These domains often contain ranges of enhancers displaying similar or related tissue specificity, suggesting that in some cases, such domains may act as coherent regulatory units, with a global on or off state. By using the HoxD gene cluster, which specifies the topology of the developing limbs via highly orchestrated regulation of gene expression, as a paradigm, we investigated how the arrangement of regulatory domains determines their activity and function.The spatial organization of the mammalian genome relies upon the formation of chromatin domains of various scales. At the level of gene regulation in Hoxd genes, regulated by flanking 3′ and 5′ TADs, respectively. We characterized the effect of large genomic rearrangements affecting these two TADs, including their fusion into a single chromatin domain. We show that, within a single hybrid TAD, the activation of both proximal and distal limb enhancers globally occurred as when both TADs are intact. However, the activity of the 3′ TAD in distal cells is generally increased in the fused TAD, when compared to wild type where it is silenced. Also, target gene activity in distal cells depends on whether or not these genes had previously responded to proximal enhancers, which determines the presence or absence of H3K27me3 marks. We also show that the polycomb repressive complex 2 is mainly recruited at the Hox gene cluster and can extend its coverage to far-cis regulatory sequences as long as confined to the neighboring TAD structure.Proximal and distal cells in the developing limb express different levels of We conclude that antagonistic limb proximal and distal enhancers can exert their specific effects when positioned into the same TAD and in the absence of their genuine target genes. We also conclude that removing these target genes reduced the coverage of a regulatory landscape by chromatin marks associated with silencing, which correlates with its prolonged activity in time.The online version of this article (10.1186/s12915-019-0677-x) contains supplementary material, which is available to authorized users. Attempts to understand the spatial organization of the genome in the nucleus have recently led to models accounting for the relationship between genome structure and gene regulation (see ). The deChromatin is organized in several levels of interactions, loops, and domains. At the level of gene regulation, topologically associating domains (TADs) –9 usuallCompartments contain chromatin domains labeled by various epigenetic marks. Inactive chromatin domains labeled by histone H3 lysine 27 trimethylation (H3K27me3), resulting from the presence of polycomb group protein complexes, have been associated either with compartment A  or with Distinct functional states associated with various chromatin structures are not as clear when TADs are considered. While several examples exist showing the functional coherence of multiple enhancer sequences present within one particular TAD –32, the HoxD gene cluster, a group of genes located at the intersection between two TADs displaying distinct functional specificities [Hoxd8 to Hoxd11 in proximal limb bud cells. Subsequently, enhancers in the centromeric TAD (5′-TAD) control the Hoxd9 to Hoxd13 genes in distal limb bud cells [Hoxd11 and relying upon a collection of bound CTCF sites. Genetic analyses in vivo revealed that this boundary was very resilient and that even a full deletion of the gene cluster was unable to merge both TADs into one single domain, likely due to a few remaining occupied CTCF sites [A useful experimental paradigm to address this question is the mammalian ficities . During ud cells . These dCF sites .Hoxd genes are transcribed demonstrates that these two TADs are functionally exclusive from one another, i.e., the concomitant function of enhancers belonging to the two domains has not been observed thus far. This is due in part to the fact that the main target gene responding to 5′-TAD enhancers is Hoxd13, whose product, along with that of Hoxa13, has a negative effect over 3′-TAD enhancers through direct binding as observed in ChIP-seq experiments [Hoxd1 to Hoxd8 genes (they are no longer transcribed) but also large DNA intervals within the 3′-TAD reflecting the off state of this regulatory landscape and re-enforcing the idea that it may behave as a coherent regulatory unit.The analysis of different developmental contexts where eriments , 35. Theeriments . TherefoHoxD cluster as well as other boundary elements. After merging, this fused-TAD contained enhancers that do not normally function in the same cellular context. We asked whether these various enhancers would keep their initial functional specificities or, alternatively, if they would all be active or repressed concomitantly, as a result of this new topological proximity. In addition, we used a set of engineered inversions, which disconnect the target Hoxd genes from their TADs to evaluate the functional and epigenetic behavior of these regulatory sequences in the absence of their target genes.In this study, we challenged this hypothesis by investigating the effects of combining the two TADs into a single domain (a fused-TAD), after deletion of a large piece of DNA containing the HoxD cluster d9lac-mutant mouse stock (hereafter del(1-13)d9lac), which contains a deletion including the HoxD cluster [Hoxd9lac reporter transgene while the Evx2 and Lnpk genes remained present. In the absence of the HoxD cluster, the 5′-TAD and 3′-TAD were still observed as independent structures despite a substantial shortening of the distance separating them d9lac (hereafter del(attP-Rel5)d9lac) Hi-C datasets from mutant limbs lacking ca. 350 kb of DNA including the HoxD cluster plus flanking regions d9lac datasets were considered d9lac were limited to those domains adjacent to the cluster, we decided to investigate the impact on the activity of these regulatory domains upon the aforementioned deletion or using inversions where the HoxD cluster was