Drosophila, Hairless, and of a second CSL interacting repressor, SMRTER. As predicted there was significant overlap between Hairless and its CSL DNA-binding partner, both in Kc cells and in wing discs, where they were predominantly found in chromatin with active enhancer marks. However, while the Hairless complex was widely present at some Notch regulated enhancers in the wing disc, no binding was detected at others, indicating that it is not essential for silencing per se. Further analysis of target enhancers confirmed differential requirements for Hairless. SMRTER binding significantly overlapped with Hairless, rather than complementing it, and many enhancers were apparently co-bound by both factors. Our analysis indicates that the actions of Hairless and SMRTER gate enhancers to Notch activity and to Ecdysone signalling respectively, to ensure that the appropriate levels and timing of target gene expression are achieved.Repressors are frequently deployed to limit the transcriptional response to signalling pathways. For example, several co-repressors interact directly with the DNA-binding protein CSL and are proposed to keep target genes silenced in the absence of Notch activity. However, the scope of their contributions remains unclear. To investigate co-repressor activity in the context of this well defined signalling pathway, we have analysed the genome-wide binding profile of the best-characterized CSL co-repressor in  The communication between cells that occurs during development, as well as in disease contexts, involves a small number of signalling pathways of which the Notch pathway is one. One outstanding question is how these pathways can bring about different gene responses in different contexts. As gene expression is co-ordinated by a mixture of activators and repressors, we set out to investigate whether the distribution of repressors across the genome is important in shaping whether genes are able to respond to Notch activity. Our results from analyzing the binding profile of two repressors, Hairless and SMRTER, show that, in many cases, they are not essential for preventing a gene from responding. Instead they are deployed at a limited number of genetic loci where they gate the response, helping to set a threshold for gene activation. Perturbations to their function lead to enhanced gene expression in limited territories rather than to new programmes of gene expression. Their main role therefore is to restrict the time or levels of signal that a gene needs to receive before it will respond. Originally thought to be the primary factor that renders enhancers and promoters silent when signalling is absent, the role of repressors has become more enigmatic since several have been found to reside at sites of active chromatin –6.Growth, patterning and differentiation during development are coordinated by the activity of conserved signalling pathways whose action is largely realised through the transcriptional programmes they regulate. This necessitates mechanisms that ensure appropriate gene expression programmes are initiated, depending on cellular context, and that allow the fine tuning of gene expression in response to signalling levels. One way this is achieved is through the deployment of repressors –9. Several different co-repressors have been found to interact directly with CSL and are proposed to keep target genes silenced in the absence of Notch activity . In Drosophila, the best characterized co-repressor, Hairless, is a large unstructured protein that binds directly to Suppressor of Hairless (Su(H)), the Drosophila CSL –15. As implied by their names, Su(H) was first identified on the basis of loss of function alleles that suppressed the phenotypes caused by a reduction in Hairless levels (H/+), highlighting the intimate relationship between these two proteins , 17. Hairless itself functions as an adaptor, binding to Groucho and CtBP that in turn have the capability to interact with histone deacetylases (HDACs) –20. It is thought that the HDACs prevent gene activity by modifying the local chromatin environment rendering it refractory to transcription.The Notch pathway is one example where the outcome of signalling is tuned by repressors. When activated, the Notch receptor becomes cleaved, releasing the intracellular domain, NICD, which collaborates with a DNA binding protein, CSL, to regulate gene expression Drosophila, it is not well conserved outside the Diptera  and its role appears to be fulfilled by multiple different proteins in mammals, including KyoT2 , 23, MINT/SHARP –26 and SMRT . While these proteins clearly bind to CSL and form a complex with HDACs and demethylases that modify chromatin , 28, their functional roles have only been demonstrated at a few specific loci. Thus it remains questionable how widely such repression mechanisms operate. Second, with the diversity of CSL partners it is unclear what contributions the different types of complex might make, for example, whether they are recruited to different targets or have different sensitivities to NICD. Indeed, even in Drosophila the SMRT orthologue SMRTER, has also been reported to bind to CSL  and might contribute to repression at a subset of targets , 31.While the model that CSL is complexed with repressors in the absence of Notch activity is a widely accepted one, there remain many uncertainties. First, although Hairless is a well established partner of Su(H) in Drosophila Kc cells and in wing imaginal discs. As predicted, Hairless binding showed substantial overlap with that of Su(H), with a clear correlation in binding intensities. However, analysing the regulation of specific targets also revealed: (i) that the role of Hairless in silencing Notch targets is limited and is not a pre-requisite for a gene’s ability to respond to Notch activity; (ii) silencing of Hairless insensitive genes cannot be accounted for by binding of SMRTER, another co-repressor. The genome-wide profiles together revealed that many enhancers are bound by all 3 factors, Su(H), Hairless and SMRTER, and detailed investigations into an enhancer from thread/Diap1 suggest this is indicative of co-regulation by Notch and Ecdysone signalling.To gain insight into the regulatory contribution from CSL interacting co-repressors, we analysed the genome-wide binding profiles of Hairless in To investigate the extent of Hairless recruitment to chromatin in Kc cells, two strategies were taken. First, GFP-tagged Hairless and GFP-Su(H) were generated in the context of genomic fragments spanning the gene loci, so that the proteins were expressed at close to physiological levels when introduced into Kc cells e.g. . The chr and, consistent with this model, the binding profiles of the proteins were found to overlap at many loci (E(spl)-complex genes, there was excellent correspondence of GFP-Su(H) and GFP-Hairless binding, while Hairless-Dam produced a broader profile centred on the same regions (Su(H) is known to form a complex with Hairless any loci . For exa regions . Overlap regions . These c (bona fide co-repressor bound sites (e.g. CHES-1-Like). Finally, in cells depleted for Hairless, there were significant changes in RNA levels from genes that were bound by both Su(H) and Hairless as well as from those bound by Hairless only (Although many Su(H) bound regions exhibit Hairless binding in close proximity, the converse is not the case: 87% of regions enriched for Hairless do not overlap with Su(H) bound sites. There are two possible interpretations: one is that Su(H) binding at those positions was not captured , the other is that additional factors besides Su(H) can recruit Hairless to DNA. Motif analysis suggests that the former explanation is likely to make, at best, a minor contribution, since enrichment for Su(H) motifs in the Hairless-only regions was only marginally significant . This suggests that other factors may contribute to Hairless recruitment. Many of the Hairless-only regions (>37%) also exhibit binding to the Hairless partner Groucho  , consistess only . Notablyess only ;S3 Table. A smaller fraction (21%) mapped to regions with characteristics of active transcription start-sites , which are also enriched in active chromatin marks. The remainder were located in intronic or primed chromatin. This distribution is broadly similar to that of Su(H) , and the regions that were co-bound had similar profiles to those bound by Hairless only , a modification that is increased following Notch activation . We found no global changes in the levels of H3K56ac in Hairless depleted cells (E(spl) locus, similar to that observed when Notch signalling is activated, indicating that the presence of Hairless can suppress histone acetylation  and that it may, under some circumstances, modulate chromatin modifications at those positions and contribute to repression. However, the broad profile of Hairless binding indicates that it is also likely to be brought to chromatin independently of Su(H), and its effects may be complex as some bound regions exhibited increased gene expression in cells depleted of Hairless, whereas others showed decreases.H[P8]/H mutant flies, indicating that the GFP-Hairless protein was functional and expressed at physiological levels. The chromatin association of GFP-H in wing discs was determined by ChIP and compared to existing data for Su(H) occupancy .To determine whether Hairless exhibits similar occupancy profiles in tissues, transgenic flies containing a genomic construct carrying GFP-tagged Hairless were generated. The line was capable of rescuing the viability of E(spl) locus, such regions included deadpan  and Hairless were bound at an intronic enhancer of the deadpan (dpn) gene that has been shown to confer expression in wing discs , this is not expressed in wing discs. We examined the Hairless-only regions for binding motif enrichments and identified matches to Aef1 (p = 1.21e-24) and Grainyhead (p = 4.04e-10) motifs, which are both widely expressed in the wing disc and are proposed to act as repressors in at least some contexts, making them plausible Hairless partners –42.As with Kc cells, a significant proportion (70%) of the Hairless associated regions in wing discs did not overlap with the sites bound by Su(H). These Hairless-only regions were not enriched for the Su(H) motif (rank = 145 p = 0.045), suggesting that other factors are involved in Hairless recruitment. Indeed, a Hairless-GFP mutated in the Su(H) binding domain appears to still be recruited to chromatin, since bands indicative of binding to salivary gland polytene chromosomes are detected in live imaging experiments . While ocut and wingless–46. Both are normally expressed at high levels at the dorsoventral (D/V) boundary. However, they can be induced by ectopic Notch activity at other locations in the wing disc . Strikingly, neither of these genes exhibited detectable binding of Hairless or Su(H) at