,47. Tpression ,49,50.hTERT has been widely studied for the past few decades and the discoveries relating to its mechanisms of action have established the importance of hTERT in cancer biology. In line with these observations, the regulation of hTERT at post-transcriptional level has demonstrated close association with mRNA alternative splicing and non-coding RNA functions [hTERT are not well understood [hTERT by microRNA (miRNA) has recently contributed to the understanding of the diverse regulatory mechanisms of hTERT [hTERT, miRNAs are able to act as tumor suppressors or oncogenes depending on their target gene [hTERT regulation in different cancers has been shown to be regulated by different miRNAs. Collectively, it has been established that every miRNA involved with hTERT regulation works synchronously with different regulators of the target genes.unctions ,52,53,54of hTERT . MicroRNof hTERT ,51,53. Bget gene ,51,52. IhTERT gene have made substantial progress as evidenced by recently published studies. It has been reported that miRNAs can post-transcriptionally alter hTERT transcripts directly or indirectly [hTERT complementary sites located in the 3′-untranslated region (3′UTR) to restrict hTERT expression by negatively regulating their translation [hTERT [PI3K/AKT signaling pathway. Therefore, together these epigenetic gene regulators influence hTERT gene expression in cancers. In contrast, miRNAs may also indirectly target the transcription factors involved in hTERT regulation [MicroRNAs (miRNAs) are short endogenous non-coding RNA molecules consisting of 20–24 nucleotides loaded onto Argonaute (Ago) proteins to regulate gene expression ,56. Theydirectly ,54. MiRNnslation ,62,63. Snslation ,59. Eachn [hTERT ,65. Thesgulation ; howeverhTERT mainly involve phosphorylation and ubiquitination by kinases and ligases respectively [hTERT activity [Post-translational modifications of hTERT could modify protein stability, subcellular localization, and ultimately, enzyme activity . To dateectively ,53,66. Bactivity .hTERT in a serum and pH-dependent manner within the hypoxic environment of solid tumors [In phosphorylation, kinases such as protein phosphatase 2A (PP2A) interact with c-Abl tyrosine kinase protein, leading to a threefold reduction of telomerase activity by dephosphorylation ,68,69. Od tumors ,72.hTERT translation through ubiquitination are Makorin RING finger protein 1 (MKRN1), SMAD specific E ubiquitin protein ligase 2 (Smurf2), CHIP (C terminus of Hsc70-interacting protein), E6AP, and the E6 ubiquitin ligase proteins. MKRN1 and Smurf2 are E3 ubiquitin ligases, which play a role as negative regulators of hTERT. Overexpression of MKRN1 results in decreased telomerase activity and shortens telomeres through ubiquitination and subsequently dampens hTERT expression in vitro and in vivo [hTERT gene by targeting NFX1091 for degradation [hTERT [hTERT in leukemia especially on the promoter and proximity regions, which is further discussed in Among the regulators reported to modify  in vivo ,67,69. S in vivo ,73,74. C in vivo ,69,75. In [hTERT . DNA methTERT. Regulation of hTERT via miRNAs are often mediated through indirect mechanisms by targeting upstream proteins. The work of Pourbagheri-Sigaroodi et al. (2019) revealed that TERT expression is regulated by miRNAs, which control the inhibition of NF-κB [p23, a heat shock protein 90 cochaperone essential for telomerase assembly and telomere length maintenance [hTERT via downregulation of c-myc [More recent studies on non-coding RNAs have identified that this class of regulatory RNAs play vital roles in influencing the dysregulation of of NF-κB . Additiontenance . Anotherof c-myc . In termof c-myc .TERT gravely affects the prognosis of the disease and is known to exert its mechanism of action via a plethora of modifications including epigenetics, mutations, amplifications, structural variants, and influences on oncogenes. The prevalence of TERT dysregulation remains to be determined in each subtype of leukemia and is also highly dependent on the population and recruitment criteria of each study. An early study has indicated that it affects approximately half of AML (53.3%) patients [TERT dysregulation is present in all acute promyelocytic leukemia  patients in their cohort [hTERT dysregulation was only observed in limited cases of relapsed childhood ALL [hTERT mutations are not linked to predisposition to childhood acute leukemia [Studies on the various forms of leukemia have disclosed the dysregulation of patients , while ar cohort . Other shood ALL , while aleukemia . In termleukemia ,84,85. ITERT dysregulation was reported to occur via TERT promoter methylation. However, contrary to canonical research, DNA methylation would increase TERT activity, as methylation occurs on the genomic region bordering the TERT promoter. This results in the inaccessibility of repressor on this site, which is proximal to the TERT promoter, thereby increasing the affinity of TERT promoter binding of crucial activators leading to TERT hyper-expression  binding. The result suggested an increase in CTCF binding, which could be seen from the reduction of C-Myc (Transcription Activator) binding and subsequent downregulation of TERT transcription. This further led to TERT reduction induced senescence in chronic myeloid leukemia [Mechanism of pression A. The obleukemia .TERT also occur via gene amplification, which results in an increase in gene copy number (GCP). This phenomenon translates to increased gene expression levels due to relatively higher abundance of mRNA resulting from amplification  treatment resulted in the accumulation of TERT in the nucleoplasm when compared to the nontreated group in which TERT accumulated within the nucleolus. Furthermore, telomeric length was also found to be implicated following Gleevec treatment of CML cells. It was observed that K562 accumulates short telomeric ends (1 Kb<) when comparing cells treated with Gleevec to non-treated cells. The results were also consistent with hTERT phosphorylation levels where a decrease in phosphorylation states were observed post Gleevec treatment suggesting that hTERT activity is induced by BCR-ABL via direct hTERT phosphorylation. Additionally, transcription of hTERT was also found to be mediated via BCR-ABL tyrosine kinase activity as it was found that Gleevec treatment reduced hTERT mRNA abundance in K562. Further experimentation reported that, this was mediated via BCR-ABL activation of STAT5a through phosphorylation, which resulted in STAT5a-Phos binding to the TERT promoter. This was further confirmed via STAT5a inhibitor treatment, which significantly reduced TERT expression. Luciferase activity assay confirmed that the full length contains STAT5a binding as co-expression of the reporter with constitutive plasmid baring STAT5a resulted in over a twofold increase in hTERT expression [The CML fusion oncogene pression . Additiopression .TERT was targeted indirectly through upstream factors crucial for TERT activation via inhibition of kinase activity. Imatinib mesylate (IM) is currently one of the major drugs used in CML treatment. However, treatment of CML using IM was found to potentiate CML towards leukemogenesis as it was reported that it enhances expression of hTERT via phosphorylation of STAT5 [of STAT5   via direct TERT suppression. Co-treatment with fludarabine was also found to potentiate apoptosis in BL treated with BIBR1532 [TERT with BIBR1532 and IM could serve as a potential treatment for CML.Since it is crucial to target BIBR1532 . This syTERT in CLL is still largely unexplored. However, correlation studies report that telomeric length serves as an initial prognostic marker in CLL disease progression [TERT