The mechanism by which protein complexes interact to regulate the deposition of post-translational modifications of histones remains poorly understood. This is particularly important at regulatory regions, such as CpG islands (CGIs), which are known to recruit Trithorax (TrxG) and Polycomb group proteins. The CxxC zinc finger protein 1  is a subunit of the TrxG SET1 protein complex, a major catalyst of trimethylation of H3K4 (H3K4me3).Here, we used ChIP followed by high-throughput sequencing (ChIP-seq) to analyse genomic occupancy of CFP1 in two human haematopoietic cell types. We demonstrate that CFP1 occupies CGIs associated with active transcription start sites (TSSs), and is mutually exclusive with H3K27 trimethylation (H3K27me3), a marker of polycomb repressive complex 2. Strikingly, rather than being restricted to active CGI TSSs, CFP1 also occupies a substantial fraction of active non-CGI TSSs and enhancers of transcribed genes. However, relative to other TrxG subunits, CFP1 was specialised to TSSs. Finally, we found enrichment of CpG-containing DNA motifs in CFP1 peaks at CGI promoters.We found that CFP1 is not solely recruited to CpG islands as it was originally defined, but also other regions including non-CpG island promoters and enhancers.The online version of this article (10.1186/s13072-018-0230-0) contains supplementary material, which is available to authorized users. In vertebrate genomes, CpG dinucleotides are relatively depleted, except in specific DNA regions with a high density of this dinucleotide. These regions are known as CpG islands (CGIs) and consist of short ~ 1000 bp) interspersed CpG-rich and predominantly unmethylated DNA sequences 000 bp in. InteresSeveral proteins have been described in mammals that bind specifically to CGIs. These proteins contain the CxxC zinc finger (ZF-CxxC) domain and include CFP1, MLL1, MLL2, KDM2A, KDM2B, TET1 and TET3 . Whilst Multiple phenotypes have been documented for CFP1 deficiency, both at the cellular and organismal level. CFP1 is required for development , differeHere we have analysed the genome-wide occupancy of CFP1 in two divergent human haematopoietic cell types: erythroid (ERY) and EBV-transformed B-lymphoid (EBV) cells. Previous studies using chromatin immunoprecipitation (ChIP) have been restricted to a couple of available antibodies with moderate signal, which consequently limited the sensitivity of the analysis , 29. HerWe previously reported an association of CFP1 binding with transcription at the α-globin locus, using a mouse model in which the mouse α-globin locus was replaced by the human locus , 31. In To identify genomic regions recruiting CFP1, we performed ChIP-seq in primary human lymphoid and erythroid cell types  in CFP1-bound regions, we plotted averaged read depth in a 2-kb window surrounding TSSs for CFP1 versus H3K27me3. As shown in Fig. We next assessed CFP1 occupancy at TSSs by gene class, specifically housekeeping genes and developmentally regulated/tissue-specific genes Fig. a, left aWe then extended our analysis to genome-wide sets of housekeeping and developmentally regulated/tissue-specific genes. First, we used the Illumina Body Map RNA-seq data set of 16 human tissues to identify 5354 genes with similar expression across most or all of these tissues and termed these housekeeping genes Fig. ”. Anothep ≤ 1.6 × 10−12, Additional file To address the confounding effect of alternate TSSs of transcribed genes, some with or without CGIs, and some transcribed or not, we next limited our analysis to putatively expressed TSSs. These were identified by accessible chromatin, which was defined by the presence of 1x-normalised/input-subtracted ATAC (Assay for Transposase-Accessible Chromatin) signal > 10 within 1 kb of the TSS. Most putatively expressed TSSs regardless of gene class were marked by CGIs  and 7/44 (16%) tissue-specific TSSs in ERY and EBV, respectively Fig. d. More tR = 0.28, p < 10−200, and R = 0.26, p = 1.4 × 10−12, in CGI and non-CGI TSSs, respectively); however, this correlation was visually identifiable in ERY . Within the limits of public data sets, these results demonstrate a weak positive relationship between Pol II and CFP1 at accessible, transcribed TSSs.We next examined more closely the relationship between CFP1, Pol II and expression level using public RNA-seq data sets. We limited our analysis to accessible TSSs ; this accessibility makes these strong candidate TSSs for the observed expression Fig. a, b. AccUnmethylated CpG dinucleotides at TSSs are known to recruit CFP1 through its ZF-CxxC domain . HoweverTo address localisation of CFP1 at enhancers, putative enhancers were defined by open chromatin (ATAC-seq) and the presence of Pol II in non-TSS regions Fig. ”. Elevatp < 10−200, t test, both cell types); this, however, was less intense than in accessible TSSs ; in lymphoid cells a weaker but specific overrepresentation was noted, with 159/5488 intragenic CFP1 peaks colocalising with this stringently defined set of putative enhancers . These findings demonstrate the presence of CFP1 at enhancers and demonstrate that its association with enhancers is specific.Elevated CFP1 signal was observed at putative enhancers in both cell types, and heatmap evidence suggested qualitative association between CFP1 and signatures of open chromatin  as representative of SET1A complexes, Menin as a representative of MLL1/2 complexes and UTX as a representative of MLL3/4 complexes , Menin (n = 583) and UTX (n = 507) peak regions not colocalising with other TrxG complex subunits  were at TSSs. MLL2 is known to deposit H3K4me3 to establish bivalent domains [We next asked if genomic occupancy of CFP1-SET1A complexes was specialised relative to other TrxG complexes. Specifically, we hypothesised that CFP1-SET1A complexes could differ from other TrxG complexes in their localisation to genomic TSSs and putative enhancers defined earlier. Removing from consideration the small numbers of exclusive CFP1-SET1A . To test the sufficiency of these features to explain CFP1 binding, we computed the correlation of each feature with CFP1 individually  that CFP1 is also known to bind all methylation states of H3K4 through its PHD finger domain , 33; (2)Previous studies have demonstrated a key role for CFP1 in the differentiation of mouse ES cells , murine Several features have been found to be correlated with CFP1 binding to DNA or chromatin. Some of the earlier analyses pointed to the ZF-CXXC domain and its role in binding to CpG dinucleotides , 16, 43.Focusing on enhancers, we found specific occupancy of CFP1 at enhancers in both cell types together with positive correlation with chromatin accessibility. Moreover, enrichment of SET1A and its strong correlation with CFP1, including at enhancers, support the stabilisation of CFP1 at enhancers. SET1A is known to interact with CFP1 and immobilise CFP1 to DNA . Weaker In addition to the understanding of the mechanisms by which CFP1-containing complexes bind to open chromatin in steady state, an enduring question is how transcription is dynamically regulated in a cell type-specific manner. Early genome-wide studies showed monovalent H3K27me3 is a mark of PcG binding at TSSs and is associated with silencing, whereas monovalent H3K4me3 at TSSs is associated with high expression in mouse ES cells. However, TSSs of genes poised for expression are found in an intermediate bivalent (H3K27me3/H3K4me3) state, which arises as a result of targeted H3K4 methyltransferase activity –49. MutuIn differentiated cells, CFP1-SET1 complexes have been found by others to be responsible for most of the H3K4me3 deposition at CGI . In thatIn view of its known specificity for binding to unmethylated CpG dinucleotides, this study revealed an unexpected association of CFP1 with expressed TSSs, even in the absence of CGIs. Furthermore, CFP1 was associated with Pol II binding at expressed TSSs, regardless of CGI status, and this was observed in both cell types. Intriguingly, in addition to strong occupancy at TSSs, CFP1-SET1A complexes were also found at other accessible chromatin regions, including putative enhancers, which were highly enriched in weaker CFP1 peaks. Colocalisation of subunits of other TrxG complexes with CFP1-SET1A complexes was also observed in both TSSs and enhancers, though with differential preference, suggesting partial redundancy of TrxG complexes in agreement with the observations of others in pluripotent stem cells .Primary erythroid cells and newly generated EBV-infected B-lymphoblasts were obtained as previously described . Public 2O) was then added at a final concentration of 1% for 15 min at RT and samples were sonicated over 20 min (10 × 30-second episodes) at 4 °C to cleave genomic DNA . Input data sets were matched with ChIP-seq samples. Antibodies used are: H3K27me3 (07-449) (Millipore); HCF1 (A301-400A), RbBP5 (A300-109A), hSET1 , Menin (A300-105A), UTX (A302-374A) from Bethyl Labs and CFP1  from Abcam. The non-commercial CFP1 antibody was kindly provided by Prof. Robert Roeder. Real-Time PCR was performed using primers and probes (5’FAM-3’TAMRA) for the murine and human α-globin locus described previously [ChIP was performed as previously described . For CFPeviously , 58. EacNuclei from human primary erythroid cells were digested with increasing concentrations of DNaseI (Roche) as previously described . DNA , Pol II and H3K4me1 signals. First, normalised genome-wide signals for each ChIP were constructed by normalising each pileup to 1x genome coverage, and subtracting similarly normalised input data using the deepTools bamCompare program as described above. Genomic regions > 2 kb from gene TSSs exhibiting ATAC-seq signal value > 10 that also exhibited a Pol II signal value > 5 were accepted as putative enhancers and confirmed by plotting heatmaps of H3K4me1 and H3K27ac around these loci.https://ccb.jhu.edu/software/hisat2/index.shtml). The hisat2 aligner, version 2.0.5, was used with default parameters. Analysis of expression was performed in R: read counts for each locus were obtained in unpaired mode using the featureCounts function from the Rsubread package, and reads per kilobase of transcript per million mapped reads (RPKM) values were calculated using the rpkm function from the edgeR package.RNA-seq data from NCBI GEO  were aligned to a special purpose, splice-aware version of the GRCh38 human genome downloaded from the hisat2 web page (2(RPKM) < 1, and no