their characterized wing-disc enhancers  do not appear to occupy those loci in most cells. This suggests that stable binding of Su(H)/Hairless is not a pre-requisite to render the genes responsive. Indeed, in discs over-expressing NICD, both cut and wg enhancers showed significant enrichment for Su(H) binding  occupancy.Both  binding , indicat binding . Notablytin mark , indicat, 31. Since several loci did not exhibit Hairless binding, we reasoned that at least some of these might instead be dependent on SMRTER regulation. We therefore determined the genome-wide profile of SMRTER occupancy in wing discs, using an in-frame YFP fusion generated by a protein-trap transposon insertion . We detected 1165 enriched regions . It is thus plausible that SMRTER could contribute to repression at Su(H) bound enhancers. However, no significant binding was detected at dpn, indicating that SMRTER is unlikely to be an obligate partner of Su(H)/Hairless, nor was binding detected at cut or wg enhancers.SMRTER is a co-repressor that, similar to Hairless, has been suggested to contribute to repression of Su(H)/Notch regulated targets  1% FDR; , of whic 1% FDR; . This waProteins that occupy the DNA together in a complex might be expected to exhibit similar enrichment profiles. Pairwise comparisons were therefore made of the top 100 bound regions, ranked by fold enrichment, for Su(H), SMRTER and Hairless. Only the profiles for Su(H) and Hairless exhibited a significant correlation , no corrthread/Diap1 . This region exhibited enhancer activity, conferring a similar expression pattern to the endogenous gene when placed upstream of a GFP reporter . We therefore examined the effects on the expression of this reporter when depleting Hairless and SMRTER, by targeting RNAi to the posterior part of the wing-disc . Knock down of either of the repressors resulted in de-repression of th1.2-GFP  and Hairless binding was within an intron of ad/Diap1 . This reh1.2-GFP . In the h1.2-GFP . When bobination . Similardepleted .th1.2 enhancer was mutated (th1.2[mut]) and its expression analysed in similar knock-down experiments. Under wild type conditions, low levels of residual expression were observed with the mutated enhancer, which were little changed by the knock-down of Hairless .To investigate whether the functions of Hairless and/or SMRTER are mediated through Su(H), the Su(H) binding motif in the Hairless . In contHairless . This im, 30) and we found that SMRTER binding peaks were significantly enriched for one of the EcR motifs . We therefore compared the profile of SMRTER binding to published EcR binding data from a similar stage . 38% of SMRTER peaks overlapped with EcR bound regions and there was a significant correlation between the SMRTER and EcR peaks when the top 100 peaks (ranked by enrichment) were compared . Target genes that were highly enriched for SMRTER and EcR binding included Hr39 and Blimp-1 (Since SMRTER can exert repression at an enhancer that lacks a Su(H) binding motif, it is likely that it is recruited to chromatin by another DNA binding protein. In this respect, SMRTER has been proposed to act as a co-repressor for the Ecdysone receptor  is likely indicative of enhancers that are co-regulated by Ecdysone and Notch.We examined whether EcR was involved in the regulation of the ock-down , while T of NICD . The up-bolished . These d, 10. Our data support the notion that the co-repressor Hairless is bound with Su(H) at several Notch regulated enhancers, since their genome-wide binding profiles in both Kc cells and wing discs exhibited considerable overlaps. Furthermore, depletion of Hairless in Kc cells resulted in transcriptional de-repression and an increase in histone acetylation at some loci. Likewise, the absence of Hairless led to de-repression of target-genes such as deadpan and thread/Diap1 throughout the wing disc.In prevailing models for Notch mediated regulation of target genes, target loci are bound by a CSL-co-repressor complex, from which the co-repressors are displaced by NICD to activate transcription cut, wg and vg did not generally display Hairless (or Su(H)) binding in the wing disc despite the fact that they are strongly induced throughout the disc when ectopic NICD is provided. This implies that their silencing is not generally dependant on the Hairless/Su(H) repressor complex. In agreement with this idea, no de-repression of cut or wg occurred in most cells lacking Hairless and only a very modest de-repression was observed at the dorsoventral boundary where these genes are normally expressed. It is therefore likely that Hairless is recruited in only a small population of cells where it may help to dampen or refine the response of target enhancers. This is borne out by the limited number of genes that are de-repressed by knock-down of Hairless in Kc cells.Our results, however, challenge the view that pre-binding of the Su(H)/Hairless repressor complex is required for genes to be able to respond to NICD. Several well-known Notch regulated genes, such as , whose homologue SMRTER was found to co-IP with Su(H) in flies , making it a plausible candidate . Analysis of genome-wide SMRTER binding indicated that a significant fraction of Su(H) bound regions were also occupied by SMRTER, although the binding intensities were not well correlated. However, many of the co-bound sites were also regions enriched for Hairless, including thread/diap1, which was robustly enriched for all 3 proteins. Further analysis of thread regulation demonstrated that both Hairless and SMRTER are important for suppressing its expression, albeit in slightly different ways. When the Su(H) motifs in the thread enhancer were mutated, only the Hairless regulation was lost while that of SMRTER remained. These data, along with the strong correlation between SMRTER and Ecdysone Receptor binding, imply that the co-repressors are recruited to the same enhancer via different DNA-binding partners: Hairless via Su(H) and SMRTER via EcR. Crosstalk between Notch and EcR also occurs at the cut enhancer, although this involves Broad rather than EcR . Thus we conclude that much of the co-localization of SMRTER and Su(H) is likely indicative of genes that are regulated by inputs from the EcR and Notch pathways, although we cannot fully rule out the possibility that SMRTER could act via Su(H) in some circumstances.Since relatively few Notch regulated genes were bound by Hairless, this raised the possibility that an alternative co-repressor might be recruited at other loci. For example, one of the CSL partners in mammalian cells is SMRT , a key partner of Hairless, and for another class of repressors/co-repressors . Likewise, Dorsal repressed enhancers exhibited some active chromatin marks (H3K4me1) although these were found to be hypoacetylated compared to their active counterparts , 53. It is proposed these repressive factors contribute to polymerase pausing , 52 rather than more long-term silencing , so that gene transcription would be kept in check until/unless conditions change and RNA polymerase is released. Another suggestion is that modulation by repressors enables a fine regulatory control over transcriptional output from a given target gene so that it can be graded over range of values. Indeed, the mammalian CSL co-repressor SHARP has been suggested to control a permissive chromatin state at Notch target genes by concomitantly promoting H3K27 deacetylation and H3K4 methylation . The modest changes in acetylated histones that occurred at some highly regulated loci in Hairless depleted cells would fit with these models, as would the varied changes in gene expression that occur in the Kc cells. Thus we propose that Hairless, like SHARP and other similar factors, is likely to interact with a range of partners through which it will modulate, rather than silence, the response of a target enhancer to the levels of Notch activity, most likely via local effects on chromatin.A striking feature of the Hairless bound regions is that they correlate with regions of active chromatin, despite Hairless involvement in repression. Similar features have been noted for Groucho  inserted in-frame before the stop codon located at exon 4, to generate a protein fusion at the C-terminus. This plasmid was used in transfection experiments (see below) and subsequently injected into strains containing an AttP40 site to generate transgenic Hairless-GFP flies. The functionality was assessed by its ability to rescue H[P8]/H flies; the viability of the mutant flies was rescued  indicating that the plasmid confers functional Hairless activity.To generate a genomic Hairless construct, AttB plasmids containing the genomic region 3R: 20621141–20628985 (using primers 5’-GCATTCGTCTCAATAACTAACGTCG 5’-CGCAATAAAAAGACACCTGCAACC) were constructed, with the coding sequences of eGFP (enhanced Green Fluorescent Protein) and Dam methylase For the genomic GFP-Su(H), an AttB plasmid containing the genomic region 2L 15038840–15045039 (using primers 5’ -CAAGTTAGATATGGCAATGCACCG 5’-ACTGCATATCTGTACTGATGACG) was constructed, with the coding sequences of eGFP inserted in frame at the start of exon 1, to generate a protein fusion at the N-terminus. This plasmid was used in transfection experiments (see below).OC in Shields and Sang M3 insect medium , supplemented with 5% FBS , 1g/L yeast extract , 2.5g/L bacto-peptone  and 1x Antibiotic-Antimycotic . For Hairless RNAi, Kc cells were transfected with 20μg dsRNA in Fugene 6  in 10 cm plates according to the standard protocol and then incubated for 72h. RNA isolation was performed using Qiagen Rneasy Midi kit (cat N 75142).Kc cells were cultured at 25 http://www.cs.wustl.edu/~jbuhler/research/dapple/). Raw data were then loaded into limma  and normalised with the vsn package . The resulting ratios are log2 ratio of sample/control. Four biological replicates were analysed, data are available from GEO as part of super series GSE97603. Genes with altered expression were assigned to a ChIP peak(s) if the peak was within 10kb (upstream or downstream).To 50μg total RNA in 28μl DEPC water 1μl of 500 ng/μl oligo (dT)23 anchored primer (Sigma) was added and incubated at 65°C for 10 minutes, then placed on ice. 8μl of 5x first strand buffer (Invitrogen), 2μl of low-C dNTP mix , 2μl of 1mM Cy3 or Cy5 dCTP , 2μl of 0.1M DTT (Invitrogen), 0.5μl of RNAsin (Promega) and 2μl of Superscript III reverse transcriptase (Invitrogen) were added and incubated at 46°C for 2 hours. The reaction was stopped with 20μl mix of 0.5M EDTA and 1M NaOH and incubated at 65°C for 15 minutes. Sample was neutralised with 25μl of 1M Tris-HCl (pH 7.5). Combined Cy3- and Cy5-labelled probe (sample and control) were purified with AutoSeq G-50 column  and the volume reduced to between 2-5μl in a speed vac with medium heat. Then 2μl of 10mg/ml sonicated salmon sperm DNA (Invitrogen) and 140μl of Ocimum hybridisation buffer were added