activation occurs via STAT5 mediated binding and its phosphorylation state [The mechanism of dysregulation of gression . This wagression . As in ton state ,97,98. TTERT promoter was crucial in different stages of leukemia development as it confers different functional advantages. As mentioned earlier, telomeric shortening is a contributing factor in disease onset. It was found that this is crucial in telomerase overexpression as promoter methylation contributes to increase in initial telomeric activity in order to repair shortened telomerase during disease onset, a mechanism of immortalization in cancers [TERT studies in CLL and its contributing mechanism via promoter methylation, which would allow us to better understand and properly treat this malignancy via direct TERT targeting. It is interesting to note that TERT dysregulation leads to disease development as previous studies in other types of leukemia associates this with chemo-resistance, disease progression, and poor prognosis [Furthermore, in terms of DNA methylation status it was found that methylation of  cancers . This asrognosis ,101.TERT in CLL was also observed via single nucleotide polymorphisms (SNPs). Different SNPS led to different potential in TERT induced self-renewal [TERT hyperactivity in these SNPs bearing patients in which may contribute to disease development. The same report also mentioned that the rs2736100 SNP were associated with early stage of disease (I-II), while rs35033501 was associated with late stages. Whether this mutation is acquired following disease progression was not mentioned, however it is interesting to note that different SNPs result in different prognosis in patients [Dysregulation of -renewal . It was patients .TERT and TERT C gene also contributed to an increase in telomeric ends. It was found that TERTC rs10936599 SNP with C allele had a significant association with CLL development as high allele frequency was observed in CLL patients. The same study also observed that TERT rs2736100 occurring in patients bearing CLL was associated with increased CLL risk [Additionally, variation within the CLL risk . How thiCLL risk .TERT dysregulation in CLL. This includes the TERT/CLPTM1L locus in chromosome 5p15 and t translocation, which resulted in the fusion of TERT to the IGH gene [IGH locus, which contains strong promoters, may have enhanced TERT activation as a significant increase in TERT expression was observed in CLL harboring this translocation [TERT suppressor p53 [Chromosomal aberrations were also found to contribute to IGH gene . The IGHlocation . Besidesssor p53 ,109. TheTERT in CLL it was found that targeting factors crucial in telomerase assembly may contribute to increase in sensitivity of CLL treatment with fludarabine. A study showed that using a telomerase inhibitor Imelstate (IS) with fludarabine does not lead to reduction in telomerase activity. However, another report on the association between NOP17 and telomerase assembly suggested that IS and fludarabine treatment dysregulate NOP17, resulting in impairment of TERT assembly at telomeric ends [TERT regulation in CLL is not extensively studied, this field of study may be worth exploring in order to better understand TERT dysregulation in CLL.In the case of drug studies against ric ends . Furtherric ends . Though ric ends . Using tTERT dysregulation that has been identified as one of the contributors to the pathogenesis of leukemia and has been reported in both AML and ALL.Acute leukemia refers to an aggressive form of leukemia that typically progresses rapidly over a short period of time. It can be further subdivided into acute myeloid (AML) and acute lymphoid leukemia (ALL) . TERT dyTERT overexpression could promote the development of t AML by working in tandem with AML-ETO possibly through two main mechanism: telomere integrity maintenance and inhibition of replicative senescence [TERT gene amplification was identified through fluorescence in-situ hybridization (FISH) in AML samples and was positively correlated with higher telomerase activity, which may contribute to AML leukemogenesis [TERT SNVs of CC genotypes (rs2853669 and rs2736100) that are associated with an increased risk of AML were identified [TERT gene, whereas rs2853669 is positioned at the TERT promoter. Inflammation is one of the hallmarks of cancer and it was found that CC variant of rs2853669 was linked to increased level of inflammatory cytokines IL-6 and TNF-α, which may contribute to cancer malignancy. In the past decade, many studies have sought to identify TERT variants in various types of cancer, as these variants could be the driver of carcinogenesis. One of the most commonly found mutation in AML is G>A conversion in codon 1062 situated at exon 15 of the TERT gene, resulting in alanine>threonine substitution (A1062T) [TERT mutation had a relatively poorer prognosis as this mutation is associated with shorter overall survival, higher relapse incidence, and greater rate of treatment-related toxicity [TERT has been the focus of many studies as it is believed to aid in the malignant transformation of cells [TERT promoter results in TERT transcription activation that subsequently leads to higher telomerase activity [TERT proximal promoter and a partial exon 1 (TERTpro/Ex1) region exhibits CpG site hypermethylation in AML cell lines and primary blasts [TERT is also regulated by oncogenic signaling FLT3-ITD . FLT3, a type of receptor tyrosine kinase is often mutated in AML with internal tandem duplications within the juxtamembrane domain. Compelling evidence has implicated the role of FLT3-ITD mutation in leukemogenesis especially in the case of AML [TERT, resulting in increased telomerase activity that contributes to AML pathogenesis [hTERT promoter [hTERT. These results, therefore, point to the combinatory interaction of hTERT promoter methylation, histone modifications, and chromatin accessibility in dysregulation of hTERT transcription. A study on childhood AML further delineated that there exist a correlation between telomerase activity and methylation of cyclin-dependent kinase inhibitor 2B (CDKN2B) CpG islands [Acute myeloid leukemia (AML) is a type of leukemia that arises from the myeloid progenitor of hematopoiesis and gives rise to immature blasts in the bone marrow and/or peripheral blood. Lin et al. (2016) reported that nescence . In addiogenesis ,116,117.ogenesis . In a stentified . rs27361(A1062T) ,122,123.toxicity ,121. Epiof cells . Hypermeactivity . Accordiy blasts . This die of AML . Recentlogenesis . Anotherogenesis . The stupromoter . In this islands . It was TERT expression and decrease telomerase activity in AML patient samples and cell lines [TERT expression and telomerase activity [TERT expression in AML has not been fully described to date.Conventional chemotherapy is one of the therapeutic approaches used to treat AML patients, whereby it is common that a combination of chemotherapeutic drugs is used. Each of the chemotherapeutic drug aims to target and inhibit the cancer cells via various mechanisms. One of the mechanisms targeted by a commonly used drug for AML, 5-azacytidine (5-AZA) is DNA methylation. 