tissue with absolute log2(RPKM/mean(RPKM)) > 2  were termed housekeeping genes. Genes for which either all expression RPKM ≤ 0.1 or for which more than half of the tissues had RPKM values ≤ 10% maximum were considered to be normally non-expressed. The maximal expression RPKM value of these candidate tissue-specific genes was compared to expression RPKM values (averaged across samples) from the analysis of erythroid and lymphoid cell types (above). If a gene was on the list of normally non-expressed genes and its RPKM expression value in erythroid or lymphoid tissue was at least half of this maximum, it was termed tissue-specific in that tissue.Housekeeping genes and candidate tissue-specific genes were identified from processed RNA-seq expression data (16 tissues) warehoused by the EBI Illumina body map resource (NCBI GEO accession GSE30611). Gene RPKM values were downloaded and thresholded at 0.1. A previously reported method  developeTo analyse which subunits of TrxG-related methyltransferase complexes colocalised, we compared six ChIP data sets in erythroid cells: CFP1 and SET1A, subunits of SET1A/B complexes; HCF1, a subunit of SET1A/B and MLL1/2 complexes; Menin, a subunit of MLL1/2 complexes; UTX, a subunit of MLL3/4 complexes; and RBBP5, a core subunit of all the complexes. A high-confidence set of peaks in each data set was defined as its most highly enriched tenth percentile, as detected by SPP. Bedtools was used to merge these regions into a non-redundant set of high-confidence peak regions. Subsequently peaks of all strengths detected by SPP were analysed for the presence or absence in these high-confidence regions.ChIP-enriched regions, identified as peaks by SPP, were analysed for motif enrichment using the homer program . For eacp < 10−20 were selected and further optimised by homer, with optimisation carried out separately for CGI and non-CGI peaks. Target sequences used for the optimisation step were combined peaks from ERY and EBV cell types, but with redundant peaks removed. The optimised motifs were clustered by homer and the most significant exemplar in each cluster was reported. The top ten exemplar motifs, five identified from CGI-associated CFP1 peaks and five from non-CGI peaks, were subsequently detected in CGI and non-CGI peaks, respectively. The purpose of this detection was to determine if a given motif, which had been optimised using sequences from both ERY and EBV cells, was biased for ERY or EBV cells; this might occur if the motif reflected genes expressed in that cell type rather than structural binding preference of CFP1.Motifs passing a detection threshold of We sought to understand the relationship between the intensity of ChIP and other signals, which might indicate functional interaction. CpG density and erythroid ChIP signals from CFP1, SET1A, HCF1, RBBP5, H3K4me3, H3K4me1, H3K27me3, DNase-seq and ATAC-seq were analysed, and ChIP signals were 1x-normalised and input was subtracted, as described above. Given that normalised and input-subtracted ChIP signals were noisy, each ChIP signal was averaged in a 2-kb region surrounding each TSS and putative enhancer to give a robust representation of the signal strength. The rare case where robust but non-overlapping ChIP-seq peaks are present at the same locus in different ChIP experiments, which would give a spurious apparent colocalisation, was ignored in this analysis. Relative chromatin accessibility was estimated from DNase-seq and ATAC-seq signals. Given that these signals give differing representations of chromatin accessibility, they were combined; first these signals were linearly scaled by the z-score transformation, and then they were averaged. The resulting chromatin accessibility score was therefore more robust and gave equal weight to DNase-seq and ATAC-seq data.R2) were performed between CFP1 and CpG density, SET1A, HCF1, RBBP5, H3K4me1, H3K4me3 and chromatin accessibility; this was done in all loci and in a subset of loci with upper decile chromatin accessibility scores. Features whose correlation R2 value was greater than 10% were identified. To test the sufficiency of these features to explain CFP1 occupancy in open chromatin, a linear regression analysis was performed, and this analysis was limited to the top-decile accessible regions.Tests of Pearson’s product moment correlation . (A-B) Analysis of CFP1 binding at the human α-globin locus in expressing and non-expressing cells. (A) Real-Time PCR analysis of immunoprecipitated chromatin using CFP1 antibody in human erythroblasts (red) and B-lymphocytes (blue). The y-axis represents enrichment over the input DNA, normalised to a control sequence in the human 18S gene. The x-axis represents the positions of Taqman probes used. The coding sequence is represented by the three exons  of the α-globin genes. 218 and hBact denote control sequences adjacent to the CpG islands of the human LUC7L (218) and ACTB promoters. Error bars correspond to ± 1 SD from at least two independent ChIPs. (B) Real-Time PCR analysis of immunoprecipitated chromatin using the CFP1 antibody indicated in humanised erythroblasts  and mutant, MCS-R2 (right). The y-axis represents enrichment over the input DNA, normalised to a control sequence in the mouse GAPDH gene. CpG Act denotes additional control sequence at the CGI of the mouse ACTB gene. The amplicons highlighted in red represent deleted regions in the humanised mice, for which no PCR signal is observed. Error bars correspond to ± 1 SD from at least two independent ChIPs. (C) CFP1 ChIP signal intensity in the top 200 peaks, by antibody and by cell type. Abcam, ab56035 antibody. Roeder, main antibody used in this study. (D) Analysis of CGI (green) and non-CGI (blue) transcription start sites . Gene symbols shown with CpG content of individual loci in parentheses. Greek letters represent individual globin genes. Fig. S2: Peak overlaps of CFP1 and marks of active and repressed chromatin in transcription start sites (TSSs). Peaks were detected by MACS2. Venn diagrams show that CFP1 peaks within 1-kb of TSSs are strongly associated with H3K4me3 histone mark and poorly associated with H3K27me3 repressive histone mark. Cell types are (A) ERY and (B) EBV. Public data sets: * NCBI GEO GSE36985, ** NCBI GEO GSE50893. Fig. S3: UCSC tracks showing CFP1 and other ChIP signals in gene loci in erythroblasts (ERY) and EBV-transformed B-lymphoblasts (EBV). Hg38 coordinates for multiple genes, CpG islands , and putative regulatory regions (blue boxes) are shown. CFP1 signals are shown in dark reds, inputs in grey, histone H3 signals in blues and open chromatin marks in greens. All ChIP pileups are scaled to 1x coverage genome-wide and shown in a range 0–50, except CFP1 (Roeder) is shown with extended range and H3K27me3 graphs scaled by 2x. (A) Tissue-specific binding of CFP1 to CGI promoters of tissue-specifically expressed genes. Left (chr16), CGI promoters of active genes in alpha globin locus are CFP1-bound in ERY, and unbound in EBV. Flanking regions are included, with known tissue-specific enhancers. Right (chr6), first seven exons of IRF4 locus, active in EBV and inactive in ERY, with CFP1 binding to CGI promoter in EBV only. (B) CGI promoters of housekeeping genes are CFP1 bound and unmarked by H3K27me3. Left (chr7), ACTB locus. Right (chr16), LUC7L locus. (C) CGI promoter of RHBDF1 locus (chr16) has H3K27me3 mark and the absence of CFP1 binding in both ERY and EBV. Fig. S4: Western blot analysis of CGBP (CFP1) expression in mouse and human erythroid and human lymphoid cell types. Whole cell extracts (20 µg) were loaded in each lane (1) mouse ES, (2) U-MEL, (3) I-MEL, (4) mouse primary erythroblasts and (5) human primary T lymphocytes and (6) human primary erythroblasts and separated on a 10% SDS-polyacrylamide gel. CFP1 antibody was used at a 1:1000 dilution. Fig. S5: Similar cell type-specific CFP1 read depth at CGI TSS of HBA1 gene and non-CGI TSS of HBB gene. Upper two tracks use the main antibody, and second two tracks use the commercial antibody. Coordinates are from the hg38 human genome build. Read depths are averaged in 50 bp bins and normalised to 1x genome-wide coverage. Blue boxes, known regulatory regions; green box, CGI. Fig. S6: Distribution of TrxG components in erythroid cells. Green indicates CGI and blue indicates other putative regulatory regions. All loci transcribed right to left. Pileups are shown scaled to 1x genome coverage, with full scale 0–50x depth. (A) Housekeeping genes ACTB, left (chr7), and LUC7L, right (chr16). (B) β-globin locus (chr11), (C) Non-expressed RHBDF1 locus (chr16). Fig. S7: Overlap of TrxG subunit ChIP peaks in a high-confidence subset of regions. SET1A complexes are represented by CFP1-SET1A colocalisation. MLL1/2 complexes are represented by Menin, and MLL3/4 complexes are represented by UTX, respectively. HCF1 is found in SET1A/B and MLL1/2 complexes, and RBBP5 is a member of SET1A/B and MLL1/2/3/4 complexes. Red outline (4220 peaks) shows strong colocalisation of Menin and CFP1-SET1A, accounting for the vast majority (99.5%) of 4242 CFP1-SET1A and half (50.0%) of 8432 Menin peak regions. Majority  of HCF1 (blue region) is accounted for by approximately half  of regions of Menin-SET1A-CFP1 colocalisation. Regions where either SET1A-CFP1 or Menin or both are colocalised with HCF1 (blue dashed line) accounts for nearly all  HCF1 regions, suggesting that HCF1 bound to DNA is primarily present as part of SET1A/B or MLL1/2 complexes. Fig. S8: Chromatin accessibility in TSSs and enhancers in erythroid cells as measured by ATAC-seq and DNase-seq. 1x-normalised, input-subtracted signals from ATAC-seq and DNase were averaged in a 2-kb window about TSSs and putative enhancers. Z-score transformed values for ATAC-seq and DNase-seq at a given locus were averaged. Fig. S9: Relationship of CFP1 signal to three predictive factors in top-decile open chromatin regions. A linear combination of CpG density and SET1A and H3K4me3 ChIP signals explains a substantial fraction of variation in CFP1 ChIP signal. Table S1: Bias of CFP1 for CGI TSSs in cell types and gene classes. Table S2: Bias of CFP1 for housekeeping gene TSSs. Table S3: Motifs associated with CFP1 peaks. Table S4: Dependence of CFP1 ChIP signal in erythroid cells on covariates putatively associated with its binding. Table S5: Analysis of variance of CFP1 signal in top-decile open chromatin regions surrounding TSSs and putative enhancers.