to the labelled mixture and boiled at 100°C for 2min. 140μl of the labelled sample was loaded to 70-mer long oligo microarrays , and hybridised for 16 hours at 51°C. Post-hybridisation washes were performed as per PowerMatrix slides protocol (FMB). Arrays were scanned at 5μm resolution with a GenePix 4000B (Axon) dual laser scanner. Images were processed and spot quantified by the Dapple software  Kit (GenomePlex #WGA2-50RXN). The amplification reaction was supplemented by adding 0.75ul of 10mM dUTP. The amplification was performed for 14 cycles. After purification with Qiagen PCR cleanup columns, 7.5μg of purified DNA was hybridized to GeneChip Drosophila Tiling 2.0R Array according to Affymetrix specifications. Three independent replicates were performed for each construct.For Chromatin immunopreciptation Kc cells were transfected with Hairless-GFP or GFP-Su(H) plasmids in combination with a plasmid containing puromicyn resistance gene (pMT-Puro) using Fugene 6 and grown under puromycin selection (2μg/ml). Chromatin preparation and ChIP were essentially as described previously DpnI overnight at 37°C. DpnI was inactivated at 80°C for 20min. Genomic DNA fragments were ligated to Phosphorylated AdR adapters  in 20μl reaction for 2 hours at 22°C using FERMENTAS (cat# EL0011), supplemented with PEG-4000. The reaction was inactivated at 65°C for 10 min and subsequently digested with DpnII, the resulting DNA fragments were cleaned using Qiagen PCR cleaning kit (Cat#28104). DNA was amplified for 15 cycles by PCR using Expand DNA polymerase (Cat#11732641001) supplemented with 0.1mM dUTP and Adr-PCR primer (5' GGTCGCGGCCGAGGATC). After amplification, adapters were removed by DpnII digestion and cleaned using Qiagen PCR cleaning columns. Samples were then fragmented and hybridized to GeneChip Drosophila Tiling 2.0R Array according to Affymetrix specifications. Three replicates of the Hairless-Dam and a Dam-only control were performed.For DamID experiments, KC cells were transfected with Hairless–Dam using Fugene 6 and incubated for 72 hours before harvesting. Genomic DNA was extracted using Qiagen DNeasy Blood and Tissue Kit (#69504 or #69506), following manufacturer's instructions. 2.5μg of genomic DNA were digested in 10μl with ImmunoPrecipitation Dilution Buffer) was then added to the mixture and the sample was sonicated for 7 min, with a 30 second “ON/OFF” cycle, in a pre-cooled Bioruptor (Diagenode UCD-200). After sonication, the sample was centrifuged at 13200rpm at 4°C for 10 min, and the chromatin containing supernatant then diluted with 200μl of IPDB. ChIP was performed as previously described , 57, using polyclonal rabbit anti-GFP (Abcam ab290). Three ChIP samples were then pooled for library preparation using the GenomePlex Complete WGA kit. 14 rounds of amplification were performed and the DNA purified using Qiagen PCR cleanup columns. 250μg DNA was then subjected to a further 10 rounds of amplification in the presence of 0.75μl of 10mM dUTP. After purification with Qiagen PCR cleanup columns approximately 7.5μg of DNA was hybridised to Affymetrix GeneChip Drosophila Tiling 2.0R Arrays according to Affymetrix specifications. Three (Hairless) or two (SMRTER) independent replicate experiments were performed.Dissected heads from 30 third instar larvae (Hairless-GFP or SMRTER-YFP) were fixed with 1ml of 4% Formaldehyde +1.5mM of EGS (25mins at room temperature) and the reaction quenched with 200μl of 2M-glycine solution. After rinsing 3x (1 x PBS + Roche complete protease inhibitor cocktail) the wing discs were removed and transferred to 50μl of nuclear lysis buffer  for 10 min on ice before homogenising the wing discs. 250μl of IPDB  and for overlap with chromatin signatures, the profile for Kc cells was used  (https://github.com/rstojnic/notch-chromatin). Motif enrichment analysis was performed using the Bioconductor package PWMEnrich , which assesses the enrichment of each motif from a library of 650 experimentally derived DNA motifs for Drosophila transcription factors. Accessible chromatin in BG3 and Kc167 cells was used as a background for calculating P-values of enrichment. The correlation between ChIP signals was calculated on enhancers that are a union of all ChIP peaks from the considered datasets. The average signal over the whole enhancer was then plotted for pairs of datasets and the Pearson correlation and corresponding P-value calculated.Dataset overlaps were analysed using GenomicRanges . The noise distribution was used to convert differences between con and HRNAi within individual 2kb regions into a P-value, which was then corrected for multiple testing using the Hochberg-Benjamini algorithm. The resulting P-value represents the False Discovery Rate (FDR). An FDR threshold of 1% was used to define regions of significant difference.Analysis of K56 acetylation changes in Kc cells following , and the binding model used. We used a null model in which Su(H)-H binding is dependent on each other (as estimated from available binding data), but SMRTER binding is independent of both. We assumed there is between 0 and 5000 additional sites in the genome that are unoccupied but that could in principle be bound. We inferred the number of unoccupied enhancers by maximising the likelihood of the fit. Finally, we calculated the P-value of the difference between the observed and expected individual patterns using Fisher’s exact test. We found that 70% more enhancers are bound by all three factors (Su(H), H, SMRTER) than expected by our best-fitting model .The significance calculation of combinatorial overlaps strongly depends on the number of unoccupied enhancers www.flybase.org) unless otherwise indicated. The following mutant and reporter lines were used: H[P8], H[P1] SMARTER-YFP[CPTI001385]; and th1.2-GFP; cut1.3-GFP and wg2.2-GFP. In RNAi and overexpression experiments, the Gal4 driver stock engrailed:Gal4 Tub:Gal80ts was combined with UAS lines and larvae were shifted to 30°C 48 hours after egg laying. The following RNAi and overexpression lines were used: UAS-w RNAi (TRiPGL00094), UAS-Hairless RNAi (TRiPJF02624), UAS-SMRTER RNAi (KK1026110), UAS-Notch-intra[79.2]; UAS-Taiman; UAS-EcR-RNAi; UAS-GFP-RNAi (BL-9330); UAS-lacZ. Note that UAS-wRNAi, UAS-GFP RNAi or UAS-lacZ were included where appropriate to ensure the number of UAS sequences was kept consistent in each experiment.All alleles and stocks are described in FlyBase , mouse anti-Cut , mouse anti-Wg , guinea-pig anti-Dpn , rabbit anti-GFP . Alexa conjugated secondary antibodies were from ThermoFisher.Region Of Interest) was pre-defined using ImageJ64, and, for a given experiment, consistent ROI settings were used across genotypes and they were placed at similar positions. Mean grey value measurements for the ROI within the manipulated posterior region were normalised to measurements for the ROI in the wild type anterior compartment for each wing disc. Individual data points are the relative values for each wing disc analysed, and the mean value was calculated for comparison between genotypes. The significance of differences in the expression ratios was assessed using a T-test; p<0.05 is indicated by single asterisk, p<0.01 is indicated by double asterisk and p<0.001 is indicated by triple asterisk.Fluorescence quantifications were performed using ImageJ64. Identical laser and confocal settings were used throughout a single experiment, and in all cases measurements were from at least two independent experiments. An experiment-specific-ROI Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S1 Fig. (C) Genomic region from 2L comparing the profiles of replicates (orange) from H-DamID  and H-GFP ChIP (lower R1-R3) with the combined profile obtained for each dataset (brown). Fold enrichment, Log2 scale -0.50 to -1.5. Orange bars indicate regions enriched in both H-GFP ChIP and H-DamID, referred to as Hairless high confidence bound regions. Gene models are depicted in blue. (D) Percentage of peaks from the different data sets as indicated overlapping with the genomic features, coloured according to the legend.(A) Expression levels from plasmids with tagged genomic fragments are similar to endogenous levels. Western blot detecting GFP from controls (no Su(H)-GFP) and from Kc cells containing GFP-Su(H) or a control plasmid. A larger band corresponding to GFP-Su(H) (large arrow) is detected in cells containing the Su(H)-GFP plasmid, expression levels are similar to endogenous Su(H)  present in all extracts. (B) Venn diagram illustrating overlap between regions significantly methylated by Hairless-Dam  and enriched in Hairless-GFP ChIP . The overlap is highly significant . Inset; Overlap between similar data sets for Groucho from (TIF)Click here for additional data file.S2 Fig for further details). (B) Percentage of peaks from the different data sub-sets as indicated overlapping with the genomic features, coloured according to the legend. (C) Percentage of peaks from the different indicated datasets overlapping with the regions bound by Groucho (from ). (D) Fold change in RNA expression levels when Hairless is depleted for genes associated with the indicated subsets of bound regions. Left graph depicts all genes with significant change in expression (p≤0.5); Right graph, only those genes with log2 fold change >0.4 (p≤0.05).(A) Distributions of regions occupied by Su(H)+Hairless, Su(H) only or Hairless only in relation to chromatin states, all exhibit strong preference for signature 3, “enhancer” state and, to a lesser extent, signature 4 active TSS state (see (TIF)Click here for additional data file.S3 Fighh. Graphs show H3K56ac enrichment (brown) and differences in H3K56ac enrichment (green) in control and H RNAi treated Kc cells, regions of significant difference are indicated by the green box . Hairless bound regions are indicated by blue boxes; not all H bound regions exhibit significant changes in H3K56ac when Hairless is depleted.(A-B) Empirical distribution frequency plots comparing K56ac enrichment in control (GFP-RNAi) and Hairless depleted (H-RNAi) cells at all peaks and at Hairless peaks, no large-scale differences are detected. (C) Empirical distribution frequency plot comparing differential K56ac levels at H peaks (red) and Su(H) peaks, indicates that they are similar, with Su(H) peaks showing a slightly higher frequency of changes. (D) Knock-down of H results in an increase in H3 acetylation at a few H bound positions, illustrated by (TIF)Click here for additional data file.S4 FigBoth wildtype and Hairless L235D (a mutation that perturbs Su(H) binding,  are seen(TIF)Click here for additional data file.S5 Figreaper11-lacZ reporter  and (B) cut1.3-GFP reporter . Wing discs expressing the indicated RNAi’s in the engrailed domain, complementary to the regions detected by anti-Ci .Depletion of Hairless or SMRTER leads to de-repression of (A) (TIF)Click here for additional data file.