5-AZA, a DNA methyltransferase inhibitor (DNMTI), has been shown to downregulate ll lines . Similaractivity . HoweverTripterygium wilfordii, that demonstrated antileukemic activity by inhibiting c-Myc transcription and its downstream target, TERT in AML cells [P16 (CDKN2A) and P21 (CDKN1A). Thus, triptonide is known as “multiple-hits” senescence-promoting agent. Furthermore, a tyrosine kinase inhibitor (TKI), PKC412 exerts its inhibitory action on TERT via FLT3-ITD in a c-Myc dependent manner that functions as the transcription factor of TERT [In addition, small molecule inhibitors have been emerging as potential therapeutic alternatives to treat AML patients. This is exemplified by Triptonide (diterpene triepoxide), a small biological molecule derived from the herb ML cells . It is a of TERT .hTERT expressing autologous dendritic cells (TERT-DC) was able to improve their overall survival rate associated with favorable recurrence-free survival [TERT-targeted immunotherapy has also become the subject of many cancer therapeutic studies. A study by Sandri et al. (2017) demonstrated that TERT865-873-specific, TCR-engineered T-cell lymphocytes were able to halt AML progression in vivo . The maisurvival . hTERT-DTERT is generally upregulated in ALL. This indicates that TERT overexpression could play a role in leukemogenesis [TERT gene amplification was detected through FISH analysis in ALL patient samples coupled with increase in telomerase activity [TERT promoter region, SNP, rs2735940 with C to T substitution, is able to induce TERT expression by upregulating its transcriptional activity in ALL [TERT promoter region SNP, rs2735940 with C to T substitution, does not increase the risk of ALL [TERT in pediatric ALL has been demonstrated by Borssén et al. (2011) [TERT promoters in 24% of ALL patient samples shows greater methylation pattern as compared to normal bone marrow samples. However, findings from this study have established that there is a negative correlation between TERT promoter methylation status and TERT gene expression. It is also important to note that the incidence of methylation is higher in T cell-ALL than B-cell precursor ALL, indicating that TERT promoter methylation can be used to differentiate between specific ALL subtypes.Acute lymphoblastic leukemia (ALL) is a type of leukemia that arises from the lymphoid progenitor of hematopoiesis and gives rise to immature blasts in the bone marrow and/or peripheral blood. Previous studies have reported that the expression of ogenesis ,136. TERactivity . Single activity . Sheng ey in ALL . Not surk of ALL . Further. (2011) . TERT prTERT expression and telomerase activity in vitro in a dose-dependent manner. In addition, BIBR1532 suppressed the expression of c-Myc that acts as a transcriptional activator of TERT. Doxorubicin, a commonly used chemotherapeutic drug, was found to exert the same inhibitory action as BIBR1532 on TERT and c-Myc. This study also reported that the combination of doxorubicin together with BIBR1532 showed a greater inhibition of TERT and c-Myc transcription as compared to its individual counterparts. Thus, this combination therapy can be an effective therapeutic approach for pre-B ALL.TERT-targeted therapies are quickly gaining popularity as a therapeutic option due to the role of TERT as a universal tumor associated antigen (TAA). BIBR1532, a small biological molecule specific for telomerase inhibition, has been studied by Bashash et al. (2017) for its application in pre-B ALL . BIBR153TERT-targeted immunotherapy is being studied for its application in ALL. According to a study by Sandri et al. (2017), TERT865-873-specific, TCR-engineered T-cell lymphocytes were able to halt ALL progression in vivo . SimilarTo date, a vast majority of experimental treatments against hTERT have not been able to display promising clinical benefits in studies on leukemia. This is primarily due to several unresolved issues, including the absence of relevant animal models, the inability to obtain high resolution molecular structure of the human telomerase enzyme, and the development of resistance towards inhibitor-based therapies .The challenge in developing mouse models for targeting TERT mainly stems from global expression of telomerase in adult somatic cells . CurrentElucidation of the molecular structure of telomerase has also been hampered by failure to isolate the enzyme in large quantities due to low cellular abundance, which therefore impedes downstream purification and crystallographic works . This hahTERT require extended durations to manifest clinical effects as they rely on the attrition of telomeres to arrest the cell cycle [hTERT. Furthermore, malignant cells may also escape treatment due to their ability to survive with low levels of hTERT and potential to evolve resistant clones, such as adapting telomere maintenance to the ALT pathway as earlier mentioned, before treatment becomes effective.In addition, studies have revealed that drugs targeting ll cycle . Off tarTERT expression [In order to address the aforementioned pitfalls, potential strategies have been improvised to overcome each of the shortcomings. TERT inhibitors with high potency, which are capable of fully depleting telomerase activity, have been proposed to exert greater selective pressure and overcome resistance in cancer cells . This stpression .The revelation that cancer cells express TERT epitopes as a surface marker enabled the development of immunotherapies to target telomerase . The devTERT-based vaccines rely largely on eliciting recognition and adaptive immune responses in T-cells against telomerase epitopes via MHC class I or II molecules . A phaseAdoptive cell therapy was developed to use the patient’s own T lymphocytes with anti-cancer activities (either primed or engineered) in an ex vivo expanded manner. Recent studies have shown that adoptive cell transfer with high avidity telomerase-specific T-cells were able to suppress prostate cancer progression and improve survival of preclinical cancer models . HoweverhTERT promoter driven E1 gene expression [Oncolytic adenoviruses such as telomelysin have been developed to infect and replicate selectively in malignant cells through the control of pression . Preclinpression . AdditioOligonucleotide inhibitors such as imetelstat work by complementary binding to the TERC template, thereby acting through competitive inhibition of telomerase. Its mechanism of action lead to attrition of telomeres, which prompts DNA damage response and ensuing cell death. However, hematological side effects were observed in a dose-dependent manner when imetelstat was administered into patients with solid tumors . A laterBIBR1532 is a small molecule inhibitor that works by non-competitive binding to a conserved hydrophobic pocket (FVYL motif), which impairs interactions between TERT and TERC . TreatmeTelomeric regions rich in guanine have been observed to form secondary structures known as G-quadruplex via Hoogsteen hydrogen bonding. G-quadruplex stabilizers are able to prevent access of DNA helicases to telomeres and therefore increase propensity towards DNA damage response and subsequent cell death . One sucNucleoside analogues including 5-fluoro-2′-deoxyuridine thiophosphate (5-FdU) and 6-thio-2′-deoxyguanosine (6-thio-dG) function as uncapping agents which prevent recruitment and formation of the shelterin complex on telomeres ,160. TheTERT expression during leukemogenesis and the stage where this gene is upregulated has contributed immensely to the understanding of the fundamental roles of TERT in various forms of leukemias. Additionally, it has also been proven that different mechanisms are involved in the expression of this gene including transcriptional, genetic, and epigenetic regulators. These mechanisms of activation and dysregulation of TERT in onco-hematological diseases are progressively being elucidated and in recent years, researchers have deciphered many novel variants, modifications, pathways, and mediators leading to its overexpression. The latest findings have identified mutations in the hTERT gene, methylation of its promoter, and microRNAs targeting its transcript as leading areas of fundamental studies and highly promising for therapeutic development. Indeed, progress in clinical trials have determined that chemical drugs and biomolecules targeting various regulators of TERT have immense potential in controlling the proliferation and metastasis of leukemias, primarily via arrest of cellular division. Noteworthy, in recent years there have been renewed interests in targeting hTERT as a therapeutic strategy due to developments in several areas including immunotherapies, drug discovery, gene therapy, and radiotherapy. Combination of agents specific to TERT and other anti-cancer drugs have also been widely explored with many studies indicating synergistic effects, reduced dose requirements and decreased side effects (In summary, many preclinical and clinical studies on leukemia have concluded that TERT plays a pivotal role in disease progression and deteriorating prognosis of patients. Studies aimed at determining the factors influencing  effects . The sur