The complex life cycle of oncogenic human papillomavirus (HPV) initiates in undifferentiated basal epithelial keratinocytes where expression of the E6 and E7 oncogenes is restricted. Upon epithelial differentiation, E6/E7 transcription is increased through unknown mechanisms to drive cellular proliferation required to support virus replication. We report that the chromatin-organising CCCTC-binding factor (CTCF) promotes the formation of a chromatin loop in the HPV genome that epigenetically represses viral enhancer activity controlling E6/E7 expression. CTCF-dependent looping is dependent on the expression of the CTCF-associated Yin Yang 1 (YY1) transcription factor and polycomb repressor complex (PRC) recruitment, resulting in trimethylation of histone H3 at lysine 27. We show that viral oncogene up-regulation during cellular differentiation results from YY1 down-regulation, disruption of viral genome looping, and a loss of epigenetic repression of viral enhancer activity. Our data therefore reveal a key role for CTCF-YY1–dependent looping in the HPV life cycle and identify a regulatory mechanism that could be disrupted in HPV carcinogenesis. Oncogenic human papillomavirus (HPV) infection causes cancers of the anogenital and oropharyngeal tracts. HPV infects undifferentiated basal cells of the epithelium at these body sites and expresses low levels of viral early genes, required for replication of the viral genome. In normal epithelia, cellular migration away from the basal layer induces cell cycle exit and differentiation. However, in an HPV-infected cell, differentiation induces increased transcription of the viral early genes to prevent cell cycle exit, supporting amplification of the viral DNA. In this study, we show that the HPV genome recruits the cellular transcriptional regulators CTCF and YY1, which coordinate an epigenetically repressed chromatin loop between the YY1-bound viral transcriptional enhancer and CTCF-bound early gene region to attenuate early gene expression in undifferentiated cells. As the cells differentiate, YY1 protein expression and recruitment to the viral genome is dramatically reduced. This results in a loss of chromatin loop formation, epigenetic de-repression of the viral genome, and enhanced viral early gene expression. The coordination of viral gene expression with cellular differentiation is vital for persistence of infection and completion of the virus life cycle, and disruption of HPV transcriptional control is also a key step in the development of cancer. Human papillomaviruses (HPVs) are a family of small, double-stranded DNA viruses that infect epithelia at specific anatomical sites. Infection with any of the 12 mucosal oncogenic HPV types is a risk factor for the development of epithelial cancers such as cancer of the uterine cervix and oropharynx [105 in HPV18 [105 is controlled by enhancer and silencer sequences upstream of the promoter in the 850 basepair (bp) viral long control region (LCR). P105 contains a canonical TATA box, essential for the recruitment of the general transcription factor II D (TFIID) and the initiation of RNA polymerase II (RNA Pol II)-dependent transcription [The HPV life cycle is dependent on the differentiation of infected keratinocytes. Infection is established in the undifferentiated basal cells of epithelia, allowing the virus access to the cellular DNA replication machinery required to replicate viral episomes. To maintain the cell in a proliferative state, the viral E6 and E7 oncoproteins work synergistically to delay differentiation and prevent cell cycle exit. These essential viral proteins are encoded by transcripts that initiate from a short promoter situated immediately upstream of the early transcription start site, termed Pin HPV18 . The actcription . Proximacription –6. Situacription , and YY1The episomal papillomavirus genome associates with histones to form nucleosomes that are subject to epigenetic modification through the specific recruitment of cellular transcription factors that regulate viral transcription . In HPV3It is clear that epigenetic regulation of HPV transcription plays an important role in the HPV life cycle and in enhanced viral oncogene expression during disease progression ,12; howeThe mechanism by which CTCF regulates HPV oncogene expression is not known. In this study, we identify CTCF- and YY1-dependent loop formation in the HPV18 genome as the mechanism through which viral oncogene expression is restricted in the early stages of infection in undifferentiated keratinocytes. We show that down-regulation of YY1 following differentiation results in loss of loop formation and reversal of epigenetic silencing and facilitates increased oncogene expression and completion of the viral life cycle.To analyse the function of CTCF in the life cycle of HPV18, primary human keratinocytes, the natural host cell of HPV, were transfected with religated HPV18 genomes, and replicating episomes were established that were stably maintained at approximately 50 copies per cell. We previously showed that mutation of the CTCF binding site within the E2 ORF of HPV18 (HPV18 ΔCTCF) results in a marked reduction of CTCF binding at this site with no effect on the establishment of HPV18 episomes in primary keratinocytes . HoweverTo determine whether HPV18 genome establishment alters CTCF protein expression, we quantified CTCF protein in isogenic primary HFKs. We observed a >2.5-fold increase in CTCF protein expression following establishment of HPV18 episomes . This waTo determine whether abrogation of CTCF binding at the E2 ORF affects CTCF recruitment elsewhere in the viral episome, we performed chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR) to specifically amplify CTCF-bound regions throughout the HPV18 genome . CTCF biWe previously concluded that CTCF recruitment is important in the regulation of HPV18 oncogene expression in differentiated epithelia . Consistp < 0.001). This increased chromatin accessibility was consistent between independent donor lines and suggests a mechanism by which CTCF binding at the distal E2 binding site influences nucleosome occupancy within the viral LCR.Our data show that recruitment of CTCF within the E2 ORF represses HPV18 early gene expression, and we hypothesised that this was due to repression of early promoter activity. Regulatory genomic elements are depleted of nucleosomes, and the remaining nucleosomes are enriched in active chromatin marks  . Formald811. These findings are in agreement with previous DNase I footprinting experiments that demonstrated dynamic nucleosome binding in the viral enhancer and tightly held nucleosomes at the viral late promoter [Interestingly, we observed that immediately downstream of the open chromatin area in the HPV18 WT genome is a region of closed chromatin in the E6 and E7 ORFs and the late promoter, PWe next investigated whether the increased accessibility of chromatin within the viral LCR following disruption of CTCF binding was associated with any change in active and repressive epigenetic marks. Using ChIP-qPCR, we analysed levels of the active-promoter–associated H3K4Me3 mark and the polycomb repressor complex (PRC)-associated repressive H3K27Me3 mark across the HPV18 genome. These experiments revealed an enrichment of H3K4Me3 in HPV18 ΔCTCF genomes compared to WT, particularly within the viral enhancer and immediately downstream of the early promoter, indicative of active transcription . In contSince H3K27Me3 has been shown to inhibit recruitment of the general transcription machinery, we examined RNA Pol II recruitment. Indeed, enrichment of RNA Pol II was observed at the early promoter and within the early gene region in HPV18 ΔCTCF compared to WT, consistent with increased transcription levels .Numerous host-cell transcriptional regulators have been shown to specifically bind to the HPV LCR and regulate transcription of viral early genes. To determine whether CTCF influences recruitment of specific cellular regulators of HPV18 transcription, we analysed enrichment of transcription factors that regulate early gene transcription using ChIP-PCR. Our analysis revealed that mutation of the CTCF binding site resulted in significantly reduced binding of the YY1 transcription factor at both the 5′ and 3′ enhancers in the viral LCR and at the early and late promoter regions . Since YNlaIII restriction enzyme, which restricts the viral DNA at multiple sites . However, a significant reduction of YY1 protein expression was observed in both HPV18 WT- and ΔCTCF-genome–containing cultures , which we predict would enhance CTCF binding [p = 0.050, one-tailed Fisher’s test). We therefore speculate that in lesions that contain this variant of HPV16, CTCF may bind with higher affinity and have a more significant effect on the attenuation of E6/E7 expression, thereby reducing the risk of cancer development. In addition to genetic variations within the CTCF binding site, we also found many sequences that had no sequence information at and around the E2 ORF CTCF binding site. This could be due to integration of the virus such that the E2 coding sequence is disrupted, but in addition to this widely reported mechanism of HPV-driven carcinogenesis, it will be important to determine the mechanism and consequence of CTCF exclusion in cancers with integrated HPV DNA.Whether this mechanism of differentiation-dependent regulation of HPV oncogene expression plays a role in HPV-driven cancer is not clear, but it is tempting to speculate that this is the case. YY1 binding sites are often mutated in the HPV16 genome in cervical cancer ,52, and  binding . InteresThe collection of circumcised foreskin tissue from newborns for the isolation of primary HFKs for investigation of HPV biology was approved by Southampton and South West Hampshire Research Ethics Committee A (REC Reference number 06/Q1702/45). Written consent was obtained from the parent or guardian. The study was approved by the University of Birmingham Ethical Review process (ERN_16–0540).EcoRI site of pGEMII and was used to create pGEMII-HPV18-ΔCTCF, which contains three conservative nucleotide substitutions  within the E2 coding region to abolish CTCF binding as previously described [pGEMII-HPV18  contains the complete HPV18 genome cloned into the escribed .CTCF (61311), H3K4Me3 (39915), H3K27Me3 (39155), RNA Pol II (61081), SP1 (39058), TEF1 (61644), EZH2 (39901), EED (61203), and Ring1B (39663) and antibodies were purchased from Active Motif . YY1 antibody (SC-7341X) was purchased from Santa Cruz Biotechnology . H2AK119Ub (D27C4) was purchased from Cell Signaling Technology, Inc . FLAG M2 was purchased from Sigma-Aldrich , E7 clone 8E2 (ab100953) was purchased from Abcam , and E6 clone G7 (SC-365089) and Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) antibody were purchased from Santa Cruz Biotechnology . Monoclonal HPV18 E1^E4 antibody 1D11 was produced by S. Roberts . All horEcoRI results in linearisation of episomes, whereas digestion with BglII restricts the host cell DNA but not the viral DNA to reveal integrated or multimeric virus. DpnI digests input DNA only.The transfection of normal primary HFKs from neonatal foreskin epithelia with recircularised HPV18 WT and ΔCTCF genomes was performed in S. Roberts’ laboratory by J. Parish as previously described ,57. To eOrganotypic raft cultures were prepared as previously described ,57,58 an6 cells) were suspended in E medium containing 10% FBS and 1.5% methylcellulose and incubated at 37°C, 5% CO2 for 48 h. Cells were then harvested by centrifugation at 250 × g and then thoroughly washed with ice-cold PBS. Cells were then either resuspended in medium containing 