Individual groups of retroviruses and retroviral vectors differ in their integration site preference and interaction with the host genome. Hence, immediately after infection genome-wide distribution of integrated proviruses is non-random. During long-term in vitro or persistent in vivo infection, the genomic position and chromatin environment of the provirus affects its transcriptional activity. Thus, a selection of long-term stably expressed proviruses and elimination of proviruses, which have been gradually silenced by epigenetic mechanisms, helps in the identification of genomic compartments permissive for proviral transcription. We compare here the extent and time course of provirus silencing in single cell clones of the K562 human myeloid lymphoblastoma cell line that have been infected with retroviral reporter vectors derived from avian sarcoma/leukosis virus (ASLV), human immunodeficiency virus type 1 (HIV) and murine leukaemia virus (MLV). While MLV proviruses remain transcriptionally active, ASLV proviruses are prone to rapid silencing. The HIV provirus displays gradual silencing only after an extended time period in culture. The analysis of integration sites of long-term stably expressed proviruses shows a strong bias for some genomic features—especially integration close to the transcription start sites of active transcription units. Furthermore, complex analysis of histone modifications enriched at the site of integration points to the accumulation of proviruses of all three groups in gene regulatory segments, particularly close to the enhancer loci. We conclude that the proximity to active regulatory chromatin segments correlates with stable provirus expression in various retroviral species. Integration of retroviral genomic DNA into the host genome is a key step in the retroviral replication cycle. Although there are reports regarding the expression of retroviral genes from an unintegrated genome , effectiMost retroviruses are known to non-randomly target the host genome. Human immunodeficiency virus type 1 (HIV) and related lentiviruses preferentially integrate into active genes ,3,4,5,6 These integration preferences are driven by cellular targeting factors, which bind to retroviral integrase and have affinity for certain histone marks. In this way, the retroviral intasomes tether to specific chromatin regions that are enriched at respective histone marks. For HIV, two proteins that are critical for the targeting of HIV proviruses have been identified, lens epithelium-derived growth factor (LEDGF/p75) and cleavage and polyadenylation specific factor 6 (CPSF6). LEDGF/p75 binds the integrase of HIV, enhances integration and targets intasomes to active genes ,11,12 anDisruption of the interaction between the intasome and BET proteins or LEDGF/p75 has resulted in the decreased efficiency of retrovirus integration and retargeting outside the preferred genomic regions ,20. HencFunctional studies correlating the integration site environment and provirus transcription have mostly focused on the HIV latent reservoir—a population of proviruses with epigenetically silenced expression in certain cell niches . Early sIn parallel to HIV, the link between integration sites and proviral expression has also been studied in ASLV-infected mammalian cells. Non-avian cells are not permissive for ASLV ,36 and AIn the present study, we compared the patterns of provirus expression in single cell clones infected with retroviral vectors derived from ASLV, HIV and MLV. The analysis of integration sites of stably active proviruses showed that some genomic and epigenomic features, especially proximity to active regulatory segments, correlate with stable provirus expression of various retroviral species.The construction of plasmids used for the propagation of LTR-driven enhanced green fluorescent protein (EGFP)-expressing vectors  cells was counted by LSRII flow cytometer . The GP-293 and HEK293 cell lines were maintained in D-MEM/F12  with 5% new-born calf serum, 5% foetal calf serum  and penicillin/streptomycin  in a 5% CO2 atmosphere at 37 °C. K562 human myeloid lymphoblastoma cell line was maintained in RPMI 1640 supplemented with 5% new-born calf serum, 5% foetal calf serum and penicillin/streptomycin  in a 5% CO2 atmosphere at 37 °C.Propagation of retroviral vector AG3 using the AviPack packaging cell line was part of the previous study and is described there . MLV-bas+ cells 3 dpi did not exceed 1% of infected cell culture. Three dpi, GFP+ cells were sorted in single-cell sort mode using an Influx cell sorter  into 96-well tissue culture plates to obtain single-cell clones. Expanded clones were sub-cultured by passaging 25% of the cells three times a week. The percentage of GFP+ cells was assessed 30 and 60 dpi with the LSRII cytometer. Clones containing ≥90% GFP+ cells in the clonal population 60 dpi were arbitrarily regarded as stably expressing clones. For ASLV and HIV-1 clones, genomic DNA was isolated separately from each clone. In the case of MLV, clones exhibiting stable GFP expression were pooled and collected for DNA isolation.The K562 cell line was infected and single-cell sorting was performed according to the previously described protocol . Cells wThe provirus-cell DNA junction sequences were amplified using the splinkerette-PCR method . The prohttp://genome.ucsc.edu/). Genomic coordinates of the LTR-proximal nucleotide of the obtained genomic sequences with unique score were considered as positions of integration.All junction sequences containing the end of 5’LTR and the unique cellular DNA sequence obtained from the splinkerette PCR were mapped to the Feb. 2009 human genome assembly (hg19) using BLAT found on the UCSC Genome Browser website . The sources are described in more detail in [http://fantom.gsc.riken.jp/5/). Analysis of distances from, and the frequency of, targeting of the features was performed using the GenomicRanges R package [Genomic and epigenomic data for in silico analysis of features associated with integration sites and umMRCs were obtained from UCSC golden path (etail in . Data fo package .A RefSeq Gene was considered to be active if its TSS was either within the H3K4me3 peak (for the selection of histone modification peaks see ), or witIn order to simplify the analysis associating integrated proviruses to chromatin states, twenty-five chromatin segments that were generated using Hidden Markov Model-based modelling  were merOne thousand umMRCs per integration site were generated. For each umMRC, the distance to active RefSeq genes whose TSSs associated with a Tss chromatin segment was counted in the same manner as performed for integration site analysis. For each integration site, the three umMRCs with the most similar distance to an active gene when compared to integration site were randomly selected.p-value of the frequencies of targeting the features Fisher’s Exact Test for Count Data was used. To count the p-value of the distances to the features, Wilcoxon signed rank test was used.R software version 3.3.2. was used for statistical analysis. To count the +) were single-cell sorted and expanded to clonal populations. The established cellular clones were then examined for the number of cells expressing EGFP at 30 and 60 dpi. Clones containing at least 90% GFP+ cells 60 dpi were regarded as clones which contain stably active proviruses. For comparison, we included the dataset of K562 clones containing the ASLV-derived pAG vector. These clones were obtained in analogous experiment described by Senigl et al. [To examine the stability of proviral expression, we used vectors derived from HIV and MLV in a clonal assay, which is schematically depicted in l et al.   maintaining provirus expression. In contrast, more than 80% of HIV- and MLV-transduced clones  maintained stable expression at 30 dpi  maintained provirus expression, the numbers of clones with stable ASLV and HIV expression further decreased to 3% (74) and 49% (136), respectively . HIV proviruses displayed an equal proportion of proviruses in sense or antisense orientations to endogenous transcription. A striking majority of MLV proviruses were found in antisense orientation compared to that of targeted RefSeq Genes .First, we analysed the frequency of integration into transcription units  and the orientation of proviruses relative to transcription of targeted RefSeq Genes A,B. ASLVNext, we measured the distance of stably expressed proviruses from the transcriptional start sites (TSS) of the RefSeq Genes C. All grIn conclusion, we have shown the differential distributions of stably expressed proviruses of ASLV, HIV and MLV. ASLV proviruses accumulated inside RefSeq Genes close to TSS and mostly in sense orientation to the gene transcription while proviruses of HIV also accumulated inside RefSeq Genes but in longer distances to TSS and in both orientations. There is no overrepresentation of stably active MLV proviruses inside RefSeq Genes but they were mainly distributed around the TSS mostly in the anti-sense orientation.p = 0.0148, Fisher’s Test for Count Data, As we have shown previously ,40, the We observed the same effect at the level of distance from the TSS of active RefSeq Genes B. Hits oIn order to address the activity of TUs targeted by integrations, we used publicly available RNA-seq data as described previously . BrieflyThese results demonstrated that the proviruses selected for stable transcriptional activity accumulated near the TSSs of active TUs, likely because of their active transcription-associated chromatin environment, which is also permissive for provirus expression.Epigenetic features of the chromatin environment at the site of integration were first described by comparing the distances of the proviruses and umMRC to peaks of eleven histone modifications  defined We then calculated the distances of the long-term active proviruses to the chromatin segments, which are defined by the combination of genomic and epigenomic features that are specific for distinct functional parts of genome specified for the K562 cell line . First, Together, the analysis of epigenomic and functional landscape of stably active proviruses showed that regardless of origin of provirus, stable expression of provirus associates within the proximity to the genomic loci driving genomic transcription. Although stably active proviruses of ASLV and MLV were found closer to the features associated with an active TSS than HIV proviruses, the proviruses of all three groups were found to harbour enhancer-proximal loci.As shown in Together, these data show that when real integration sites are compared to their matched controls that mimic the active gene targeting of proviruses, the close proximity to the features that are characteristic for active TSS and enhancers are preserved as a hallmark of stably active proviruses of ASLV, HIV and MLV.The heterogeneity of proviral expression and the role of chromatin environment in proviral transcriptional activity, for example in HIV infection in vitro and in vivo, are still unclear as some controversies remain to be resolved . In In our previous studies, we showed that most ASLV proviruses in human cells are effectively silenced and that rare transcriptionally stable proviruses strongly depend on their position in the host genome ,40. The Unlike ASLV, the majority of HIV and MLV proviruses transcriptionally active early after infection were transcriptionally stable during the subsequent culturing. This confirmed the previous observation of cellular clones that were productively infected with HIV-derived vector, which kept the provirus expression stable for months after infection . Our sysAn important issue of the splinkerette PCR is the comparison with random matched control, which normalizes the imperfect coverage of insertion sites and potentially biased amplification in multiplex PCR. Our datasets of integration sites were compared to random controls matched on several levels—the distance to restriction enzyme recognition sites, the mappability of the region and the distance to specific chromatin segment. Only significant differences compared to the random matched controls were used to draw conclusions.We found similar frequencies of stably active ASLV and HIV proviruses integrated in active RefSeq Genes. In the case of ASLV, their accumulation in active RefSeq genes results from the selection eliminating the silenced proviruses . HIV proStably active proviruses of MLV did not accumulate in active RefSeq Genes but were concentrated around TSSs, with the median distance comparable to that observed in ASLV and with even shorter distances around enhancers. While ASLV accumulated close to active TSSs and enhancers only after long-term selection for proviral expression, MLV preferentially targeted active TSS and enhancers due to the interaction of integrase with BET proteins ,17,18. TTERT and Myb genes were found among the most clonally expanded integrations showing the link between the provirus accumulation and common integration sites widely studied using ALV [The weak preference of ASLV integration for active genes and close-to-random distribution of non-selected ASLV proviruses is advantageous for insertional tumorigenesis studies. Malhotra et al.  comparedsing ALV ,56. We asing ALV .Based on our comparison of stably active ASLV, HIV and MLV proviruses, we suggest that the proximity to an active TSS is important for the stable expression of proviruses with silencing-prone promoters such as ASLV and HIV, whereas the proximity to enhancers favours the stable activity of proviruses with silencing-resistant promoters such as MLV or our previously described ASLV vector artificially equipped with a CpG island core sequence . InteresAlthough our data points to the importance of chromatin content in proviral transcriptional activity, further studies that include the analysis of a larger set of integration sites together with single-provirus expression profiles will be needed to confirm the proposed model. Our clonal approach used here and in previous studies offers a longitudinal record of single provirus expression and correlation with the properties of respective integration site. The drawback of this method, the labour intensity and low throughput, has recently been overcome by Chen et al. , who couThe results of this study are important particularly for the design of retroviral vectors. Our data shows that proviruses selected for their long-term expression stability accumulate at transcriptionally active chromatin in the vicinity of regulatory elements such as promoters and enhancers. This raises the risk of genotoxicity and clonal expansion, which should be taken into account and addressed in future studies.