Foxl2 generally presents a sexually dimorphic expression pattern in animal gonads and is highly expressed in the ovary. However, few studies on the transcriptional regulation of Foxl2 have been documented. To understand the transcriptional regulating of Foxl2 high expression in the ovary, we used the Y1H system, a high throughput approach, for the first time to screen the transcription factors binding to the high transcriptional activity region of Foxl2 promoter in Zhikong scallop (Chlamys farreri) gonads. In the present study, the highly transcriptional activity promoter sequence of Cf-Foxl2 was determined at −1000~−616 bp and 11 candidate factors were verified to involve in Cf-Foxl2 transcriptional regulation. Our findings provided valuable data for better understanding the specific transcriptional regulation mechanism of Foxl2 in the ovary and would further assist in the breeding of aquacultural bivalves.Foxl2 is an evolutionarily conserved female sex gene, which is specifically expressed in the ovary and mainly involved in oogenesis and ovarian function maintenance. However, little is known about the mechanism that regulates Foxl2 specific expression during the ovary development. In the present study, we constructed the gonadal yeast one-hybrid (Y1H) library of Chlamysfarreri with ovaries and testes at different developmental stages using the Gateway technology. The library capacity was more than 1.36 × 107 CFU, and the length of the inserted fragment was 0.75 Kb~2 Kb, which fully met the demand of yeast library screening. The highly transcriptional activity promoter sequence of C. farreri Foxl2 (Cf-Foxl2) was determined at −1000~−616 bp by dual-luciferase reporter (DLR) assay and was used as bait to screen possible transcription factors from the Y1H library. Eleven candidate factors, including five unannotated factors, were selected based on Y1H as well as their expressional differences between ovaries and testes and were verified for the first time to be involved in the transcriptional regulation of Cf-Foxl2 by RT-qPCR and DLR. Our findings provided valuable data for further studying the specific regulation mechanism of Foxl2 in the ovary. Foxl2 was first studied in Homo sapiens, in which Foxl2 mutation causes blepharophimosis-ptosis-epicanthus inversus syndrome (BPIS) and premature ovarian failure [FOXL2 (forkhead box L2) is a member of the forkhead superfamily which is characterized by the forkhead box/wing-helix DNA binding domain . Foxl2 w failure . As an e failure ,5,6 but  failure , skeleta failure , reactiv failure .Foxl2 has been revealed to be highly expressed in the ovaries of many animals, but weakly or even not expressed in the testis, showing a sexually dimorphic expression pattern [Capra hircus, loss of Foxl2 leads to a sex reversal from female to male, in which the embryonic XX gonads develop into testes instead of ovaries [Oreochromis niloticus, Foxl2 is revealed to involve in the production of estrogen maintaining ovarian differentiation [Gallus gallus, Foxl2 has been reported to play an important role in ovarian differentiation by antagonizing Sox9 [Sox9 [anti-Müllerian hormone [Esr2 [CYP19A1 [Foxl2 have been rarely documented. Li et al. [Foxl2 ectopic expression in the testis by directly binding the Tcf/Lef binding site of Foxl2 promoter, and the CTNNB1-Foxl2 pathway further induces the transformation of testicular Sertoli cells into ovarian granular cells in Mus musculus. Han et al. [Foxl2, and the STAT3-FoxL2 pathway plays an important role in HeLa cell apoptosis. A high motility group protein HMGA2 has been revealed to regulate metastases and epithelial-to-mesenchymal transition of chemoresistant gastric cancer by up-regulating Foxl2 expression [Foxl2, and which TFs are involved in the Foxl2 specifically expression in the ovary.Up to now,  pattern ,10,11,12 ovaries . In fishntiation , and itsing Sox9 . Up to nx9 [Sox9 , anti-Mü hormone , estrogene [Esr2 , and ste[CYP19A1 ,19,20, ei et al.  found can et al.  reportedpression . HoweverFoxl2 has also been revealed to present a sexually dimorphic expression pattern with significantly higher expression in ovary than that in testis, such as in Zhikong scallop Chlamys farreri [Mizuhopecten yessoensis [hyriopsis cumingii [Argopecten irradians irradians [C. farreri, one of the most important mariculture scallops in China, is a dioecious and sexually stable bivalve. In our previous research, we did not find the M. musculus-like CTNNB1 regulating Foxl2 in C. farreri, suggesting that the transcriptional regulation of Foxl2 in C. farreri may be different from that in M. musculus. To screen TFs regulating specific high expression of Foxl2 in the ovary, we identified a promoter sequence of Cf-Foxl2 with high transcriptional activity, constructed C. farreri gonadal yeast one-hybrid (Y1H) library using Gateway technology, and further verified TFs that may bind to this high transcriptional activity sequence through Y1H system. Outcomes of the present study would provide a theoretical basis to resolve the regulatory mechanisms of Foxl2 in C. farreri and further assist in the breeding of aquacultural bivalves.Bivalve is a kind of invertebrate with rich biodiversity and frequently occurred sexual reversal. In these species,  farreri , Yesso sssoensis ,25, frescumingii , and bayrradians . The ZhiC. farreri with a mean shell height of 6.38 ± 0.33 cm were collected from the Nanshan Aquatic Products Market in Qingdao, China. Gonads (ovaries and testes) were dissected, rinsed with PBS (pH 7.4), immediately frozen in liquid nitrogen, and then stored at −80 °C for extractions of genomic DNA and total RNA.Healthy male and female According to the morphologic characteristics described by Liu et al. , the gonCf-Foxl2 gene sequence was obtained from the C. farreri genome (scaffold41309. 