1% formaldehyde to cross-link for ChIP and 3C or in urea lysis buffer for protein extraction.HPV18-genome–containing keratinocytes (3 × 10T) values were calculated at a constant threshold for each experiment, and fold-enrichment–compared to negative control FLAG antibody was calculated using the following formula:ChIP assays were carried out using the ChIP-IT Express kit (Active Motif) following the manufacturer’s instructions. Briefly, cells were fixed in 1% formaldehyde for 3 min at room temperature, quenched in 0.25 M glycine, and washed in ice-cold PBS. Nuclei were released by 40 strokes in a tight dounce homogeniser. Samples were sonicated at 25% amplitude for 30 s on/30 s off for a total of 15 min using a Sonics Vibracell sonicator fitted with a microprobe. ChIP efficiency was assessed by quantitative PCR (qPCR) using SensiMix SYBR master mix using an MXPro 3000 . Primer sequences for ChIP experiments are shown in ΔCT target)/(2ΔCT IgG),Fold binding over IgG =  and protein concentration determined by Bradford assay. Equal amounts of protein were separated by SDS-PAGE and western blotting carried out using conventional methods.RNA was extracted with an RNeasy Mini Kit  according to the manufacturer’s protocol and DNase treated. For RNA-Seq, libraries were prepared using TruSeq Stranded mRNA Library Prep kit for NeoPrep  using 100 ng total RNA input according to manufacturer’s instructions. Libraries were pooled and run as 75-cycle–pair end reads on a NextSeq 550 (Illumina) using a high-output flow cell.cDNA was synthesised using Superscript III  according to the manufacturer’s instructions. qPCR was performed using a Stratagene Mx3005P detection system with SyBr Green incorporation and the primers listed in 6 cells, one for Input and one for FAIRE. To the FAIRE samples, 150 μl water was added. To the Input sample, 150 μl water and 10 μl of 5 M NaCl were added, and the samples were incubated at 95°C for 15 min to reverse the crosslinks. RNaseA (10 μg/μl) was added, and the samples incubated at 37°C for 15 min. Proteinase K (0.5 μg/μl) was added followed by incubation at 67°C for 15 min.Cells were fixed and chromatin extracted and sheared as described above for ChIP. FAIRE analysis was then carried out as previously described . BrieflyT method. Primer sequences are shown in Both Input and FAIRE samples were then extracted with 200 μl phenol:chloroform:isoamylalcohol (25:24:1) and the aqueous layer retained. DNA was precipitated by conventional methods and the pellet resuspended in 50–150 μl 50 mM Tris-HCl, pH 7.4, 10 mM EDTA. Recovery of FAIRE-extracted DNA in comparison to Input DNA was then determined by qPCR using the ΔΔC7 cells were trypsinised and resuspended in 1 ml 10% (v/v) FCS/PBS. Cells were passed through a 70 μm cell strainer and 9.5 ml of 1% formaldehyde in 10% FCS/PBS added before incubation for 10 min at RT with end-to-end rotation. Glycine was added to a final concentration of 125 μM before the cells were pelleted at 4°C. Cells were resuspended in 5 ml of ice cold lysis buffer  and incubated on ice for 10 min. Samples were centrifuged at 400 × g for 5 min at 4°C to pellet the nuclei. Five hundred μl 1.2× restriction enzyme buffer and 0.3%  SDS were added and samples incubated at 37°C for 1 hr while shaking at 900 rpm. Fifty μl of 20% Triton X-100 was then added, followed by incubation at 37°C for 1 hr with shaking at 900 rpm. Prior to digestion, an aliquot was removed for assessment of digestion efficiency. Four hundred units of NlaIII restriction enzyme were added, and the samples were incubated at 37°C overnight with shaking at 900 rpm. An aliquot of each sample was removed and assessment of digestion efficiency performed by adding 500 μl of 5 mM EDTA, pH 8.0, 10 mM Tris-HCl, pH 8.0, 0.5% SDS, and 20 μg proteinase K and incubating at 65°C for 30 min. One μg RNase A was added, followed by incubation at 37°C for 2 hr. The DNA was extracted with PCI and ethanol precipitated using conventional methods and the pellet resuspended in 60 μl dH20. Digestion efficiency of the viral genomes was assessed by qPCR of genome regions sensitive and insensitive to containing NlaIII restriction sites  Triton X-100 was added. Samples were incubated for 1 hr at 37°C with gentle shaking. One hundred units of T4 DNA ligase were added and the samples incubated for 4 hr at 16°C, followed by 30 min at RT. Three hundred μg proteinase K was added, and the samples were incubated at 65°C overnight.To purify the digested DNA, 300 μg RNase A was added and the samples incubated for 45 min at 37°C. The DNA was extracted with PCI twice and ethanol precipitated. Finally, the DNA pellet was resuspended in 10 mM Tris-HCl, pH 7.5. Ligation of specific regions of the HPV18 genome was assessed by PCR using sense primers specific to the L1 and E2 ORFs to detect interactions between the CTCF-bound E2 ORF and the viral LCR and sense primers specific for the L2 and E2 ORFs to detect ligation events that could occur by chance . PCR prog for 90 min to facilitate infection, after which media were replaced with E medium. Twenty-four hr later, lentiviral infection was repeated as described above before cells were detached and seeded onto fresh irradiated feeder cells in 10 cm dishes. Puromycin to a final concentration of 1 μg/ml was added to the cells 72 hr later to select infected cells. shRNA expression was induced with 1 μg/ml doxycycline for 48 hr.Human embryonic kidney 293T (HEK293T) cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% FBS and transfected with second-generation lentiviral packaging plasmids, psPAX2 and pMD2.G, and pTRIPZ-shRNA expressing plasmid using polyethylenimine (PEI) Max at a DNA-to-reagent ratio of 1:3. Medium containing lentiviral particles was recovered at 48 and 72 hr post transfection and passed through a 0.45 μM filter. The resulting recombinant lentiviruses were concentrated using Vivaspin ultrafiltration spin columns  and used to spin infect HPV18-genome–containing keratinocytes growing in 6-well plates in E medium containing 8 μg/ml polybrene after feeders had been removed. Plates were spun at 3,220 × S1 Table*Calculated compared to untransfected isogenic donor. CTCF, CCCTC-binding factor; RNA-Seq, RNA-Sequencing.(DOCX)Click here for additional data file.S2 Table*ΔCTCF HPV18 gene expression compared to WT HPV18. CTCF, CCCTC-binding factor; HPV, human papillomavirus; ORF, open reading frame; RNA-Seq, RNA-Sequencing.(DOCX)Click here for additional data file.S1 FigNlaIII digestions site (green), and CTCF binding site (blue). CTCF, CCCTC-binding factor; LCR, long control region; ORF, open reading frame; 3C, chromosome conformation capture.Showing 3C forward and reverse primer sites (red), (DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.


Termination of RNA polymerase II (RNAPII) transcription is a fundamental step of gene expression that is critical for determining the borders between genes. In budding yeast, termination at protein-coding genes is initiated by the cleavage/polyadenylation machinery, whereas termination of most noncoding RNA (ncRNA) genes occurs via the Nrd1–Nab3–Sen1 (NNS) pathway. Here, we find that NNS-like transcription termination is not conserved in fission yeast. Rather, genome-wide analyses show global recruitment of mRNA 3′ end processing factors at the end of ncRNA genes, including snoRNAs and snRNAs, and that this recruitment coincides with high levels of Ser2 and Tyr1 phosphorylation on the RNAPII C-terminal domain. We also find that termination of mRNA and ncRNA transcription requires the conserved Ysh1/CPSF-73 and Dhp1/XRN2 nucleases, supporting widespread cleavage-dependent transcription termination in fission yeast. Our findings thus reveal that a common mode of transcription termination can produce functionally and structurally distinct types of polyadenylated and non-polyadenylated RNAs. Termination of RNA polymerase II (RNAPII) transcription is an essential step of gene expression. Here the authors provide evidence that in fission yeast termination of ncRNA genes occurs by a cleavage-dependent mechanism involving recruitment of mRNA 3′ end processing factors and requires the conserved Ysh1/CPSF-73 and Dhp1/XRN2 nucleases. Although transcription termination has been investigated in a wide range of organisms, it has been most extensively studied in the model organism Saccharomyces cerevisiae, where two major termination pathways exist depending on the class of genes transcribed2. For protein-coding genes, data support a mechanism triggered by the cleavage activity of the Ysh1 endonuclease (CPSF-73 in humans), which is part of a nuclease module within the larger mRNA 3′ end processing complex3. Specifically, the co-transcriptional recruitment of conserved cleavage and polyadenylation factors at poly(A) signal (PAS) causes cleavage of the nascent pre-mRNA, followed by 3′ end polyadenylation of the released transcript by the poly(A) polymerase4. This cleavage also provides a free and uncapped 5′ entry point for a protein complex that includes an evolutionarily conserved 5′–3′ exonuclease . The exonuclease is thought to chase RNAPII and promote its dissociation from the DNA template8, a mechanism referred as “torpedo”-mediated transcription termination.RNA polymerase II (RNAPII) is responsible for the synthesis of a broad range of coding and noncoding transcripts, and termination pathways have a decisive influence on the fate of transcribed RNAsS. cerevisiae, transcription of snoRNAs, snRNAs, and CUTs does not rely on the cleavage/polyadenylation machinery for termination, but instead uses a cleavage-independent termination pathway that requires a complex (referred to as NNS complex) consisting of the RNA-binding proteins Nab3 and Nrd1 as well as the DNA/RNA helicase Sen12. In this mode of termination, the NNS complex interacts with both the transcription machinery10 and specific RNA motifs enriched downstream of ncRNA genes12 to engage the transcription elongation complex via the Sen1 helicase, which translocate onto the nascent RNA and catches up with the transcribing polymerase to elicit termination13.In addition to mRNAs, RNAPII synthesizes an extensive set of noncoding RNAs (ncRNAs) that include small nucleolar RNAs (snoRNAs), small nuclear RNAs (snRNAs), long noncoding RNAs (lncRNAs), and cryptic unstable transcripts (CUTs). In 14. The RNAPII CTD is subjected to a plethora of post-translational modifications throughout the transcription cycle that are key to coordinate the sequential recruitment of RNA-processing factors. Among CTD modifications, phosphorylation of Ser2 and Ser5 have been most extensively studied and appear to be the most abundant in S. cerevisiae15. In the cases of small ncRNA genes, NNS recruitment is influenced by Ser5 phosphorylation (Ser5-P) via the CTD interaction domain (CID) of Nrd110. As transcription elongation progresses into protein-coding genes, the ratio between the levels of phosphorylated Ser2 (Ser2-P) and Ser5-P gradually increases, peaking near the mRNA cleavage site17. Pcf11, a component of the mRNA 3′ end processing machinery, preferentially recognizes Ser2-P CTD repeats via its CID domain19, which may explain the robust levels of Pcf11 at the 3′ end of protein-coding genes20. Yet, Pcf11 recruitment at the 3′ end of mRNA genes may also be influenced by additional CTD modifications. For instance, Tyr1 phosphorylation (Tyr1-P) can impair binding of Pcf11 to Ser2-P CTD peptides in vitro20. Accordingly, it was proposed that Tyr1-P prevents recruitment of termination factors in the coding region of genes in S. cerevisiae, and that timely dephosphorylation of Tyr1-P upstream of the polyadenylation site by the Glc7 phosphatase would allow for recruitment