Brassica oleracea is from variation in vernalization response through allelic variation at FLOWERING LOCUS C.C2 (FLC4Bo). We characterize two alleles of FLC.C2Bo that are both functional and confer a requirement for vernalization, but they show distinct expression dynamics in response to cold. Complementation experiments in Arabidopsis thaliana revealed that the allelic variation results from cis polymorphism at FLC.C2Bo, which quantitatively influences the degree of cold‐induced epigenetic silencing. This results in one allelic variant conferring consistently later heading under both glasshouse and field conditions through reduced environmental sensitivity. Our results suggest that breeding of brassica varieties for commercially valuable variation in heading date has been achieved through the selection of cis polymorphism at FLC, similar to that underpinning natural variation in A. thaliana. This understanding will allow for the selection of alleles with distinct sensitivities to cold and robust heading dates under variable climatic conditions, and will facilitate the breeding of varieties more resistant to climate change.Variation in flowering time and response to overwintering has been exploited to breed brassica vegetables that can be harvested year‐round. Our knowledge of flowering time control now enables the investigation of the molecular basis of this important variation. Here, we show that a major determinant of heading date variation in  Brassica oleracea) varieties throughout the year is a function of allelic differences at the floral repressor BoFLC.C2. Here, we show that epigenetic silencing and reactivation of expression after cold exposure of BoFLC.C2 are critical factors in this variation. Domestication in horticultural brassicas has therefore exploited similar cis polymorphism at FLC to that underpinning natural variation in Arabidopsis thaliana.Being able to harvest different broccoli ( Arabidopsis thaliana. Mutations in many loci influence flowering time, but the majority of the natural variation in A. thaliana flowering time maps to two loci, FRIGIDA (AtFRI) and FLOWERING LOCUS C (AtFLC). Allelic variation at AtFRI is the major determinant of vernalization requirement . This variation is used commercially to ensure continuous production of the crop. We chose two genotypes, E5 and E9, for further study. Both have an obligate requirement for cold, but E9 requires longer cold periods than E5 to head. This difference in vernalization response was observed in duplicate field trials at independent UK sites with contrasting winters in Lincolnshire (relatively hard winters) and Cornwall . In these trials the heading date of the E5 parent line significantly differed between years and locations (P < 0.001), whereas that of the E9 parent was the same in Lincolnshire in both 2007/8 and 2011/12, and in Cornwall in 2011/12 (P = 0.227). Only in Cornwall in 2007/8, with a milder winter in which the mean weekly temperature did not fall below 6°C, was the heading date of the E9 parent significantly later .We investigated heading date in four genotypes of purple sprouting broccoli . Thus, variation at this locus appears to result in differential heading and environmental sensitivity.A proprietary Doubled Haploid (DH) mapping population was available from a cross between these genotypes, and we used this to map QTLs controlling vernalization response under both controlled and field conditions. Up to eight QTLs of varying levels of significance were identified, four of which were common across at least four of the seven growth conditions Figure S1d). One QTL was mapped on all seven occasions. This common QTL, accounting for between 5 and 25% of the heading date variation, mapped to linkage group C2  were transformed into the A. thaliana genotype Columbia FRI flc2  independent transgenic plants were generated for each allele and flowering time was analysed in the T3 generation. Homozygous BoFLC.C2E9 transgenic plants flowered consistently later than those carrying BoFLC.C2E5 . We sequenced BoFLC.C2 from the E5 and E9 genotypes and found that the two alleles encode predicted open reading frames of 198 and 197 residues, respectively  in 20 genotypes from the cultivated B. oleracea Diversity Foundation set . Analysis of polymorphism between the nine allelic classes revealed a network divided into three broad groupings, with BoFLC.C2E5 and BoFLC.C2E9 the most frequently occurring alleles within the main two groups, BoFLC.C21‐1 and BoFLC.C23‐1, respectively . Once genotypes carrying the previously identified loss‐of‐function single nucleotide polymorphism (SNP) in exon 4 .The high level of non‐coding polymorphism between the FLC leads to the phenotypic differences observed, we analysed BoFLC.C2E5 and BoFLC.C2E9 expression in the B. oleracea E5 and E9 genotypes by quantitative real‐time RT‐PCR. Both BoFLC.C2 alleles are repressed by 10 weeks of vernalization at either 5°C or 10°C . Following 4 weeks at 5°C the expression of both the BoFLC.C2E5 and BoFLC.C2E9 alleles reactivated after plants were returned to warm conditions; however, following 8 weeks at 5°C, expression of the BoFLC.C2E5 allele was almost completely repressed when plants were returned to the warm, whereas expression of the BoFLC.C2E9 allele reactivated  in the E5 and E9 genotypes  regulate the cold‐sensitivity requirement of vernalization. Our analysis identified BoFLC.C2 as a candidate for a major QTL for heading date variation after different exposures to cold. Heterologous complementation analyses in A. thaliana then showed that the differential expression dynamics of the two BoFLC.C2 alleles post‐vernalization were recapitulated in the transgenic lines. Thus, cis variation between two functional BoFLC.C2 alleles confers quantitative variation in heading date, via an influence on the epigenetic silencing of FLC expression. Therefore, the two BoFLC.C2 alleles show differential environmental sensitivity, an important factor in commercial broccoli production .A requirement for vernalization defines whether a plant overwinters before flowering – a winter annual, biennial or perennial – or adopts a summer annual or rapid‐cycling reproductive strategy, which in some environments enables multiple generations a year. As such, vernalization requirement and the ability to fine‐tune the cold‐temperature sensitivity of vernalization provides key variation that plant breeders have used and will need in the future to develop varieties in an era of climate change. Here, we provide evidence for how cis polymorphisms is responsible for BoFLC.C2 expression variation is yet to be determined. The fact that the exon‐2 polymorphisms do not appear to segregate with crop type  points to non‐coding intronic polymorphism at BoFLC.C2 underpinning quantitative variation in cold‐induced BoFLC silencing and reactivation. There are therefore parallels between this molecular variation and the natural variation in vernalization response in A. thaliana  appear to flower at a similar time following the same number of weeks of cold at temperatures ranging between 2°C and 12°C  of domestication resulting in a variation bottleneck caused by the removal of cis‐acting polymorphisms, as a consequence of manmade selection  at 18°C . Seedlings were pricked out after 11 days and grown for 70 days in experiment 1 and 90 days in experiment 2, so the plants were no longer in the juvenile phase and were responsive to vernalization treatment. Plants were then vernalized for 10 or 18 weeks under a short‐day photoperiod at 5°C or 10°C in a controlled environment room. Plants were transferred to warm conditions in April 2010 and 2011, potted on into 2‐L pots and grown in an unheated glasshouse with a minimum 14‐hour natural photoperiod. Plants were scored for buds visible at the apex, apical head at approximately 12 mm (the size of a 10‐pence coin in the UK) and date of opening of first flower.A total of 120 and 82 Doubled Haploid (DH) lines from the proprietary mapping population were transplanted into the field at independent sites in Cornwall  and Lincolnshire  in three randomized, replicated blocks in July 2007 and 2011, respectively. The plots were netted to prevent damage from rabbits and pigeons. Plants were scored for buds visible at the apex, apical head at approximately 12 mm (the size of a 10‐pence coin in the UK) and date of opening of first flower.genstat  following the manufacturer's conditions, and was then sequenced (primers are given in Table S1). The constructs were ligated into binary vector pSLJ1711  is a core collection of lines that represent the genetic variation across the morphologically diverse crops of this species (http://www.brassica.info/resource/plants/diversity_sets.php). DNA was isolated as described in Irwin et al. . Sequences were aligned using AlignX in Vector NTI (Invitrogen) and analysed in splitstree4  and analysed by qPCR on a LightCycler 480 II instrument , using LightCycler 480 SYBR Green I Master mix . BoFLC.C2 mRNA accumulation was assayed with primers BoFLC.C2‐F and BoFLC.C2‐R. Expression was normalized using an orthologue of the Arabidopsis gene UBC , with primers UBC‐F and UBC‐R. BoFT.C2 and BoFT.C6 were similarly assayed using the following primer combinations: BoFT.C2‐F1 and BoFT.C2‐R1; BoFT.C6‐F2 and BoFT‐C6‐R2.Total RNA from three biological replicates was extracted from leaf material sampled at the same time of day as described previously  with primers UBC21_UPL_F and UBC21_UPL_R, and PP2A (At1g13320), PP2A_F2 and PP2A_R2. Expression of endogenous Arabidopsis FT was assayed with primers FT_UPL#138_F and FT_UPL#138_R. Primers are listed in Table S1.Expression analysis in Arabidopsis transgenics was conducted on pooled samples of homozygous TFigure S1. Heading date variation in purple sprouting broccoli.Click here for additional data file.Figure S2. Allelic variation at BoFLC.C2.Click here for additional data file.Figure S3. Expression analysis in E5 and E9 parent lines.Click here for additional data file.Figure S4. Flowering time of Arabidopsis BoFLC.C2 transgenics.Click here for additional data file.Figure S5. Expression of BoFLC.C2 alleles in transgenic Arabidopsis.Click here for additional data file.Figure S6. Expression of AtFT.C2 in transgenic Arabidopsis.Click here for additional data file.Table S1. Primers used in this study.Click here for additional data file. Click here for additional data file.