29:724895-741680) [http://www.softberry.com/berry.phtml?topic=fprom&group=programs&subgroup=promoter (accessed on 10 January 2021). The genomic DNA of C. farreri ovary at the proliferative stage was prepared using Plant Genomic DNA Kit . A 1905 bp promoter sequence (−1705~+200) of Cf-Foxl2 was amplified using the ovarian cDNA as a template with the primers Fwd −1705/Rev +200  were linearized using QuickCut XhoI and HindIII restriction enzymes , and then these four fragments were respectively subcloned into pGL3-Basic and sequenced (2. The transient transfections of the constructed vectors (1000 ng in each assay) were performed in 24-well plates with HEK293T cell confluency of up to 90% and Invitrogen Lipofectamine® 2000 Reagent  diluted in Opti-MEM medium  according to the manufacture’s instruction as previously reported [A dual-luciferase reporter (DLR) assay system was employed to obtain the high transcriptional activity region in the promoter sequence. Briefly, the 1905 bp sequence was divided into four fragments A and ampequenced . HEK293Treported . LuciferC. farreri male and female gonads of three stages using Trizol  according to the manufacturer’s protocol. The extracted total RNAs were analyzed with 1.2% agarose gel electrophoresis and Bioanalyzer 2100 , and quantified with NanoDropTM One/OneC . An equal mass of each sample was mixed together and the mRNA was separated and purified with the OLIGOTEX kit  according to the manufacturer’s instructions. The double-strand cDNA was synthesized and ligated with attB1 adapters with the CloneMiner II cDNA Library Construction kit  according to the manufacturer’s instruction and ligated with attB1 adapters.Total RNA was extracted from C. farreri gonad was produced with the Gateway cloning technology [® II enzyme mix  and cloned into pDONR222 vector and Escherichia coli DH10B (BP recombination reaction) for the construction of a primary library. Then, the primary library was further cloned into pGADT7-DEST vector and Saccharomyces cerevisiae Y187 with LR Clonase® II enzyme mix  to construct the secondary library (LR recombination reaction).A cDNA library of chnology . BrieflyE. coli clones on the plate/50 μL × 1000 (dilution factor) × 103 × total volume of library bacterial solution (mL). The titer was calculated with cells/mL = Number of S. cerevisiae clones on the plate x dilution factor. A total of 24 monoclonal colonies were randomly selected to test the size of inserted fragments and calculate the recombination rate of the library . PCR amplification was performed using universal sequencing primers of the pGADT7-DEST vector , titer (secondary library), and inserted fragments inspection. The library capacity was calculated using the formula CFU/mL = Number of Cf-Foxl2 promoter was amplified using the primer pairs Y1H-5/Y1H-3  were respectively linearized with the BstB I enzyme  and integrated into the Y1HGold yeast strain, which was selected on synthetic defective SD/-Ura agar plate at 30 °C for 5 days. The recombinant Y1HGold strain was confirmed by PCR with the primer pairs Y1H-5/Y1H-3  described in the manufacturer’s instructions. The high transcriptional active region (−1000~−616 bp) of -5/Y1H-3 , and the-5/Y1H-3 .Foxl2 bait vector were prepared as recipients, and the pGADT7-DEST prey plasmids (the secondary library) were transferred into them and screened on SD/−Leu agar plates with 100 ng/mL AbA at 30 °C for 5 days. Colonies with a >2 mm diameter were selected as positive candidates and amplified in SD/−Leu liquid medium; these vectors were then isolated with the Yeast Plasmid Extraction Kit . Their sequences were identified by PCR with the primer pairs pGADT7-DEST-F/pGADT7-DEST-R (The competent Y187 yeast transformants containing the pAbAi-7-DEST-R  and SangC. farreri transcriptome database MolluscDB. Available online: http://mgbase.qnlm.ac/home (accessed on 9 December 2021) [2 FC| > 1 as well as p < 0.05. The candidate factors exhibiting sexual expression differences were selected for further verification.The TPM (transcripts per million) values of the candidate factors were retrieved from the er 2021)  and the er 2021) . The sigIn order to exclude false-positive results, the full-length CDS sequences of the candidate factors were amplified with gene-specific primers , cloned Cf-Foxl2. Two types of transfection systems were utilized: (i) single transfection: the recombinant pGL3-Foxl2 vector containing the high transcriptional activity sequence detected in 2.2 was transfected into HEK293 cells alone; (ii) co-transfection: the pGL3-Foxl2 vector was co-transfected with the constructed candidate factor-expression vector above  respectively. The pGL3-Foxl2-Luc + pcDNA3.1 (+) group was used to calibrate expression levels of different transfection systems.The full-length CDS sequences of candidate factors were amplified with primers  and wereEf-1α was used as a reference gene [® 480 Real-time fluorescence quantitative PCR instrument . All reactions were performed in triplicate. The 2–ΔΔCt method was used to analyze the mRNA expression level of these factors [The mRNA levels of the candidate factors in the gonads during the reproductive cycle were detected using RT-qPCR with specific primers , and Ef-nce gene ,34. The  factors .p < 0.05, and extreme statistical significance was set at p < 0.001, respectively.All data were presented as the mean ± SEM from three samples and three technical replicates. Statistical analysis was tested using one-way ANOVA followed by Duncan’s test . For all analyses, statistical significance was set at Cf-Foxl2 gene sequence (scaffold41309. 29:724895-741680) was 21, 376 bp in full-length and consisted of 2 exons and 1 intron . Therefore, the region (−1000~−616 bp) in the Cf-Foxl2 promoter sequence was determined as a high transcriptional activity region which would be used as a target sequence for screening the related transcription factors in the Y1H system.A 1905 bp promoter sequence (−1705/+200 bp) of rev +200 , and thepromotor B were copromotor C. In addC. farreri at the different stages were mixed equally as one sample, and its RIN value was determined to be 7.9  was constructed by connecting cDNA to the pGADT7-DEST vector using homologous recombination. The recombinant vectors were electroporated into E. coli DH10B, the inserted fragments were determined with a size range from 0.75 Kb bp to 2 Kb in length, a recombination efficiency was obtained 100% (7 CFU/mL (S. cerevisiae Y187 yeast library (secondary library) ranged from 0.75 Kb bp to 2 Kb in length, with a recombination efficiency of 100%  as bait. A total of 348 positive monoclonal colonies were obtained, which was 145 for the first screening and 203 for the second one. Sixty-four coding sequences were identified from the screening, of which 10 sequences were shared in both screenings. Furthermore, eight functionally unannotated sequences were obtained  between testes and ovaries  containing the Cf-Foxl2 high transcriptional activity region as well as the effector vector pcDNA3.1 (+) containing full-length ORF of the factors. The results . Among them, six target genes  were expressed significantly higher in the ovary than in the testis  showed inconsistent differences between sex at different stages  with a partial sequence of the first exon, P1 (−1705/+1) without the sequence of the first exon, P3 (−616/+1) with only the core promoter sequence. Considering that the truncation of Cf-Foxl2 promoter should avoid the separation of transcription factor binding sites predicted by PROMO. Available online: http://alggen.lsi.upc.es/cgi-bin/promo_v3/promo/promoinit.cgi?dirDB=TF_8.3/ (accessed on 16 June 2021), JASPAR. Available online: https://jaspar.genereg.net/ (accessed on 16 June 2021) and GPMiner. Available online: http://gpminer.mbc.nctu.edu.tw/ (accessed on 16 June 2021) software, P2 (−1000/+1) was truncated between P1 and P3. The results  provides a convenient gene-centered (DNA to protein) approach to identify transcription factors that can bind the DNA sequence of interest genes . A high-e of 7.9 , and thee of 7.9 , indicate of 7.9 , suggest7 CFU/mL , and the7 CFU/mL , which s library . MoreoveCf-Foxl2 high transcription activity sequence (−1000~−616 bp) by Y1H , Vitellogenin-4 (Vtg), Protein singed (Ps) and three unannotated factors  exhibited higher expression in the ovary than that in the testis during the annual development of C. farreri. As a new member of the steroid dehydrogenase family, HSDL2 is considered to be involved in lipid metabolism, and the occurrence, proliferation, development of cancer cells [HSDL2 mRNA exhibited the highest level in the ovary, which was 154.9-fold higher than that in testis at the mature stage , commonly considered as a nutritional source as well as participating innate immune defense [Cf-Foxl2 expression. However, further