of the 3′ end processing machinery via recognition of Ser2-P CTD repeats by the CID domain of Pcf1121.One transcription-associated feature that appears to influence the choice between torpedo- and NNS-mediated termination is the phosphorylation status of the carboxy-terminal domain (CTD) of the RNAPII catalytic subunit, Rpb1. The CTD consists of a succession of conserved heptad repeats, with the consensus amino acid sequence Y-S-P-T-S-P-S23. Yet, how RNAPII transcription is terminated at ncRNA genes remains poorly understood for many eukaryotic species. Also unclear is whether the use of distinct pathways to terminate coding and noncoding transcription, such as described in S. cerevisiae, is evolutionarily conserved. Recently, we have shown that the S. pombe homolog of S. cerevisiae Nrd1, Seb1, does not physically associate with Nab3 and Sen1 homologs in fission yeast24. Here we show that the absence of Nab3 and Sen1 homologs in S. pombe does not affect transcription termination of coding and ncRNA genes. Unexpectedly, we find that mRNA 3′ end processing factors are enriched at the 3′ end of ncRNA genes and that this recruitment coincides with high levels of Ser2 and Tyr1 CTD phosphorylation. Consistently, we find that most independently transcribed fission yeast snoRNA genes are cleaved and polyadenylated in a manner dependent on conserved 3′ end processing factors, and that termination at ncRNA genes is sensitive to deficiencies in Ysh1 and Dhp1. Our findings indicate that torpedo-mediated transcription termination is widespread in fission yeast, thereby revealing that a universal mode of transcription termination can promote the synthesis and accumulation of both polyadenylated mRNAs and non-polyadenylated ncRNAs.High-throughput sequencing analyses indicate that the majority of genomes are transcriptionally active, thus yielding a large amount of ncRNAsS. pombe, we analyzed genome-wide RNAPII (Rpb1) occupancy by ChIP-seq using nab3Δ, sen1Δ, and dbl8Δ  single mutants as well as a sen1Δ dbl8Δ double mutant. The absence of Nab3, Sen1, and Dbl8 did not result in noticeable read-through transcription at mRNA and snoRNA genes compared to the wild-type (WT) control. In contrast, a deficiency in the essential protein Seb1 results in defective termination at most RNAPII-transcribed genes -binding protein Pab2, the homolog of human PABPN126. We previously uncovered a polyadenylation-dependent pathway required for the maturation of independently transcribed snoRNAs that relies on Pab228. To test for the possibility that mRNA cleavage and polyadenylation factors function in 3′ end processing of ncRNA genes in S. pombe, we used ChIP-seq to examine the genome-wide-binding profile of proteins with conserved roles in mRNA 3′ end processing and transcription termination. This analysis included two independent components of the cleavage and polyadenylation factor I (CFI) complex, namely Rna14 and Pcf11, the endonuclease Ysh1 that is responsible for pre-mRNA cleavage before 3′ end polyadenylation, and Dhp1, the homolog of S. cerevisiae Rat1 and human XRN2 that promote transcription termination of RNAPII via 5′–3′ exonucleolytic activity. The ChIP-seq profile of Seb124 was also included, as this protein was shown to be important for 3′ end processing of both mRNAs and ncRNAs. Consistent with roles in 3′ end processing at mRNA genes, Rna14, Pcf11, Ysh1, Seb1, and Dhp1 all showed strong binding at the 3′ end of protein-coding genes . Importantly, levels of Seb1, Pcf11, and Dhp1 expressed from the nmt promoter were similar to levels expressed from their endogenous promoter in non-repressing conditions, but showed robust depletion in thiamine-supplemented conditions when expressed under the nmt promoter  were obtained from wild-type S. pombe cells grown in rich and minimal media by 3′READS34. Although the majority (~60%) of unique PAS reads mapped to 3′ UTR of protein-coding genes, roughly 18% of unique PAS locations mapped to intergenic regions. Notably, out of 31 independently transcribed monocistronic snoRNAs, 24 (77%) and 27 (87%) had a mappable poly(A) site located downstream of a snoRNA annotation in minimal and rich media, respectively , the two different PASs identified in the WT, pab2Δ, and Pnmt-seb1 strains were used in cells deficient for Pcf11 , an approach developed to map mRNA polyadenylation sites at the genome-wide levelPAS Fig. . Notablyf11 Fig. . Collectf11 Fig. .Fig. 3In28  snoRNA 3′ end and the pre-snoRNA cleavage site is 77-nt in wild-type cells grown in rich medium  signals around S. pombe mRNAs are associated with upstream AAU[A/G]AA hexamers and downstream GUA motifs36. However, the relatively small number of independently transcribed snoRNAs (n = 31), as compared to mRNAs (n = 4755), limited the identification of significantly enriched sequence motifs around snoRNA poly(A) sites. We therefore tested whether cis elements promoting mRNA 3′ end processing could support 3′ end maturation of a snoRNA. For this, we generated constructs in which 1-kb of snR99 downstream sequence was exchanged with 1-kb of downstream sequence from rps2 and trx1 protein-coding genes . Furthermore, RNase H cleavage assays and 3′ RACE experiments revealed Pab2-dependent polyadenylated snoRNA precursors that used the natural rps2 and trx1 cleavage sites  site20. Occupancy profiles of CTD phosphorylation marks at snoRNA genes showed a pattern somewhat similar to that of mRNA genes, with peaking Ser5-P and Ser7-P signals at the 5′ end that started decreasing in the snoRNA gene body  that preferentially recognize Ser2-phosphorylated RNAPII in vitroene Fig. , the peaene Fig. . GloballS. pombe). To address whether termination of snoRNA transcription in S. pombe was generally dependent on Dhp1, we analyzed RNAPII occupancy in Dhp1-depleted cells. Because deficiencies in Rat1 and XRN2 have been shown to affect RNAPII occupancy37, we introduced a spike-in normalization step38 using a constant amount of S. cerevisiae chromatin to directly compare ChIP-seq samples between wild-type and Dhp1-depleted cells (see Methods for details). The distribution of total RNAPII (Rpb1) displayed increased density at the 3′ end of the fba1 mRNA and the snR99 snoRNA in Dhp1-deficient cells , consistent with read-through transcription. Evidence of delayed transcription termination in the dhp1 mutant was also noted at snRNA genes, as indicated by a shift of Rpb1 density into the 3′ flanking region of U5 and U1 snRNAs  are thus consistent with the detection of long read-through transcripts  complex, Ysh1 (CPSF-73 in humans), is required for transcription termination of ncRNA genes in fission yeast, we analyzed RNAPII density in cells where Ysh1 was depleted from the nucleus using an anchor-away strategy. As expected, inactivation of Ysh1 resulted in a clear read-through phenotype at a protein-coding gene Fig. . Globalllls Fig. . Importaene Fig. , causingene Fig. . pcf11 apts Fig. , which aant Fig. , lane 8 nes Fig. , the nucnes Fig. .Fig. 6Thysh1 alleles expressing single amino acid substitutions at conserved histidine residues that were shown to contact critical zinc atoms in the active site of human CPSF-7339. We used a “complementation after nuclear depletion” approach40 by chromosomal integration of the different ysh1 alleles into the ysh1 anchor-away strain and confirmed that the corresponding proteins were expressed  contribute a substantial and diverse portion of noncoding transcriptomes. In 532 Fig.  and SPNC491 Fig.  lncRNA g532 Fig.  and SPNC491 Fig.  in cells491 Fig. , consistam1 Fig. , which rS. cerevisiae, whether NNS-like transcription termination is conserved across eukaryotic species was unclear. Despite the presence of homologs for all of the NNS components, our results indicate that NNS-mediated termination is not conserved in the distantly related yeast S. pombe. In the absence of an NNS-like complex, our findings reveal that a universal cleavage-dependent mechanism that involves the conserved Dhp1 5′–3′ torpedo nuclease is used to terminate transcription of both mRNA and ncRNA genes.Despite extensive characterization of how the NNS complex promotes termination at ncRNA genes in 44. Second, transcription termination defects were not detected in nab3Δ, sen1Δ, dbl8Δ, and sen1Δ dbl8Δ mutants. These data suggest that while NNS components have been conserved between budding and fission yeasts, they have acquired species-specific functions. For instance, S. pombe Seb1 recognizes Ser2-phosphorylated RNAPII and is recruited to the 3′ end of both mRNA and ncRNA genes25. In contrast, S. cerevisiae Nrd1 preferentially binds to Ser5-phosphorylated RNAPII and is enriched at noncoding transcription units2. Also consistent with the idea that NNS components have functionally diverged between the evolution of budding and fission yeasts from a common ancestor, Sen1 is primarily associated with RNA polymerase III (RNAPIII)-transcribed genes in S. pombe44. An NNS-like transcription termination pathway is also unlikely to exist in metazoans, as clear homologs or functional analogs of Nrd1 and Nab3 components have not been described. Conversely, a homolog for the yeast Sen1 helicase has been characterized in humans , and a role for SETX in promoting efficient transcription termination at model protein-coding genes has been described46. However, how SETX globally contributes to transcription termination of mRNA genes remains to be demonstrated, as data presented here as well as in S. cerevisiae47 indicate that yeast Sen1 is not required for efficient transcription termination at protein-coding genes.Two key indications support the absence of an NNS-like transcription termination pathway in fission yeast. First, Seb1 (Nrd1 homolog), Nab3, Sen1, and Dbl8 do not to form a stable complex in fission yeastcis-sequences of protein-coding genes can promote snoRNA 3′ end maturation and accumulation; and (v) transcription termination at ncRNA genes requires endonucleolytic cleavage and the torpedo nuclease Dhp1. These data support a model in which cleavage and polyadenylation are essential steps for 3′ end processing and transcription termination at both mRNA and snoRNA genes. Although it has been shown that particular components of the mRNA 3′ end processing machinery, such as Pcf11, Rat1, and Glc7, are recruited to short ncRNA genes in S. cerevisiae50, these factors appear to function either separately from the CPF complex to contribute to NNS-dependent termination or as a failsafe mechanism of transcription termination. This contrasts our findings in fission yeast, where the prevailing mechanism of transcription termination at ncRNA genes involves the cleavage and polyadenylation complex. Given the unexpected similarity of cleavage-dependent transcription termination at mRNA and snoRNA genes, it will be interesting to understand the mechanism used to distinguish between mRNAs and snoRNAs; whereas the mature mRNA needs to retain its poly(A) tail, the polyadenylated 3′-extended pre-snoRNA is targeted by Pab2-dependent exosome-mediated 3′ end trimming to yield a mature non-polyadenylated snoRNA. We speculate that co-transcriptional decoration of nascent pre-mRNAs with nuclear export factors prevents nuclear retention and Pab2-dependent 3′ end trimming, whereas the nucleolar-targeting signals of snoRNA ribonucleoproteins (snoRNPs) assembled during snoRNA transcription51 would promote nuclear retention and 3′ end maturation.By combining genome-wide studies and functional analyses of the fission yeast mRNA 3′ end processing machinery, we provide evidence supporting that a general cleavage-dependent, torpedo-mediated mechanism is used to promote transcription termination of protein-coding and