Long Interspersed Elements (LINE-1) demonstrated that elements formally encode a reverse transcriptase activity . The characteristics of class2 structures allude to the occurrence of additional integration mechanisms by the LINE-1 reverse transcriptase that may occur in germ cells or during embryogenesis (Onozawa and Aplan). To note, the features described in these class2 structures are consistent with previous reports of endonuclease-independent LINE-1 retrotransposition . Here the authors examined the expression and integration differences in breast invasive carcinoma, head and neck squamous carcinoma, and lung adenocarcinoma and their analysis indicates two cases of LINE-1 mediated insertions near two different tumor suppressor genes, including an Alu insertion into the CBL gene in breast invasive carcinoma and a LINE-1 insertion into the first exon of the BAALC gene in a head and neck squamous cell carcinoma. Again, these findings are consistent with the protovirus hypothesis. However these tumors may also harbor mutations in “host” genes that regulate LINE-1 retrotransposition. A number of reviews were included in this topic that address recent studies on LINE-1 retrotransposition in cancer . In addition, identifying cellular genes and pathways that regulate LINE-1 transcription and activity is an active area of research, and two reviews discuss the current understanding regarding the regulation of LINE-1 retrotransposition in somatic cells, which may become dysregulated in cancer . The topic also includes two original research articles on the impact of endogenous retroviruses on genome evolution. In the article by Irie et al., the authors use dN/dS analysis and molecular approaches to validate their findings regarding the contribution of the sushi-ichi retrotransposon during the evolution of the zinc finger protein-encoding gene SIRH11/ZCCHC16 and the impact of this gene during eutherian brain evolution. In addition, another research article examines the evolution of the Tbx6 transcription binding sites, (ORRA1-ORRA1D), which are LTRs derived from the endogenous retroviruses, MaLRs . The authors examine the impact on transcription of genes harboring these Tbx6 binding sites, using the Tbx6 knockout mouse. Their findings are coupled with biochemical and bioinformatic approaches. Finally two reviews nicely described the host cellular factors that impact the transcriptional dynamics of ERVs in the human genome .Phylogenetic analysis of the reverse transcriptase domains support the idea that retroviruses and telomerase evolved from non-LTR retrotransposons, due to the gain or loss of LTR sequence and/or sequences encoding for specific domains , including the LINE-1 encoded RT, and the endogenous retroviruses ERVs and MaLR. These articles also summarize the findings in the field regarding these reverse transcriptases in normal biology and disease. These summaries and newly reported findings are consistent with the protovirus hypothesis Temin, . IdentifAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


Profiles of DNA methylation of many tissues relevant in human disease have been obtained from microarrays and are publicly available. These can be used to generate maps of chromatin compartmentalization, demarcating open and closed chromatin across the genome. Additionally, large sets of genome-wide transcription factor binding profiles have been made available thanks to ChIP-seq technology.We have identified genomic regions with altered chromatin compartmentalization in prostate adenocarcinoma tissue relative to normal prostate tissue, using DNA methylation microarray data from The Cancer Genome Atlas. DNA binding profiles from the Encyclopedia of DNA Elements (ENCODE) ChIP-seq studies have been systematically screened to find transcription factors with inferred DNA binding sites located in discordantly open/closed chromatin in malignant tissue (compared with non-cancer control tissue). We have combined this with tests for corresponding up-/downregulation of the transcription factors’ putative target genes to obtain an integrated measure of cancer-specific regulatory activity to identify likely transcriptional drivers of prostate cancer.Generally, we find that the degree to which transcription factors preferentially bind regions of chromatin that become more accessible during prostate carcinogenesis is significantly associated to the level of systematic upregulation of their targets, at the level of gene expression. Our approach has yielded 11 transcription factors that show strong cancer-specific transcriptional activation of targets, including the novel candidates KAT2A and TRIM28, alongside established drivers of prostate cancer MYC, ETS1, GABP and YY1.This approach to integrated epigenetic and transcriptional profiling using publicly available data represents a cheap and powerful technique for identifying potential drivers of human disease. In our application to prostate adenocarcinoma data, the fact that well-known drivers are amongst the top candidates suggests that the discovery of novel candidate drivers may unlock pathways to future medicines.Data download instructions and code to reproduce this work are available at GitHub under ‘edcurry/PRAD-compartments’.The online version of this article (doi:10.1186/s13073-017-0443-z) contains supplementary material, which is available to authorized users. Study into the mammalian nucleus has revealed that higher order chromatin structure involves organization of DNA into co-localized compartments, such that physical interactions between loci occur almost exclusively within the same compartment . One comInitial data on the partitioning of the genome into these two compartments have come from applications of the Hi-C technique, which uses chromosome conformation capture in conjunction with high-throughput DNA sequencing to identify pairs of loci that were physically proximal enough to be cross-linked with formaldehyde . When a Prostate cancer is the most common cancer in males in developed countries, resulting in more than 300,000 deaths worldwide in 2012 (Cancer Research UK (CRUK) statistics). While many localized cancers are cured with initial therapy or may be sufficiently indolent that no treatment is necessary, some will be aggressive with metastasis leading to death from the disease . Recent Importantly, despite considerable efforts, the molecular drivers remain unknown for approximately a quarter of all primary prostate cancers with both good and poor clinical prognosis . GreaterLevel 1 DNA methylation microarray data were downloaded from The Cancer Genome Atlas (TCGA) Data Portal. These data comprise two ‘idat’ files for each of 502 primary PRAD tissues and 50 normal prostate tissues. Idat files were processed in R using the ‘minfi’ package, according to the protocol in . The sum of this signal of unique reads was computed for each 100-kb window, and these scores were compared for windows with different compartment calls as inferred from DNA methylation data.Processed data as H3K27ac ChIP-seq peaks positions  mapped Processed data as H3K27me3 ChIP-seq peak summits  , from 1) mapped Gene-level thresholded GISTIC2-processed copy-number data were downloaded from the University of California, Santa Cruz (UCSC) Cancer Browser website. Genes were mapped to each 100-kb genomic window using coordinates defined by Ensembl (Feb 2014 archive with hg19), and the total number of copy-number states  across the cohort was counted for each window.A compendium of TF binding sites was obtained from ENCODE representing 495 ChIP experiments with duplicates, covering 119 TFs in 77 human cell lines. Only peaks passing an irreproducible discovery rate (IDR) filter of 2% across at least two replicates were included as putative DNA binding sites. Androgen receptor binding sites were obtained from GEO [GEO:GSE65478], using data from . Bindingt statistics for differential expression between tumour and normal samples were obtained using ‘limma’ [Normalized gene-level counts for RNA-seq data for 500 primary PRAD tumours and 67 normal prostate tissues were downloaded from the UCSC Cancer Browser website. Empirical Bayes moderated  ‘limma’ .The fold enrichment of TFs binding DNA to regions of aberrant chromatin compartmentalization in PRAD was calculated as follows:without tumour-specific open chromatin; ‘where ‘peaks’ refers to the genomic regions showing reproducible TF binding in the ChIP-seq experiment; ‘TSO’ refers to the genomic regions with tumour-specific open chromatin; ‘The statistical significance of differential expression of a TF target was assessed through rank sum tests implemented in the ‘geneSetTest’ function within the R package ‘limma’. This tests against the null hypothesis that the ranks of the TF target genes are randomly distributed across the differential expression statistics, from most overexpressed gene  to most underexpressed gene.p value for enrichment of the TF target genes in systematic overexpression in tumour samples relative to normal prostate tissues. TFs with a large positive integrated score were thus hypothesized to be likely transcriptional drivers of prostate adenocarcinoma, especially those TFs with relatively high-ranking scores in each individual characteristic.An integrated measure of tumour-specific chromatin accessibility was obtained by multiplying the logarithm (base 10) of the fold-change enrichment of the TF binding sites in tumour-specific open chromatin with –1 times the logarithm (base 10) of the A similar approach was used to find TFs with enrichment of binding sites in tumour-specific closed chromatin and systematic gene expression silencing in tumour samples relative to normal prostate tissues.https://portals.broadinstitute.org/achilles). Prostate-specific lethality was tested by using a t test to compare the selection bias z-score in prostate cancer cell lines with the z-scores from all non-prostate cancer cell lines.Gene-level short hairpin (shRNA) selection biases in 216 cancer cell lines were downloaded from the Project Achilles portal  are very similar for the tumour-specific open chromatin windows and the remaining windows  100-kb windows sharing the same compartment call in both cancerous and normal tissue. The profiles made by the numeric values reflecting compartment open-ness were very highly correlated, with Pearson correlation coefficient 0.753. Furthermore, when we exclude 203 windows with a low confidence of compartment assignment in either tissue type  set of aberrantly compartmentalized genomic windows were identified. Annotated pathway terms from Consensus Path DB (CPDB)  were tes2 fold changes, chi-squared test p values and adjusted p values for all ChIP-seq studies, for both tumour-specific open chromatin and tumour-specific closed chromatin, is provided in Additional file Hypothesizing that TFs critical to the malignant state of PRAD would have their DNA binding sites residing specifically in regions of aberrant chromatin compartmentalization, we used genome-wide TF binding profiles to identify likely drivers of the malignant characteristics of these tumours. This was achieved through evaluating the expected number of peaks from each ChIP-seq study lying in tumour-specific open chromatin windows and the expected number lying in tumour-specific closed chromatin