research is needed to illustrate detailed mechanisms.Tissue-specific transcription factors play important roles in regulating the expression and biological functions of target genes. In the present study, we verified for the first time that eleven candidate factors interacted with ) by Y1H  reverse on assay . Based oon assay  and the on assay  at diffeer cells ,47. In tre stage B, and itCf-Foxl2 A. Meanwh control , suggeston level . In part control , and theelopment D was als defense ,49,50, wC. farreri testis than that in the ovary during the annual development  which was significantly higher expressed in elopment H. Considrominent , it is sThe situation of the other four factors  was more complicated, in which the expression levels of these genes presented inconsistent sex differences in bisexual gonads at different developmental stages I–L. MoreFoxl2 specific expression have been revealed, such as HMGA2 in chemotherapy-resistant gastric cancer of M. musculus [M. musculus HeLa cells [Foxl2 transcription in gonads has only been reported in M. musculus, in which CTNNB1 was found to induce the transformation of Sertoli cells into granular cells by activating ectopic expression of Foxl2 in the testis of M. musculus [Cf-Foxl2 high transcription activity sequence by YIH library screening. Unfortunately, we did not find the transcription factors as reported. In addition, we cloned the CTNNB1 sequence of C. farreri, and carried out transient co-transfection of CTNNB1 and Cf-Foxl2 promoter sequence to test whether CTNNB1 could regulate Cf-Foxl2 transcription. The results showed that CTNNB1 did not change the Cf-Foxl2 expression level  to try to find these reported transcription factors [Cf-Foxl2, but only the STAT3 transcription factor was identified. Since the STAT3 binding site was predicted to be outside the Cf-Foxl2 high activity region obtained in this study, and its expression level was not different between ovary and testis based on the gonadal transcriptome data of C. farreri, further experimental verification was not performed. In conclusion, the specific transcription factors regulating Foxl2 expression should be species specific and tissue specific.Previously, several transcription factors regulating musculus ; STAT3 iLa cells ,39; whilmusculus . In thison level  and thus factors ,22,23,39Cf-Foxl2 promoter was identified to be at −1000 to −616 bp. A number of transcription factors potentially involved in the specific regulation of Foxl2 expression in the C. farreri gonad were screened using a high-quality C. farreri gonadal Y1H library constructed with Gateway technology. Eleven candidate factors were verified to significantly up-regulate Cf-Foxl2 transcription levels, and HSDL2 and Uf1 may be important for the high expression of Cf-Foxl2 in the ovary. Our data are meaningful to better understand the specific transcriptional regulation mechanism of Foxl2 in the ovary.In the present study, a high transcriptional activity region of the


This protocol tracks engaged transcription complexes across functional genomic regions demonstrated in human K562 erythroleukemia cells.Nascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide analytical steps to (1) identify transcribed regulatory elements For complete details on the use and execution of this protocol, please refer to   •de novo genome-wideIdentification of transcribed regulatory elements •Quantification of engaged transcription complexes at functional genomic regions•Measuring distribution of transcription regulators across the functional genomic regions•Revealing functional genomic regions from nascent transcription data de novo genome-wide, (2) quantify engaged transcription complexes at enhancers, promoter-proximal regions, divergent transcripts, gene bodies, and termination windows, and (3) measure distribution of transcription machineries and regulatory proteins across functional genomic regions. This protocol tracks engaged transcription complexes across functional genomic regions demonstrated in human K562 erythroleukemia cells.Nascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide analytical steps to (1) identify transcribed regulatory elements  Transcription is a fundamental process in every organism, and its coordination defines RNA synthesis in the cell. A plethora of transcription factors, cofactors, chromatin remodelers and RNA-processing complexes orchestrate the process of RNA synthesis  complexes, and the three-dimensional architecture of the linear DNA molecules  for PRO-seq have been reported. Here, we begin with sequenced and mapped PRO-seq reads in bed format (https://www.ncbi.nlm.nih.gov/geo/) using accession code GSE181161.Wet-lab protocols  and compd format B and strd format C. The bed format C and unrd format , remappehttp://hgdownload.soe.ucsc.edu/goldenPath/. Here, the human hg38 file (2020-08-17) is downloaded in step 4 using wget (https://www.gnu.org/software/wget/).We derive functional genomic regions from the profile of active transcription and the refGene-annotated coordinates of gene transcripts. The refGene list of transcripts can be downloaded from the UCSC genome golden path: de novo using the pattern of divergent transcription (via the web interface (https://django.dreg.scigap.org/) or installed locally (https://github.com/Danko-Lab/dREG). For broad accessibility, the web-based tool is used here. Unnormalized bigWig files are generally provided with PRO-seq data. If needed, the code below converts a bed file reporting the whole read (https://www.encodeproject.org/software/bedgraphtobigwig/). The required chrSizes.txt file is a two-column data frame that contains the chromosome names and the sizes , obtainable for the appropriate genome from http://hgdownload.cse.ucsc.edu/goldenpath/.awk ‘$6 == "+"’ PROseq.bed | genomeCoverageBed -i stdin -3 -bg -g chrSizes.txt > PROseq_pl.bedgraphawk ‘$6 == "-"’ PROseq.bed | genomeCoverageBed -i stdin -3 -bg -g chrSizes.txt > PROseq_temp.bedgraphawk ‘{$4=$4∗-1; print}’ PROseq_temp.bedgraph > PROseq_mn.bedgraphbedgraphToBigWig PROseq_pl.bedgraph chrSizes.txt PROseq_pl.bigWigbedgraphToBigWig PROseq_mn.bedgraph chrSizes.txt PROseq_mn.bigWigEnhancers can be identified cription . In thiscription . dREG inole read C. One ofhttps://github.com/Vihervaara/ChIP-seq_analyses).Regulatory proteins coordinate every step of transcription. In this protocol, the functional genomic regions are first identified and color-coded to show enhancer regions in green, sites of divergent transcription (div) in purple, promoter-proximal regions (pp) in orange, gene body (gb) in black, region around CPS in light blue and termination window (tw) in pink A and 3B.https://www.r-project.org) and coordinates of functional genomic regions are compared to active sites of nascent transcription using bedtools ((https://bedtools.readthedocs.io/en/latest/).The data-analyses reported here are conducted in the command line environment of the Apple OS X operating system. Lists of genomic coordinates are processed in R  de novo A. Subseqde novo A. Sites de novo . For simvia GitHub .Enhancer coordinates reported here are the dREG-identified sites of divergent transcription that do not overlap with any annotated promoter of a gene. Active genes, instead, are further divided into distinct regions B. A browTiming: 1–3 hThis section identifies transcribed regulatory elements in the investigated cell line and condition.1.https://django.dreg.scigap.org/. Log in.a.Choose dREG peak calling.b.plus strand file to the correct box.Upload the unnormalized 3′-coverage bigWig c.minus strand file to the correct box.Upload the unnormalized 3′-coverage bigWig plus strand and -1 for the minus strand).Please note that the bigWig files need to be unnormalized  