ncRNA genes. Several observations support this conclusion: (i) mRNA 3′ end processing  and termination (Dhp1) factors are specifically recruited at the 3′ end of independently transcribed snoRNA, snRNA, lncRNA genes; (ii) mRNA 3′ end processing factors are required for snoRNA synthesis; (iii) polyadenylated pre-snoRNAs are produced from most snoRNA genes; (iv) 3′ end pab2Δ mutant. Thus far, our studies on 3′ end processing and transcription termination at snoRNA genes have identified three types of mutants: (i) one type showing transcription termination defects but no detectable RNA-processing deficiencies (dhp1), (ii) one type showing RNA maturation defects but normal transcription termination28 (pab2), and (iii) mutants that show defects in both transcription termination and snoRNA 3′ end processing . Collectively, these findings suggest that in addition to promoting the endonucleolytic cleavage for Dhp1-dependent termination, the CPF also contributes to snoRNA 3′ end processing in fission yeast. Although the precise role of the CPF in snoRNA 3′ end maturation remains to be determined, it may be important for the proper recruitment of Pab2, a view that is supported by protein interaction studies53.In addition to the detection of read-through transcription at snoRNA genes, depletion of CPF components including Pcf11, Ysh1, and Rna14 also led to the accumulation of polyadenylated snoRNA precursors similar to the S. cerevisiae appears primarily dependent on NNS54. We found that whereas transcription termination at both snoRNA and snRNA genes required Dhp1 in S. pombe, termination of snRNA transcription was not affected in Ysh1-deficient cells. This result suggests that the 5′ entry point for Dhp1 loading at snRNA genes may be mediated independently of the nuclease activity of the mRNA 3′ end processing machinery. Interestingly, read-through transcription at the S. pombe U2 snRNA gene was previously reported in a temperature-sensitive mutant of pac155, which encodes a homolog of the S. cerevisiae RNase III-like endonuclease Rnt1. Although the identity of the nuclease responsible for cleavage at S. pombe snRNA genes remains to be determined, our data suggest that snRNA transcription termination in fission yeast is more closely related to humans than to S. cerevisiae, as mRNA 3′ end processing factors56 and the torpedo nuclease XRN26 are important for efficient transcription termination of human snRNA genes.As for snoRNA genes, termination of snRNA transcription in S. cerevisiae and humans14, the peak of Ser2-P signal at the 3′ end of both mRNA and ncRNA genes provides an additional line of evidence supporting co-transcriptional 3′ end processing by the CPF in fission yeast. Intriguingly, however, Ser2-P does not appear to be essential in S. pombe58, suggesting that protein-RNA interactions may function as a redundant mechanism of CPF recruitment, as recently shown for elongation factors in budding yeast59. Second, our data indicates that the pattern of Tyr1-P on the CTD of S. pombe RNAPII at the 3′ end of genes differs from the distribution of Tyr1-P in S. cerevisiae20. Accordingly, although Tyr1-P levels increase along coding regions in both budding and fission yeasts, Tyr1-P signal decreases upstream of the poly(A) site in S. cerevisiae, whereas Tyr1-P signal persists downstream of the poly(A) site in S. pombe. These differing patterns of Tyr1-P around the poly(A) were unexpected, as Tyr1-P in S. cerevisiae was previously proposed to inhibit binding of CID-containing termination factors (Pcf11 and Rtt103) to Ser2-P CTD and prevent premature termination in coding regions20, a role that would also be anticipated to contribute to general transcription in S. pombe. Yet, the similar distribution of Ser2-P and Tyr1-P profiles downstream of the poly(A) site in S. pombe argues for diverging roles of Tyr1-P between budding and fission yeasts. Consistent with this idea, a truncated version of the CTD in which a phenylalanine replaces Tyr1 (Y1F) in each heptad repeat results in lethality in S. cerevisiae60, whereas the analogous truncated Y1F CTD mutant is viable in S. pombe58.Our study also elicits interesting questions as to the functional significance of RNAPII CTD phosphorylation in fission yeast. First, given the reciprocal relationship between Ser2 phosphorylation and 3′ end processing in S. cerevisiae rat137. Our data extend these finding by showing that (i) this observation is conserved in fission yeast, (ii) that Dhp1 depletion also causes elevated levels of Tyr1 phosphorylation, and (iii) that Dhp1 deficiency affects Tyr1 and Ser2 CTD phosphorylation at the genome-wide level. Although further studies will be needed to investigate how Dhp1/Rat1 nucleases modulate CTD phosphorylation at the 3′ end of genes, which may involve competition with the recruitment of CTD kinases61, this finding highlights the important functional relationship between CTD phosphorylation and transcription termination.Our genome-wide analysis of RNAPII occupancy revealed that Dhp1 is necessary for transcription termination of most protein-coding genes in fission yeast. In addition to transcription termination defects, elevated levels of Ser2-P signal were found at model protein-coding genes in a temperature-sensitive mutant of 62 supports the existence of an evolutionarily conserved role for Pab2/PABPN1 in the maturation of independently transcribed snoRNAs. It will be interesting to determine whether 3′ end processing and transcription termination of human snoRNA genes that are characterized by independent transcription unit depend on the mRNA cleavage and polyadenylation complex, as unveiled by our findings using fission yeast.Given that NNS-like transcription termination does not appear to be conserved in mammalian cells, it remains unclear how independently transcribed human snoRNAs, such as U3, U8, U13, and the human telomerase RNA, acquire their mature 3′ end. The fact that we have recently uncovered a polyadenylation-dependent 3′ end maturation pathway for the human telomerase RNA that depends on the nuclear poly(A)-binding protein PABPN1S. pombe strains used in this study is provided in Supplementary Table pcf11, dhp1, and seb1 are expressed from the thiamine-sensitive nmt41 and nmt81 promoters , Ysh1-FRB-GFP (ysh1-AA), and Rna14-FRB-GFP (rna14-AA) strains were grown in either EMM without leucine or YES media, and rapamycin was added or not at a final concentration of 2.5 µg/ml for 4–15 h. Cells were collected at OD600nm of ∼0.5–0.8. Gene disruptions and C-terminal tagging of proteins were performed by PCR-mediated gene targeting63 using lithium acetate method for yeast transformation. Expression of tagged proteins was confirmed by western blotting and knockouts strains by the absence of RNA by RT-PCR.A list of all S. pombe cells were adjusted to an OD600nm of 1.0, and serially diluted tenfold using water. Each dilution was spotted (3 µl per spot) on EMM plates with or without 15 µM of thiamine in the case of strains using the thiamine-sensitive nmt promoter (Pnmt), or on YES plates containing DMSO or 2.5 µg/ml rapamycin for the analysis of anchor-away mutants. Plates were incubated at 30 °C for 2–7 days.Exponential cultures of −) were used to inoculate larger 25-ml cultures that we grown in EMM leu− to early log phase (OD600nm 0.25–0.3). Rapamycin was then added to a final concentration of 2.5 µg/ml  and samples were taken at 0, 0.5, 1, 2, 3, 4, and 5 h, which were diluted 1:10 in water. Nuclei were stained using Hoechst 33342 for 5 min (0.2 mg/ml) and live cells were mounted on a 1.2% agarose/EMM leu− pad as described previously64. GFP-tagged proteins and nuclei were detected at 470 nm and 365 nm, respectively, using a Colibri system  on a Zeiss Axio Observer Z1 inverted microscope with a ×60/1.4 oil objective. Data were analyzed using the ZEN black software (Carl Zeiss Canada).Ysh1-GFP and Rna14-GFP localization was detected by using fluorescence microscopy. Briefly, precultures grown in EMM supplemented with adenine, uracil and histidine  to remove the heterogeneity of poly(A) tails. Preparation of probes, blot hybridization, washes, and quantification of signals were done as described previously24. Uncropped blots are shown in Supplementary Fig. Total RNA was extracted using the hot-acid phenol method. RNA samples were resolved on agarose-formaldehyde gel or on 6% polyacrylamide-8M urea gels, transferred onto nylon membranes and probed as described previously24. Chromatin was immunoprecipitated directly using Pan Mouse IgG Dynabeads  for TAP-tagged proteins. ChIP were also performed using Pan Mouse IgG Dynabeads coated with antibodies specific to Rpb1  or the hemagglutinin (HA) sequence . ChIP with phospho-specific CTD antibodies were performed using 2 µg of antibody: Ser2-P  and Ser5-P  were coated to Dynabeads M-280 Sheep anti-rabbit IgG beads , whereas Tyr1-P  and Ser7-P  were coated to Dynabeads Protein G beads . Control ChIP assays with untagged strains or with isotype matched control antibody were performed throughout the study.ChIP-qPCR and ChIP-seq experiments were performed as described previouslynab3Δ, sen1Δ, dbl8Δ, and sen1Δ/dbl8Δ strains were performed in YES media as described previously24. ChIP-seq experiments of total RNAPII and phospho-CTD modifications in wild-type and dhp1-depleted cells were performed with a spike-in adjustment procedure that allows a quantitative comparison between independent strains or conditions38. Chromatin preparations of S. pombe FBY1995  and FBY2016  strains and S. cerevisiae FBY2064 strain (reference strain containing a copy of HA-tagged histone H2B) were done as a regular ChIP, except that chromatin extracts have been frozen in liquid nitrogen and stored at −80 °C before affinity purifications. For Tyr1-P, Ser2-P, Ser5-P, Ser7-P, and 8WG16 IPs, a S. pombe/S. cerevisiae chromatin ratio of 0.9:0.1 was used, whereas a chromatin ratio of 0.995:0.005 was used for Rpb3-HA purifications. Following combination of S. pombe/S. cerevisiae chromatin extracts, ChIP assays were performed as described above using antibody-coated beads. ChIP-seq profiles of total RNAPII from WT and ysh1-AA strains were also performed with a spike-in adjustment (ratio S. pombe/S. cerevisiae of 0.9:0.1) using extracts from S. pombe that were previously grown in EMM and treated for 4 h with 2.5 µg/ml of rapamycin. Similarly, ChIP-qPCR of Rpb1 in ysh1 nuclease mutants  in WT, 24. Briefly, total extracts were prepared by lysis of mid-log phase S. pombe cultures in ice-cold lysis buffer (50 mM Tris-HCl (pH 7.5), 5 mM MgCl2, 150 mM NaCl and 0.1% NP-40 supplemented with 1 mM PMSF and 1× PLAAC) using a Precellys 24 homogenizer system (Bertin Technologies). Clarified lysates were normalized for total protein concentration using Bradford protein assay. Total extract proteins were separated by SDS-PAGE, transferred to nitrocellulose membranes, and analyzed by immunoblotting using antibodies against the hemagglutinin (HA) protein  dilution), the GFP protein , the protein A tag  dilution), the FLAG peptide  dilution) and the α-tubulin protein  dilution). Membranes were then probed with goat anti-rabbit or anti-mouse secondary antibodies conjugated to IRDye 800CW  dilution) and AlexaFluor 680  dilution), respectively. Protein detection was performed using an Odyssey infrared imaging system (LI-COR).Protein analysis was essentially performed as describedsnR99 constructs containing snR99, trx1, or rps2 terminator sequences were generated using the ade6 integration vector (pFB366) containing 1-kb of snR99-specific 5′ promoter sequences followed by the snR99 snoRNA region. The snR99 snoRNA region was then fused to either 1-kb of snR99 3′ sequences (pFB600), of trx1 3′ sequences (pFB622), and rps2 3′ sequences (pFB652). All constructs were confirmed by DNA sequencing. For single integration into the ade6 locus, pFB600, pFB622, and pFB652 were linearized by digestion with the AatII restriction enzyme and transformed into a snR99-null strain. Positive integrants were confirmed by growth selection on EMM agar plates lacking adenine and expression were confirmed by RT-qPCR using primers located in the snR99 region. Deletion of pab2 was than generated in these strains using the kanMX6 marker.A list of all plasmids and primers used in this study is provided in Supplementary Table ade6 integration plasmid (pFB366) as a host vector containing 640-bp of ysh1 5′ UTR sequences, the ysh1 coding sequence including introns, and 846-bp ysh1 3′ UTR sequences. Fusion of a 3x FLAG tag to C terminus of Ysh1 was performed using Q5 site-directed mutagenesis using primers containing the 3× FLAG tag DNA sequence, generating plasmid pFB1337. To generate amino acid substitutions at residies involved in Ysh1 endonuclease activity, histidine (H) residues 165 or 403 of Ysh1 were substituted to phenylalanine (F) to create pFB1355 (H165F) and pFB1358 (H403F), respectively. All mutations were performed by site-directed mutagenesis using pFB1337 as a template. All DNA constructs were confirmed by DNA sequencing. For single integration into the ade6 locus, pFB366, pFB1337, pFB1355, and pFB1358 were linearized and transformed into FBY2066 and/or FBY2110 strains. Positive integrates were confirmed by growth selection on EMM agar plates lacking adenine and leucine and by western blotting.The wild-type Ysh1 expression constructs were created by a three-step cloning procedure using the 24 using either the NEBNext ChIP-Seq Library Prep Master Mix Set for Illumina kit (New England BioLabs) or the SPARK DNA Sample Prep Kit Illumina Platform (Enzymatics) according to the manufacturer’s instructions.DNA libraries for ChIP-seq experiments were prepared as described previously65 with param ILLUMINACLIP:2:30:15 LEADING:30 TRAILING:30 MINLEN:23, and quality inspection was conducted using FastQC version 0.11.4 (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Considering that most of the samples were generated from chromatin contain exogenous spiked-in from S. cerevisiae, the trimmed reads from all data sets were aligned using BWA version 0.7.12-r103966 with the algorithm mem or aln depending on the read length (above or below 70 nt) and default parameters, onto a concatenated reference genome containing both the sequences of the S. pombe ASM294v2 and S. cerevisiae sacCer3 assemblies, inspired by others38. Note that no filtering on mapQ was performed in order to avoid discarding the signal at regions of the genome that are duplicated (BWA is randomly assigning the reads), but we generated mappability tracks for various read length to help the interpretation of particular regions. The number of reads mapped on the concatenated genomes varied from 91.5 to 99.6% of the sequenced reads .Briefly, the raw reads were trimmed using Trimmomatic version 0.32S. pombe genome is equivalent to 1 M reads of 100 nt, then the signal of the input data set was subtracted from its corresponding IP data set to generate the “sclWT-ctrl” files. The normalization of the data sets with spike-in was inpired by the method of presented by Orlando et al.38. For each data set, the sum of the signal coming from the reads aligned to the S. cerevisiae genome was first scaled to the equivalent of 1 M mapped reads of 100 nt, and the same scaling factor was applied to the signal coming from the reads aligned to the S. pombe genome to generate the “normSI” files. For the data sets generated in a WT and mutant strains, the S. pombe signal was next scaled to a total signal equivalent to 1 M mapped reads of 100 nt and the same scaling factor was applied to the corresponding mutant data set to generate the “normSI_sclWT” files. The signal of the input data set was then subtracted from its corresponding IP to generate the final “normSI_sclWT-ctrl” files used in downstream analyses.Each signal density file of the data sets without spike-in was scaled such that the total sum of the signal over the 68 Visual inspection of the data were performed using an AssemblyHub on the UCSC Genome Browser69 (https://genome.ucsc.edu/cgi-bin/hgHubConnect?hubUrl=https://datahub-i8kms5wt.udes.genap.ca/CTD_sno_pombe/hub&hgHub_do_firstDb=on&hgHub_do_redirect=on&hgHubConnect.remakeTrackHub=on).The normalized WIG files were then encoded in bigWig format using the Kent utilities34, 3′READS reads were mapped onto S. pombe ASM294v2 assembly using Bowtie 2 70. Uniquely mapped reads (with MAPQ score >10) that had at least two additional 5′ Ts after genome alignment were considered as polyA sites (PAS) reads. Each PAS was then assigned to the closest gene, including ncRNAs. The GTF genome annotations file version ASM294v2.29 was downloaded from PomBase72 in May 2017. However, based on manual inspection of our ChIP data, the orientation of three snoRNAs  was inverted. In more details and based on Liu et al.34, PAS supported with at least two reads outside CDS were associated to the closest 3′ end gene annotation in a strand-specific manner within 1 kb, whereas PAS inside CDS were ignored (except for overlapping genes if the closest 3′ end was within 500 pb). For each gene, the strongest PAS identified in the WT strain grown in minimal medium was used to modify the transcriptional 3′ end gene coordinate provided for mRNA genes  toolAll scripts used for data processing and statistical analysis were written in Python, Perl, or R, and are available upon request.Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3


Senile osteoporosis has become a worldwide bone disease with the aging of the world population. It increases the risk of bone fracture and seriously affects human health. Unlike postmenopausal osteoporosis which is linked to menopause in women, senile osteoporosis is due to aging, hence, affecting both men and women. It is commonly found in people with more than their 70s. Evidence has shown that with age increase, bone marrow stromal cells (BMSCs) differentiate into more adipocytes rather than osteoblasts and undergo senescence, which leads to decreased bone formation and contributes to senile osteoporosis. Therefore, it is necessary to uncover the molecular mechanisms underlying the functional changes of BMSCs. It will benefit not only for understanding the senile osteoporosis development, but also for finding new therapies to treat senile osteoporosis. Here, we review the recent advances of the functional alterations of BMSCs and the related mechanisms during senile osteoporosis development. Moreover, the treatment of senile osteoporosis by aiming at BMSCs is introduced. The word “osteoporosis” means “porous bone”, which is actually a worldwide metabolic bone disorder with high incidence. It is characterized by decreased bone mass, increased bone fragility and deteriorated microstructural bone tissues . It occuOsteoporosis is generally divided into two forms, primary osteoporosis and secondary osteoporosis. The primary osteoporosis mainly contains three categories, juvenile, postmenopausal, and senile osteoporosis, while the secondary osteoporosis is mainly caused by a large number of diseases and medications . The priBesides the imbalance between bone formation conducted by osteoblasts and bone resorption conducted by osteoclasts, evidence demonstrates that changes in number and function of bone marrow stromal cells (BMSCs) are also one key cause for senile osteoporosis . Study sTo date, numerous medicines have been used to treat senile osteoporosis, but there are still some limitations, due to their side effects ,17,18,19BMSCs are MSCs located in the bone marrow and have multiple differentiation potentials to become osteoblasts, adipocytes, or chondrocytes, which play an important role in maintaining normal bone stability. It has been demonstrated that the altered proliferation and differentiation of BMSCs is one main cause of senile osteoporosis . MoreoveBMSCs differentiation is controlled by various biological, chemical and physical factors. They have the ability to differentiate into osteoblast, chondrocytes and adipocytes, which are responsible for making bones, cartilages and adipose tissues. Unfortunately, in old ages, BMSCs start to differentiate into fewer osteoblasts, but more adipocytes, which is one main cause of senile osteoporosis . JusteseLike other cells, BMSCs also follow senescence, as their primary culture does not grow infinitely, but in a limited fashion. Senescence is considered to be strongly related to aging and age-related disorders like senile osteoporosis . TherefoBMSCs are constantly affected by various exogenous and endogenous factors. These factors regulate BMSCs either to proliferate, die, or undergo a permanent cell cycle arrest . FactorsAlthough BMSCs are pushed into irreversible growth arrest during senescence, being metabolically active, they assume large, granular and flat shapes with increased β-galactosidase expression ,43,44. DDuring old ages, the shift of differentiation into adipocytes rather than osteoblast or become senescence of BMSCs both contribute to senile osteoporosis. Therefore, it is necessary to elaborate on the underlying molecular mechanisms. Here we primarily discuss the various intracellular biological factors like transcriptional factors, signaling pathways and epigenetic regulations. Moreover, we also introduce the various chemical and physical factors that affect BMSCs either positively or negatively, like exercise, excessive fat diet and radiations.Transcription factors play an important role in regulating BMSCs to differentiate into osteoblasts or adipocytes, or undergo senescence. They are involved in regulating the expression of different genes that are responsible for initiating and promoting differentiation and senescence in BMSCs.A series of transcription factors have been discovered to play major regulatory roles in osteogenic differentiation of BMSCs. Besides Runx2 and Osterix, two key osteogenic transcription factors, there are some other transcription factors that have been demonstrated as important regulators in differentiation of BMSCs into osteoblasts including β-catenin, homeobox C7 (HOXB7), core binding factor α1 (CBF-1α), forkhead box C2 (FOXC2), tumor necrosis factor-α (TNF-α), homeobox A2 (HOXA2), yes-associated protein (YAP) and bone morphogenic factor 9 (BMP9) .Runx2 also known as core binding factor α1 (Cbfa1) is an important transcription factor involved in osteogenic differentiation of BMSCs. Its activation has been recognized as an initiation signal for the commitment of BMSCs to osteogenesis . ActuallTo date, a range of transcriptional factors has been identified to participate in adipogenic differentiation in BMSCs. The most well-known transcription factor is PPARγ. In addition, early B cell factor-1 (EBF-1), Twist-1, Twist-2, CCAAT/enhancer binding protein α (C/EBPα), chicken ovalbumin upstream promoter transcription factor II (COUP-II), PR domain containing 16 (PRDM16), sex determining region Y-box 2 (Sox2) and octamer-binding transcription factor 4 (Oct4) also play roles in regulating adipogenic differentiation of BMSCs . ForkheaPPARγ belongs to the nuclear receptor (NR) superfamily of ligand-activated transcription factors that regulates the genes involved in adipocyte differentiation of BMSCs . It has During aging, BMSCs become senescent, and transcription factors are involved in this process. Nuclear factor erythroid 2-related factor 2 (NRF2) is downregulated in senescent BMSCs ,61. ActuTo date, several signaling pathways have been reported to be involved in the regulation of BMSCs differentiation and senescence. Bone morphogenic protein (BMP), wingless-type MMTV integration site (Wnt) and Notch signaling pathways are critically important for differentiation of BMSCs, while p53/p21 and p16/Rb are important for BMSCs senescence. Apart from these, other signaling pathways like Hedgehogs (Hh), neural epidermal growth factor-like (NEL)-like protein 1 (NELL-1), insulin-like growth factor-I (IGF-I) and fibroblast growth factors (FGFs) also plays an important role in BMSCs differentiation and senescence.