windows. The ratio between observed and expected numbers was used to compute a fold enrichment for systematic co-localization of TF DNA binding sites to aberrantly compartmentalized chromatin in PRAD. The distribution of log fold changes is shown in Fig. n = 251) of tumour tissue samples for the two groups to compare. Firstly, the closed-ness scores inferred from each tumour subset were both markedly more correlated to the closed-ness scores inferred from the full tumour set than from the normal prostate tissue set (0.99 (tumour) vs 0.78  for the first subset, and 0.99 (tumour) vs 0.75  for the second). Second, to the two tumour subsets’ compartment scores we applied the approach previously used to identify 100-kb genomic regions with a clear difference in compartmentalization between two sets of compartment scores. This approach yielded 231 regions specifically open in one tumour subset vs the other, where the same threshold yielded 1582 regions specifically open in the tumours vs normal tissue. Of these, only 2 regions were shared across both analyses, which strongly implies that the genomic regions we have called tumour-specific open chromatin are not an artefact of our analytical approach and do indeed reflect the state of prostate tumour compartmentalization relative to normal prostate tissue.To further evaluate the specificity of the TF binding site enrichment to tumour-specific open chromatin windows, we repeated this analysis with different selections of windows of interest. Varying the cutoff for filtering selected windows with low confidence of compartment assignment, and including the windows that were given the same compartment assignment in both tumour and normal tissues, we recomputed the fold enrichment for TF binding sites lying in the selected windows. A heatmap illustrating pairwise Spearman correlation coefficients between the profile of fold enrichment across the ChIP-seq studies for each selection of windows of interest is provided in Additional file p < 2 × 10–16), which implies that an enrichment of a TF’s binding sites in tumour-specific open chromatin regions generally coincides with a depletion of that TF’s binding sites in tumour-specific closed chromatin.To further test that the enrichments reflect properties of these specific sets of genomic regions, for each TF we evaluated the relationship between the log fold enrichment to tumour-specific open chromatin and the log fold enrichment to tumour-specific closed chromatin. The Spearman correlation coefficient across all TF studies was –0.524 ; these are presented in Additional file 2 enrichment towards tumour-specific chromatin and their –log10p value representing degree of enrichment towards tumour overexpression of downstream target genes, we find a reassuring correlation . These values are shown in Fig. 10p values using a range of cutoffs . The resulting profiles of per-TF enrichment scores were compared by computing the Pearson correlation coefficient for each pair of cutoffs. That the smallest pairwise correlation coefficient was greater than 0.99 strongly suggests that the degree of PRAD-specific overexpression we have calculated is robust to the particular cutoff for assigning target genes to TFs.If a transcription factor were to drive a malignant phenotype through activation or repression of its downstream targets, one would expect these targets to have systematically altered levels of expression in tumours relative to normal tissue. In order to test this hypothesis, we used corresponding expression microarray data from the same cohort of TCGA samples as were profiled with DNA methylation microarrays and from which we inferred the chromatin compartmentalization calls. Using p > 1 × 10–4. Excluding RNAPolII (which would most likely just reflect actively transcribed genes in the corresponding ENCODE cell line), we find KAT2A, MYC, SIN3A, HEY1, SP2, MAX, YY1, ATF3, NRF1, BCL3, THAP1, MXI1, GABP and ETS1. These represent our top candidates for TFs driving aberrant gene expression in PRAD tumours. Looking back at the TCGA gene expression microarray data, we can see if any of the predicted driver TFs themselves show aberrant expression in the tumours, providing an obvious mechanism for the observed overexpression of their downstream targets. A volcano plot showing differential expression of these candidates in the context of all genes is presented in Fig. We predict that these TFs have a key role to play in the pathogenesis of PRAD and as such merit further examination. To this end we looked at TFs for which ChIP-seq studies showed >1.5-fold enrichment to aberrantly open chromatin and systematic target gene overexpression with t test p = 0.06) in terms of incorporation into prostate cancer cell lines relative to all other cancer cell lines in the Achilles high-throughput screen [This set of putative drivers of aberrant transcription in PRAD tumours contains a number of known drivers of malignancy, either through hyperactivation or loss. Gain-of-function drivers include MYC , ETS1 2, GABP 2, YY1 2626 and NRt screen .The approach taken in this study utilizes integration of a publicly available dataset of matched DNA methylation and gene expression profiles, together with a compendium of DNA-binding profiles, to identify transcriptional drivers of disease. To our knowledge, this is the first time that inference of spatial organization of chromatin has been used in such a way. This study therefore provides an example from which applications to other clinically relevant phenotypes could be undertaken, highlighting potentially therapeutically targetable pathways. To this end, we acknowledge that direct pharmacological targeting of TFs has historically been challenging . We therThe genomic regions of interest with tumour-specific open chromatin were identified from primary tissue samples; therefore, differences in the infiltration of different cell types across each of the two primary tissue cohorts could leave a signature in the correlations in the levels of CpG methylation, on which the compartment calls are based. As the potentially confounding cell types and their methylation profiles at the CpG sites included in the analysis (which excludes those in promoter CpG islands) are unknown, it is impossible at this stage to separate correlations due to varying levels of infiltrating cell types from the correlations that reflect the chromatin compartments. Given that our analysis of DNase-seq data shows that the compartment calls we have used for the work presented here do indeed reflect chromatin accessibility and associated histone modifications in a prostate cancer cell line, we believe that any effect of cell type composition in the primary tissues is not sufficient to detract from the assumed biological significance of the compartment calls.We have assumed that TFs with clear evidence for preferential binding of DNA at regions of the genome undergoing spatial reorganization in a disease state are likely to be important for driving, or at least maintaining, that state. While it is out of the scope of this study to carry out experimental work needed to obtain direct evidence of the role of the candidate TFs highlighted through our application in prostate cancer, it is encouraging to have found considerable evidence in the literature. It is noticeable that a number of the candidates identified in our application to PRAD are linked to the oncogene MYC: notably MXI1, MAX and SIN3A. MXI1 forms a heterodimer with MAX which sequesters MAX away from MYC . SIN3A dIt would also require further experimental work to determine whether the identified TFs were behaving as ‘pioneer factors’  and actiIn this study we have shown how DNA methylation and gene expression datasets can be used in conjunction with ENCODE’s collection of DNA binding profiles from human TFs to find likely transcriptional drivers of a disease state. We have highlighted known and novel drivers of prostate adenocarcinoma, suggesting further investigation into the role of KAT2A and TRIM28 in carcinogenesis. Through this application we have demonstrated that, given the ready availability of such datasets, our approach represents a powerful technique for understanding the complex transcriptional dysregulation underlying carcinogenesis and identifying pathways of inquiry for novel therapeutic targets in cancer.Additional file 1:Table of open/closed compartment calls for PRAD tumours in 100-kb genomic windows. (TXT 1267 kb)Additional file 2:Table of open/closed compartment calls for normal prostate tissue in 100-kb genomic windows. (TXT 1267 kb)Additional file 3:Bar chart showing distribution of copy-number calls across PRAD tumour cohort for tumour-specific open chromatin genomic windows and for all other windows. (PNG 45 kb)Additional file 4:Ratios of observed/expected numbers of aberrantly compartmentalized windows for each chromosome. (TXT 532 bytes)Additional file 5:List of pathways found to be significantly enriched in regions of tumour-specific open chromatin. (TXT 468 kb)Additional file 6:2 fold changes, chi-squared test p values and adjusted p values for all ChIP-seq studies, for both tumour-specific open chromatin and tumour-specific closed chromatin. (TXT 50 kb)Table of logAdditional file 7:Heatmap illustrating correlation coefficients for per-TF profiles of enrichment to tumour-specific open chromatin, across a range of thresholds for excluding windows with low confidence of compartment assignment. (PNG 163 kb)Additional file 8:Table of median differences in tumour-specific open chromatin enrichment log fold changes for sets of ChIP-seq studies profiling the same TFs in different cell lines, and different TFs in the same cell lines. (XLS 24 kb)Additional file 9:p values and adjusted p values for mapped TF targets from each ChIP-seq study, representing systematic over- or underexpression in PRAD tumour samples relative to normal prostate tissue. (TXT 69 kb)Table of geneSetTest