to describe your run and press Launch. The run time depends on the size of the file and available processing capacity, commonly ranging 1–3h.Create an account at 2.When the run is complete, download the prefix.dREG.peak.full.bed.gz file and gunzip it.3.Move the downloaded file to the working directory and rename it to a simpler form:mv ∼/Downloads/K562_hg38.dREG.peak.full.bed /pathToWorkingDirectory/dREGcalls_hg38_K562.bedTiming: 30 minThese steps (4–6) divide genes into functional regions.4.Download RefGene datafile, gunzip it and open it in R.http://hgdownload.soe.ucsc.edu/goldenPath/hg38/database/refGene.txt.gzwget -c -O hg38.refGene.txt.gz gunzip hg38.refGene.txt.gzRrefGene = read.table#gives the number of rows and columns in the refGene dataframedim(refGene) #shows the first six rows of the dataframehead(refGene)  #shows information on each dimensionstr(refGene) 5.Name the refGene columns and remove unnecessary columns and chromosome entries.names(refGene) =c#maintains chromosomes 1-22, X, Y and M.refGene = refGene  #drops the extra levels removed above.refGene$chr = factor(refGene$chr)  refGene = refGene#look at the dataframe againhead(refGene)  6.Generate coordinates of functional regions for every annotated gene transcript.### Subset the genes based on the strand:refGene_pl = subsetrefGene_mn = subsetplus strand:### Genes on the # TSSrefGene_pl$TSS = refGene_pl$txStart # CPSrefGene_pl$CPS = refGene_pl$txEnd  # region of divergent transcriptionrefGene_pl$DIVs = refGene_pl$txStart-750 refGene_pl$DIVe = refGene_pl$txStart-251# promoter-proximal regionrefGene_pl$PPs = refGene_pl$TSS-250  refGene_pl$PPe = refGene_pl$TSS+249# genebodyrefGene_pl$GBs = refGene_pl$TSS+250  refGene_pl$GBe = refGene_pl$CPS-501# CPS regionrefGene_pl$CPSs = refGene_pl$CPS-500  refGene_pl$CPSe = refGene_pl$CPS+499# termination windowrefGene_pl$TWs = refGene_pl$CPS+500  refGene_pl$TWe = refGene_pl$CPS+10499minus strand:#### Genes on the # TSSrefGene_mn$TSS = refGene_mn$txEnd  # CPSrefGene_mn$CPS = refGene_mn$txStart  # divergent transcription regionrefGene_mn$DIVs = refGene_mn$txEnd+251  refGene_mn$DIVe = refGene_mn$txEnd+750# promoter-proximal regionrefGene_mn$PPs = refGene_mn$TSS-249  refGene_mn$PPe = refGene_mn$TSS+250# genebodyrefGene_mn$GBs = refGene_mn$CPS+501  refGene_mn$GBe = refGene_mn$TSS-250# CPS regionrefGene_mn$CPSs = refGene_mn$CPS-499  refGene_mn$CPSe = refGene_mn$CPS+500# termination windowrefGene_mn$TWs = refGene_mn$CPS-10499  refGene_mn$TWe = refGene_mn$CPS-500#### combine the data of plus and minus stands:refGene = rbindrefGene$promC1 = refGene$TSS-500refGene$promC2 = refGene$TSS+500#### generate data files:write.tablewrite.table], file="hg38_refGenes_TSSpm500.txt", col.names=F, row.names=F, quote=F, sep="\t")save.image      # saves the above entries in the Rq       # exits Ry        # answers ‘yes’ for saving the workspace imageIn the RefGene data file, the ‘txStart’ is smaller than the same transcript’s ‘txEnd’. This is convenient when working with the coordinates of genes, but it leads to different columns reporting different functional sites depending on whether the plus or the minus strand encodes the gene. For example, the annotated TSS for genes on the plus strand is reported as txStart, while the TSS for genes on the minus strand is reported as txEnd. In the following steps, we add a column ‘TSS’ that reports the annotated TSS for each transcript. We then output a file that reports a 1000-nt window around the TSS. These windows of 1000 nt are intersected with the coordinates of dREG-identified sites of divergent transcription in step 7 to identify genes with active transcription and distal sites of divergent transcription, i.e., enhancers. We also obtain transcript-specific coordinates of promoter-proximal region (PP), divergent transcription (DIV), gene body (GB), CPS, and termination window (TW) according to the scheme in https://github.com/Vihervaara/functionalGenomicRegions).Please note that an R script comprising the steps from reading the refGene file in step 4 to the end of step 6 is provided in GitHub 9.Generate a new data frame in R that contains only actively transcribed genes. In essence, the ‘refGene’ data frame generated in step 6 is reduced here to contain only gene transcripts which initiate transcription. The ‘txID’ column contains an individual identification code for each transcript variant.refGeneAct = subset10.Write files that contain the coordinates of promoter-proximal and divergent transcription regions. These coordinates were generated in step 6.write.table], file="ppPolII.txt", col.names=F, row.names=F, quote=F, sep="\t")write.table], file="divTx.txt", col.names=F, row.names=F, quote=F, sep="\t")11.Remove short genes before generating files with the gene body coordinates. This stage is needed to omit gene transcripts, where, due to shortness of the gene, the gene body would overlap with the promoter-proximal region (stretching to +500 from TSS) and CPS (starting from −500 from CPS) windows.shortGenes = subsetrefGeneAct_ = subset#in K562 cells mapped against hg38, 351 active genes are removed at this stage.12.Write the files for the CPSs, gene body coordinates and transcription windows.write.table], file="CPS.txt", col.names=F, row.names=F, quote=F, sep="\t")write.table], file="TW.txt", col.names=F, row.names=F, quote=F, sep="\t")refGeneAct_ = subset #ensuring no negative gene body lengths remain.write.table], file="geneBody.txt", col.names=F, row.names=F, quote=F, sep="\t")save.imageqyOf note: In the RefGen for hg38 file, short genes constitute 3,575 transcripts. Of these, only 351 genes were uniquely mappable, identified as ‘Active’ and, therefore, removed from our list of active gene transcripts in K562 cells.The steps 8–12 can also be run via an R script provided in GitHub .Timing: 20 minIn steps 13 and 14, active sites of transcription are allocated to individual functional genomic regions. The active sites of transcription are derived from the nascent transcription sequencing data.13.a.echo retaining 3prime most coordinate of the bed file awk ‘$6 == "+"’ PROseq_K562_hg38.bed > tempPL.bed awk ‘$6 == "-"’ PROseq_K562_hg38.bed > tempMN.bedSplit the file based on the strand of the mapped readb. awk ‘{$2 = $3; print}’ tempPL.bed > tempPL_3p.bed awk ‘{$3 = $2; print}’ tempMN.bed > tempMN_3p.bedActive site of transcription (3′-most nt) is the coordinate given in the third column of plus strand reads and the second column for minus strand reads. In this step, the active site of transcription (single nt) will be placed both to the second and the third column.c. cat tempPL_3p.bed tempMN_3p.bed | tr ‘ ‘ ‘\t‘ > temp_3p.bed sortBed -i temp_3p.bed > PROseq_K562_hg38_3pnt.bed rm ∗temp∗The reads from plus and minus strands are combined, the data is converted to tab-delimited, and the reads sorted based on genomic coordinates. Intermediary files are removed.Generate a bed file that only contains the 3′-nucleotide (active site of transcription) of each read B. In the14.Intersect the coordinates of nascent transcription with the coordinates of functional genomic regions.Note: To allocate each engaged Pol II complex only once, we use the -u option in the bedtools intersect command and sequentially allocate the coordinates of active transcription to the distinct genomic categories. In each round, two different files are generated: File 1 retains active sites that localize to the given functional category (options -u and -wa). File 2 reports the active sites that do not localize to the given functional category (controlled with option -v). The file 2 will be used in the subsequent round to ensure that each engaged Pol II is allocated only to one genomic region. The order of the intersections is: i) promoter-proximal