β1 family that is widely involved in regulating various BMSCs cellular processes like proliferation and differentiation [BMPs belong to TGFntiation . To datentiation   including BMPR-I and BMPR-II and activates canonical Smad-dependent pathways  or non-canonical Smad-independent signaling pathway (p38 mitogen-activated protein kinase (MAPK) pathway) ,70. Stimntiation   are the two interrelated key pathways involved in regulating senescence of BMSCs. In addition, some other pathways like TGF-β, Wnt, MAPK, PI3K/AKT/mTOR, Notch and FGFs also function in controlling senescence of BMSCs.p53/p21 and p16/Rb signaling pathways are actually regulated in responding to some phenomena causing DNA damage, such as telomeres shortening, reactive oxygen species (ROS) accumulation. Shortening of telomeres occurs after every cell division, ultimately reach to “Hayflick limit”, which deprives the cells of further division . This phBMP signaling is also involved in inducing senescence in BMSCs through contributing to the production of ROS and triggering DNA damage response . Wnt/β-cEpigenetic regulations play important roles in the differentiation and senescence of BMSCs. During transcription, transcriptional factors are not only involved in regulating gene expressions, but also in correlation with epigenetic factors. Mutations in such epigenetic factors even result in severe disorders like osteoporosis and cancer. Therefore, it is important to elaborate the role of epigenetic regulations including DNA methylation, histone modifications, and epigenetic regulators such as non-coding RNAs  in the differentiation and senescence of BMSCs.OC promoter to osteo-inductive transcription factors [Epigenetic regulations actually alter the binding ability of osteogenic transcriptional factors with their target promoters by changing chromatin structures. It is a recognized fact that Runx2 works as a master regulator in inducing osteogenesis in BMSCs . However factors . Villar- factors . Villagr factors . Upregul factors . Further factors . Apart f factors ,103,104. factors ,107,108. factors .γ is the master regulator of adipogenic differentiation of BMSCs [adiponectin, glut4, and lep during commitment [PPARγ gene [Epigenetic regulations also play an important role in adipocyte differentiation. Just as osteogenic differentiation, adipogenic differentiation is a well-organized phenomenon containing transcription factors performing various functions. PPAR-of BMSCs . Its actof BMSCs . Bowers of BMSCs . Similarof BMSCs . H3K4me2mmitment . MoreoveARγ gene .Apart from these, microRNAs also function in regulating adipogenic differentiation of BMSCs. Qadir et al. have identified that miR-124 promotes adipogenesis of BMSCs by suppressing the expression of a pro-osteogenic transcription factor Dlx5 . SimilarINK4A and p21CIP1/WAF1 promoter regions [In addition to the other factors, epigenetic changes are also involved in causing senescence of BMSCs. It has been identified that the DNA methylation levels slowly decrease with time in cell culture . So et a regions . Histone regions . Moreove regions . MicroRN regions . The let regions . Lal et  regions . Wagner  regions . In addi regions . MiR-195 regions ,129.Besides transcription factors, signaling pathways and epigenetic regulations, there are some other external or internal chemical, physical and biological factors that induce differentiation and senescence of BMSCs.Normally, for osteogenic differentiation, BMSCs are cultured in a medium containing L-ascorbic acid (AA), β-glycerophosphate (βGP) and Dexamethasone. Combination of these chemicals has the ability to initiate collagenous extracellular matrix formation, which upregulates the expression of osteogenic indicators alkaline phosphatase (ALP) and OC . SimilarSome physical factors, such as radiations and mechanical stimuli also contribute importantly to the differentiation and senescence of BMSCs. It was observed that a range radiations (0–16 Gy) applied on human pluripotent cells and BMSCs promoted adipogenesis and declined osteogenesis . FurtherOther biological factors like aging and metabolism, also regulate BMSCs differentiation and senescence. During aging, BMSCs differentiate more into adipocytes and less into osteoblasts, resulting in bone loss. Moerman et al. found increased expression of PPARγ in aged BMSCs, which is considered as the master regulator of adipogenesis . AlteredIn old ages, BMSCs either differentiate into more adipocytes than osteoblasts or assume senescence, which ultimately results in senile osteoporosis. Therefore, in order to treat senile osteoporosis, it is required to use the strategies in what BMSCs can be stimulated either to differentiate into more osteoblasts than adipocytes or be eliminated their senescence. To date, numerous molecules including parathyroid hormone (PTH 1–84) or only its N-terminal fragment teriparatide (PTH 1–34), bisphosphonates, tetracycline, cationic peptides and antibodies like denosumab and romosozumab have been used in the treatment of senile osteoporosis ,17,18,19In order to treat senile osteoporosis, several researchers have reported the successful transplantation of BMSCs using animal models. Transplanted BMSCs, serve in bone formation either by allocating damaged areas to differentiate into osteoblasts or assume paracrine mode, due to which they secrete specific growth factors to make a favorable environment for the nearby cells to repair the degenerative tissue . IchiokaκB signaling inactivation [Certain factors, microRNAs and long non-coding RNAs have also been recognized to play significant roles in treating senile osteoporosis by stimulating BMSCs to differentiate into more osteoblasts than adipocytes. Suppression of ectopic viral integration site‑1 (Evi1) gene through RNA interference in rat BMSCs resulted in increased osteogenesis and decreased adipogenesis, suggesting Evi1 as a potent target for targeting osteoporosis . Huan ettivation , which mDifferent approaches have also been used to eliminate the senescence of BMSCs, and thus, treat senile osteoporosis. Elimination of senescent cells is of much importance regarding bone mass and strength. In order to uncover such importance, Joshua et al. used some genetic and pharmacological procedures to eliminate the senescent cells. They found that activating INK-ATTAC caspase 8 in senescent cells or treating senescent cells with JAK inhibitor or senolytics increased bone mass and bone strength in mice with the bone loss . A senolSenile osteoporosis is an age dependent bone disorder occurring both in men and women, which has become a worldwide health concern. The functional change of BMSCs has been demonstrated to contribute to senile osteoporosis, showing as BMSCs differentiate into fewer osteoblasts, but more adipocytes and BMSCs become senescent. Besides the critical involvement of BMSCs in senile osteoporosis, BMSCs are also favorite cell source for cell therapy and have been applied for osteoporosis treatment. Therefore, uncovering the underlying mechanisms of function changes of BMSCs during senile osteoporosis is important not only for better understanding the involvement of BMSCs in senile osteoporosis, but also for manipulating them for clinical applications.Recent findings demonstrate that numerous transcriptional factors, signaling pathways, epigenetic regulations and other factors play key roles in regulating the differentiation and senescence of BMSCs, the alteration of which contributes to senile osteoporosis. Runx2 and PPARγ are two key transcription factors that are responsible for osteogenic differentiation and adipogenic differentiation of BMSCs, respectively. Decreased Runx2 expression and increased PPARγ results in senile osteoporosis. NRF2 and FOXP1 are two transcription factors related to the senescence of BMSCs by regulating antioxidant responsive genes. They are decreased with age, thus, leads to BMSCs senescence and bone loss. BMP signaling, Wnt signaling and Notch signaling pathways all show dual roles in regulating osteogenic and adipogenic differentiation of BMSCs. They function either by targeting the downstream transcription factors, such as Runx2, PPARγ, or by cross-talking with each other. Recently, p53/p21 and p16/Rb signaling pathways have been demonstrated to be involved in the senescence of BMSCs, which is one main cause of senile osteoporosis. These signaling pathways are activated by DNA damage or ROS accumulation and finally lead to cell senescence. Besides, BMP signaling and Wnt signaling also participate in inducing senescence of BMSCs by inducing ROS, triggering DNA damage or interacting with p53/p21 signaling. Moreover, epigenetic regulation also plays important role in regulating differentiation and senescence of BMSCs. The epigenetic regulation, such as DNA methylation and histones acetylation, regulates the differentiation and senescence of BMSCs by regulating the expression of transcription factors or disturbing the binding of transcription factors to specific gene’s promoter. These findings provide an understanding of the molecular mechanisms underlying the altered differentiation and senescence of BMSCs during senile osteoporosis and provide potential targets or methods for treating senile osteoporosis.Direct transplantation of normal BMSCs and elimination of senescent BMSCs both efficiently treat senile osteoporosis. Transplantation of normal allogeneic BMSCs into aged mice shows both prevention and treatment effects on senile osteoporosis. In addition, modification of the differentiation ability of BMSCs through targeting some genes can be applied for treating senile osteoporosis. More recently, elimination of senescent BMSCs has been demonstrated to be an effective therapeutic method for treating senile osteoporosis. All these findings strongly demonstrate that BMSCs can be applied for clinical treatment of senile osteoporosis by directly transplanting normal BMSCs, modifying differentiation of BMSCs, or eliminating senescent BMSCs. However, present findings are obtained from animal studies. Further clinical trials are needed.In summary, the altered differentiation and senescence of BMSCs contribute to senile osteoporosis. Transplantation of normal BMSCs, modification of altered differentiation ability of BMSCs, and elimination of senescent BMSCs can effectively treat the senile osteoporosis. However, as differentiation and senescence, the two key physiological processes of BMSCs, are sometimes closely linked, there are still some questions to be investigated. How do BMSCs make a choice, to differentiate to specific cell type or undergo senescence? What regulatory factors play a primary role in regulating these processes? Moreover, for the treatment of senile osteoporosis, as present findings are from animal studies, clinical trials are needed in future. By answering these questions and conducting clinical trials, we will get a better understanding of the role and mechanisms of BMSCs in senile osteoporosis and may provide new insights for manipulating BMSCs for clinical applications.