Rb1) is necessary for the maintenance of telomere integrity in osteoblastic cells. We now show that the compaction of telomeric chromatin and the appropriate histone modifications of telomeric DNA are both dependent upon Rb1-mediated transcription of the telomere-derived long non-coding RNA TERRA. Expression of TERRA was reduced in Rb1 haploinsufficient cells, and further decreased by shRNA-mediated reduction of residual Rb1 expression. Restoration of Rb1 levels through lentiviral transduction was sufficient to reestablish both transcription of TERRA and condensation of telomeric chromatin. The human chromosome 15q TERRA promoter contains predicted retinoblastoma control elements, and was able to confer Rb1-dependent transcription upon a promoterless reporter gene. Chromatin immunoprecipitation revealed preferential binding of phosphorylated over non-phosphorylated Rb1 at the TERRA promoter. As Rb1-deficient cells show increased genomic instability we suggest that this novel non-canonical action of Rb1 may contribute to the tumour suppressive actions of Rb1.The tumour suppressor gene ( Rb1 tumour suppressor gene contributes to both of these phenotypic features. Thus, germ-line mutation of RB1 increase the risk of radiation-induced osteosarcoma3Rb1 allele or deletion of an Rb1 allele in the osteoblastic lineage is sufficient to predispose mice to radiation-induced osteosarcomaRb1 dependent radiation-induced osteosarcoma show increased chromosome instability that is coupled with accelerated telomere shortening in dividing cellsOsteosarcoma are unusual amongst solid tumours in having a high rate of genomic instability and a propensity for developing at sites of prior radiation exposure1A number of proteins co-localize with telomeric DNA to create the shelterin complex. The correct assembly of shelterin is essential for the organization and stability of telomeric heterochromatic chromatin and the maintainance of telomere length6The long non-coding RNA TERRA (Telomere-Repeat-Containing-RNA) is an RNA polymerase II transcript from a genomic locus that extends distally from the subtelomeric region into the telomere89111014Rb1 indeed influences telomeric integrity through directly regulation of TERRA promoter Rb1-dependent modulation of TERRA transcript levels and that ultimately results in structuring of the telomere architecture.The Rb1-dependent telomeric stability, the interaction between RB1 and SUV39H1+/loxP or FVB-COL1A1-Cre-Tg × FVB Rb1+/+ mice as described previouslyOsteoblasts were grown from explants of long bone fragments from 2- to 4-week-old FVB-COL1A1-Cre-Tg × FVB Rb16 cells using the ChromaFlash Chromatin Extraction Kit (Epigenetek P2001-100). Protein-free “naked” DNA was isolated from 1.5 × 106 cells treated for 1 hour at 56 °C in lysis buffer .Chromatin was extracted from 1.5 × 102O, 25 μl Bal 31 buffer and 1.2 U of Bal 31 nuclease. Digestions were performed at 30 °C for the desired times, followed by inactivation at 65 °C and lysis in 100 μl of lysis buffer containing 50 μg/ml of proteinase K. The length of the protected telomeric repeats was quantified by real-time qPCR using the ΔΔCt method2 = B0 + B1x + B2x 2 (R2 ≥ 0.90). A chromatin protection factor (CPF) was calculated from the ratio of the Bal 31 digestion rates of chromatin and naked DNA.Telomere chromatin compaction was evaluated by determinining the rates of Bal 31 exonuclease, digestion of native and protein-free genomic DNA following a previously described protocol5 or 1 μM of the U6 oligonucleotide GAACTCGAGTTTGCGTGTCATCCTTGCGC respectively13Total RNA was extracted with the High Pure RNA Tissue kit (Roche diagnostics). RNA was treated with RNase-Free DNase (Qiagen) for 1 hour, cleaned and concentrated with RNA Clean & Concentrator™ (Zymo Research) with an additional in-column DNase treatment made prior to elution. Specific reverse transcription of TERRA and the U6 control RNA were performed using 10 μM of the TERRA specific oligonucleotide (CCCTAA)2, 10 mM PIPES pH 7, 0.5% Triton X-100) containing 10 mM Vanadyl Ribonuclease Complex (NEB). Cells were rinsed with PBS, fixed in 4% formaldehyde in 1× PBS (pH 7) for 10 minutes and rinsed in 70% ice-cold ethanol. Cells were dehydrated though an ice-cold ethanol series . Slides were air-dried and further dried at 37 °C for 5 minutes. Hybridization with the PNA TelC-Cy3 probe (PANAGEN) was performed with the manufacturer’s hybridization mixture 10 mM NaHPO4, 10 mM NaCl, 20 mM Tris with 50% formamide and containing 10 mM Vanadyl Ribonuclease Complex for 18 h at 37 °C. Slides were washed 2 × 5 minutes in 60% formamide in 2× SSc at 37ªC and 1 × 5 min in 2× SSc at 37 °C and 1 × 2 min in 2× SSc at room temperature. DNA was counterstained with 100 ng/ml DAPI in mounting media and covered with a glass cover. RNAse treatment was performed on a separate slide (without Vanadyl Ribonuclease Complex) to probe the RNA nature of the signal. Images were visualized with a Nikon Eclipse E800 epifluorescence microscope and acquired with a CCD camera .Telomeric RNA FISH was performed as previously describedRB1 expressing lentivirus (LV-RB1) and knock-down (LV_shRB1) have been previously described4The The chromosomal region encompassing the TERRA promoter was amplified from human DNA using PCR primers harboring flanking XhoI and HindIII sites . The Xho1/HindIII restricted PCR product was ligated into the promoterless pGL3 luciferase expression vector (Promega) created by XhoI and HindIII excision of the original SV40 promoter sequence. This resulted in a TERRA promoter-driven lucifierase reporter vector (vTERRA). A second construct, lacking the 3′ end of the TERRA promoter (vTERRA*) was tested. This truncated version of the TERRA promoter was generated from a chance polymerase misread and is missing the 3′ end of the original construct. This resulted in a truncated version missing the RCEs, located on the minus strand but retaining the three predicted RCEs in the positive strand. The truncated version did not maintain the predicted minimal promoter required for transcription activation.5 U2OS cells were seeded in 6 well plates and transiently transfected 24 hours after plating with 500 ng of plasmid DNA using the X-tremeGENE 9 DNA Transfection Reagent (Roche). To determine the effects of Rb1 on the promoter the Rb1-expression modifying plasmid constructs , as well as a β-Gal-expressing transfection control vector were transiently transfected along with the reporter construct in U2OS cells. Transfected cells were collected after 72 hours. Promoter activity was quantified using the firefly luciferase glow assay (Pierce Thermo Scientific) and the β-Galactosidase enzymatic assay (Promega), both performed following the manufacturer’s recommendations.For the assay of promoter activity we measured luciferase reporter expression and compared this to a transfected control β–Galactosidase reporter. Briefly, 7.5 × 102O and subjected to qPCR analysis using the telomeric primers previously described as well as primers flanking the candidate Retinoblastoma Control Element we identified at the 5′ end of the human TERRA promoter region in chromosome 15q homologous to mouse chromosome 18q (Forward: 5′CTGCAACACACGCCCCCC3′ and reverse: 3′TAGCATGTGTCTCTGCGCCT5′). Thermal cycling was performed using 1 cycle at 95 °C for 10 minutes, followed by 50 cycles of 95 °C for 15 seconds, 60 °C for 30 seconds and 72 °C for 45 seconds with a final extension at 72 °C for 2 minutes. ChIP antibodies used for immunoprecipitation were anti-H3K9Ac , anti-H4K16Ac , anti-H3K4ME3 , anti-H3K9ME3 , anti-H3K79ME2 , anti-H4K20ME3  as well as anti-Rb1  and anti-pRb1 S807/811 .Assays were performed using the Simple ChIP Enzymatic Chromatin IP Kit . Chromatin was fragmented by ultrasound , then incubated with the appropriate primary antibodies overnight at 4 °C. For the subsequent immunoprecipitation the samples were incubated for 2 hours at 4 °C with agarose-bound secondary antibodies, before being washed and separated by centrifugation. Antibody-bound DNA was eluted in HThe analysis of the transcriptional control sequences of the TERRA repeats was performed using the MatInspector and PromoterInspector and the library of general core promoter elements of the Genomatix Suite software 23Rb1+/+, Rb1Δ19+/ and LV-RB1-recovered Rb1Δ19+/ osteoblastic cells  cells (Rb1Δ19+/osteoblasts.Whilst the level of H3K4me3 modification of telomeric histone was unaffected by retinoblastoma status (p = 0.5016), the representation of both H3K9me3 and H3K9ac in the telomeric chromatin was significantly increased in haploinsufficient (9) cells . The incRb1 haploinsufficient cells , further reduced the endogenous TERRA levels. Conversely a lentiviral-mediated increase in Rb1 levels in the haploinsufficient cells resulted in an increase of the steady state levels of endogenous TERRA  named vTERRA and a chance PCR polymerase misread truncated version (317 bp) named vTERRA* . When inRB1 expression in U2OS cell using the shRB1 vector reduced transcription from the vTERRA luciferase reporter; conversely RB1 overexpression resulted in an increased reporter gene transcription  the removal of all three Retinoblastoma family members  also increased genomic instability, although paradoxically this was reported to be associated with telomeric elongationThe increase in telomere sensitivity to nuclease digestion that we now report in Rb1-haploinsufficien osteoblast cells occurs rapidly during passages, and can be equally rapidly restored by recovery of Rb1 expression. This could point to a system where improper telomeric chromatin architecture, drives the loss of telomere length. The telomeric decondensation observed in Rb1 deficiency is accompanied by a quantitative shift in the pattern of histone modifications at the telomeres  that is consistent with the observed relaxation of the chromatin. Interestingly, this pattern of histone alteration has been previously recognized as a landmark of malignant transformation. We now suggest that it is also an indicator of telomere-dependent genomic instability, which may well precede acquisition of malignancyWhilst the observed decrease in H4K20me3 and increase in Histone-3 acetylation are consistent with a reduced condensation of telomeric chromatin they do not explain the elongation of telomeres reported in MEFs deficient in all three Rb family members1437Overall, our results support the hypothesis that Rb1 regulates the condensed state of telomeres both genetically and epigenetically. This is brought about via Rb1-dependent transcription of the TERRA long non-coding RNA, thereby ensuring appropriate telomeric chromatin architecture. Activation of TERRA transcription has also been reported to be activated by local depletion of TRF2 The 434 bp region studied on human chromosome 15q is located immediately adjacent to the telomeric tract and contains the 232 bp in silico predicted.minimal promoter. This chromosomal location is similar to that of other subtelomere promoter areas previously reported, such as for chromosomes XpYp where the TSSs was found 250 bp upstream the telomeric tractet al.Nergadze We demonstrate that TERRA transcription is under the control of Rb1 but there is a formal possibility that this effect is restricted to the two chromosomes  studied. However the available evidence suggests a global TERRA reduction as the RNA-FISH experiments performed in this study showed an Rb1 expression-dependent reduction in TERRA foci. Nevertheless, as TERRA transcripts from other chromosomes become available in mice it will be interesting to determine if there is differential regulation.The co-precipitation of phospho-Rb1 and the TERRA promoter suggests that the cyclin-dependent kinase mediated phosphorylation of Rb1 may serve to cycle phospho-Rb1 from E2F complexes to the TERRA promoter. This would allow temporal coordination of the activation of E2F-dependent genes required for G1/S transit with the opening of the telomere chromatin for replication by TERRA. Intriguingly, human herpesviruses HSV1 have evolved the capacity to target both Rb1-E2FAs shown for other long non-coding RNA molecules, TERRA is able to form local DNA:RNA hybrids733Rb1 as a tumour suppressor in osteosarcoma will be exerted by both canonical Rb1 activity on cell cycle transit, and telomere homeostasis. This may be the mechanism by which germ line mutations of Rb1 so effectively predispose to cancer46We suggest that the role of How to cite this article: Gonzalez-Vasconcellos, I. et al. The Rb1 tumour suppressor gene modifies telomeric chromatin architecture by regulating TERRA expression. Sci. Rep.7, 42056; doi: 10.1038/srep42056 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.