regions, ii) sites of divergent transcription, iii) enhancers, iv) CPSs, v) gene bodies, and vi) termination windows. In this order, promoter-associated Pol II molecules are not counted into enhancer transcription. Furthermore, transcription at intragenic enhancers is allocated to enhancers instead of gene bodies. Finally, termination windows can be relatively short or extend over several kilobases  are allocated to distinct functional categories.Timing: 10 minThe code in step 15 calculates engaged Pol II molecules in each category of functional genomic regions . Engaged Pol II that does not occur in any of the categories is indicated as unannotated. Step 15 further analyses the distribution of engaged Pol II across the functional genomic regions  in the dataset. Here, we only have a single sample and, therefore, focus on the distribution (proportions) of active sites across the genomic regions. With PRO-seq data, a normalization factor that accounts for differences in data handling and sequencing depth can be computed. Detailed description of normalization factors is out of the scope of this study. In brief, invariant whole-genome spike-in from a distinct organism can be added to all samples before the run-on reaction. This equal amount of foreign chromatin provides a count of nascent transcription against which the samples can be normalized . If desired, the color-code for each category of functional genomic regions can be adjusted here by changing the rgb values.awk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="243,132,0"; print }’ ppPolCounts.tmp > ppPolCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="178,59,212"; print }’ ppDivCounts.tmp > ppDivCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="115,212,122"; print }’ enhancerCounts.tmp > enhancerCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="0,0,0"; print }’ geneBodyCounts.tmp > geneBodyCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="103,200,249"; print }’ CPSCounts.tmp > CPSCounts.bedawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="255,54,98"; print }’ TerminationWinCounts.tmp > TerminationWinCounts.bed18.Combine the files. Add an extra column "." to obtain a genome browser compatible bed file for visualization.cat ppPolCounts.bed ppDivCounts.bed enhancerCounts.bed geneBodyCounts.bed CPSCounts.bed TerminationWinCounts.bed > catRegions.tempawk -F ‘\t’ -v OFS=‘\t’ ‘{ $(NF+1) ="."; print }’ catRegions.temp > catRegions2.temp19.Reorganize the columns and add a header track.awk ‘{print $1 "\t" $2 "\t" $3 "\t" $7 "\t" $5 "\t" $6 "\t" $2 "\t" $3 "\t" $8}’ catRegions2.temp > catRegions3.tempawk ‘!seen++’ catRegions3.temp | sortBed > catRegions4.temptouch headerLine.txtecho track name="functional_genomic_regions" itemRgb="On" >> headerLine.txtcat headerLine.txt catRegions4.temp > functionalGenomicRegions.bedrm ∗.temprm headerLine.txtNote: As mentioned above, the number of engaged Pol II complexes at the distinct genomic regions generated in this protocol originates from raw read counts of the data. This count depends on the sequencing depth. To get a normalized count of engaged Pol II, the column 4 (reporting raw count) in the ’functionalGenomicregions.bed’ file can be multiplied with a normalization factor.The generated ’functionalGenomicregions.bed’ file can be read in genome browsers to show the identified functional genomic regions as well as the count of engaged Pol II at each indicated region . As starting material, please use a file that reports the summit coordinate of each peak, named with '_summits.bed', for example: K562_TBP_summits.bed, K562_GATA1_summits.bed, K562_CTCF_summits.bed, K562_H3K36me3_summits.bed .Obtain or generate datasets of interest. Place them in the folder of your working directory. Here, we used TBP, GATA1, CTCF, H3K36me3, NELFe, p300 and RAD21 ChIP-seq data . We remab.for x in the code below. In the loop, the ${x} will be replaced with the factor name, one listed factor after another.The peak summits for each given chromatin-associated factor are intersected with the distinct genomic regions. The strategy described in step 14 is used to ensure that each identified enrichment of a factor at the genome (peak) is counted once. For efficiency, we use a loop function that takes one bed file of mapped peak summits at a time. To define which datasets are analyzed in the loop function, please place names of factors in quotation marks, separated by a space, after the c.Run the code below using the factors of your choice. Please, ensure that the files are placed in the correct folder (working directory) and that the file names correspond to the names in the code. The files listing the coordinates of functional genomic regions were generated in steps 1–12.Count genome-associating factors at distinct functional genomic regions.for x in "TBP" "GATA1" "CTCF" "H3K36me3"do## Factor-derived reads at promoter-proximal regionsbedtools intersect -u -wa -a K562_${x}_summits.bed -b ppPolII.txt > ${x}_K562_ppPolII.bedbedtools intersect -v -a K562_${x}_summits.bed -b ppPolII.txt > ${x}_ppRemoved.bed## Factor-derived reads at the sites of divergent transcriptionbedtools intersect -u -wa -a ${x}_ppRemoved.bed -b divTx.txt > ${x}_K562_ppDiv.bedbedtools intersect -v -a ${x}_ppRemoved.bed -b divTx.txt > ${x}_ppdivRemoved.bed## Factor-derived reads at enhancersbedtools intersect -u -wa -a ${x}_ppdivRemoved.bed -b enhancers.bed > ${x}_K562_enhancers.bedbedtools intersect -v -a ${x}_ppdivRemoved.bed -b enhancers.bed > ${x}_ppdivEnhRemoved.bed## Factor-derived reads at CPSbedtools intersect -u -wa -a ${x}_ppdivEnhRemoved.bed -b CPS.txt > ${x}_K562_CPS.bedbedtools intersect -v -a ${x}_ppdivEnhRemoved.bed -b CPS.txt > ${x}_ppdivEnhCPSRemoved.bed## Factor-derived reads at GBbedtools intersect -u -wa -a ${x}_ppdivEnhCPSRemoved.bed -b geneBody.txt > ${x}_K562_GB.bedbedtools intersect -v -a ${x}_ppdivEnhCPSRemoved.bed -b geneBody.txt > ${x}_ppdivEnhCPSgbRemoved.bed## Factor-derived reads at termination windowsbedtools intersect -u -wa -a ${x}_ppdivEnhCPSgbRemoved.bed -b TW.txt > ${x}_K562_TW.bedbedtools intersect -v -a ${x}_ppdivEnhCPSgbRemoved.bed -b TW.txt > ${x}_K562_noGene_noEnh.bedrm ∗Removed.beddone21.a.script Factor_counts_at_functional_regions.txtInitiate the script that collects factor counts at the functional genomic regions.b.Plot the counts of rows in each intersected bed file.c.control + D in the terminal window.Terminate the log script by pressing Plot the counts of chromatin-associated factors at distinct categories of functional regions.22.The file ‘Factor_peaks_at_functional_regions.txt’ reports the number of ChIP-seq peaks at each functional category. ined see E and 4C.functional_genomic_regions.bed file, each block represents the coordinates of an individual functional genomic region. The block color codes for the category of the region . In UBET2 and PPP1R12B genes are shown, and two intergenic enhancer candidates identified on the longer isoform of PPP1R12B. Furthermore, the protocol counts engaged Pol II complexes that localize to each identified functional genomic region. The raw count of active sites of transcription is given in column 4 of the functional_genomic_regions.bed file, appearing above the color-coded block when visualized in a genome browser (HBE1 gene to the region’s upstream locus control element (LCR). In PRO-seq used here :https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"/bin/bash -c "$. Likewise, the names of the files in the scripts should be updated to match the user-specific input files.Please find the code as shell and R script files in the GitHub repository viher@kth.se).Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Anniina Vihervaara (This study did not generate new unique reagents.