disconnected either from the 3′-TAD or from the 5′-TAD  on E11.5 fetuses, using a LacZ RNA probe and could identify both the distal and proximal limb domains in the two del(attP-Rel5)d9lac and del(1-13)d9lac lines, though with subtle variations in their relative strengths d9lac allele), the functional partition of proximal and distal enhancers occurred in a close-to-normal manner, with a clear separation between the two expression domains. While the distal domain overlapped well with the wild-type HoxD distal limb pattern (see Hoxd10 and Hoxd11 wild-type WISH for a comparison), the proximal domain was somewhat different in shape and position from the wild-type HoxD pattern  and del(attP-Rel5)d9lac-mutant limbs at E12.5. In control proximal cells, transcripts were expectedly detected for Hoxd genes, for the flanking Lnpk and Mtx2 genes as well as for the Hog and Tog lncRNAs, two non-coding RNAs localized within the 3′-TAD and normally responding to enhancers located in this domain [Hog, Tog, and Island3) as proxies to evaluate the activity of their surrounding proximal versus distal enhancers in the two deletion alleles that removed all target Hoxd genes.In order to have a more precise account of these local modifications in transcriptional responses following the fusion of the two TADs, we carried out RNA-seq for both proximal and distal cell populations in both control d9lac-mutant limb cells, the Hog and Tog RNA levels substantially increased  while at the same time, the mRNA levels corresponding to the Mtx2 and Atf2 housekeeping genes remained approximately the same  d9lac-mutant limb cells, the level of Island3 eRNA decreased in the deleted configuration  and by WISH d9lac, only Dbx2 and the 1810046K07Rik RNA appeared significantly reduced in the DESeq2 comparison  on the other end of the regulatory domain d9lac-mutant fetuses. In proximal cells, the distribution of H3K27ac marks in the mutant material was as in control (wild-type) cells .To confirm these observations, we looked at the acetylation of H3K27, a histone modification that positively correlates with transcriptional activity, and compared proximal and distal E12.5 limb bud cells derived from both control and del(attP-Rel5)d9lac-mutant distal cells, an increase in H3K27ac was scored at region CS38-41 d9lac-mutant limb buds were in agreement with the distributions of both the H3K27ac marks and the transcripts. In proximal mutant cells, the profile was globally similar to that seen in control cells showing no salient difference along the remaining part of the former 5′-TAD , whereas a 22% decrease was scored over the remnant of the 3′-TAD . This decrease was mostly centered on region CS38-41, which showed a 51% decrease in the mutant  whereas they were found mildly yet not significantly enriched all over the remaining 5′-TAD region containing the regulatory islands   are generally associated with lack of gene expression and usually recruited to the CpG islands close to the transcriptionally active regions , 41, 42.HoxD cluster itself, the distribution of both EZH2 and RING1B nicely matched the coverage by H3K27me3 marks d9lac-mutant proximal cells could result from the mere absence of the HoxD gene cluster. To this aim, we used the engineered HoxDinv(attP-Itga6) inversion (hereafter inv(attP-Itga6) where the HoxD cluster was disconnected from the 3′-TAD and displaced circa 3 Mb away while preserving both its integrity and its association with the 5′-TAD [Considering that H3K27me3 covered both e 5′-TAD   inverted allele by performing a 4C-seq analysis in mutant and control distal limb cells, with Hoxd4 and CS38 as viewpoints  allele (hereafter inv(Nsi-Itga6) [HoxD cluster remains in place yet the 5′-TAD is inverted towards the same Itga6 breakpoint  inversion allele, the enrichment of H3K27me3 over the 3′-TAD remained unchanged either in distal cells , or in proximal cells , as was the case for the inv(attP-Itga6) allele d9lac allele suggest that the presence of Hoxd genes was necessary to achieve a full spread of H3K27me3 marks over the 3′-TAD, up to 800 kb in far-cis.In this inverted configuration, the global amount of H3K27me3 marks deposited over the 3′-TAD was substantially lower when compared to the control cells  , the Hoxint Fig. f. TherefHoxD cluster. In control distal cells, the distribution of H3K27me3 marks was enriched selectively over the 3′-TAD, terminating abruptly at its TAD boundary with no further telomeric spreading. In mutant del(attP-Rel5)d9lac distal cells, despite the large reduction of H3K27me3 signals, the remaining coverage was also restricted up to the new telomeric boundary of the fused-TAD . In all cases, though to a different extent, the TAD structure appeared to determine the extent of H3K27me3 spreading.Of note, this effect was restricted to the 3′-TAD, a conclusion reached after zooming out and looking at a 10-Mb interval surrounding the inv(attP-Itga6) allele, the 3′-TAD proximal enhancers were disconnected from their target Hoxd3 to Hoxd11 genes, similar to a previous case when a deletion of 3′-TAD was used [Hoxd9 and Hoxd11 mRNAs were also reduced in distal cells (see digits II and V), where these genes are under the control of 5′-TAD enhancers . UnexpeattP-Itga allele, f 3′-TAD .Fig. 6HoHoxD cluster in the inv(attP-Itga6) allele. In proximal cells, we found a high and homogeneous coverage of this histone modification, from Hoxd1 up to Evx2, unlike in the control allele where the DNA interval between Hoxd8 and Hoxd11 was transcriptionally active and hence depleted from this mark , where these genes are normally expressed in proximal tissue d9lac deletion, in the almost complete absence of CpG islands in and around the HoxD cluster, the enrichment by H3K27me3 marks in the 3′-TAD was severely reduced in distal cells, indicating that indeed the recruitment of PRC2 complexes over the HoxD cluster was mandatory to start covering the telomeric regulatory landscape by H3K27me3 marks, concomitantly to its functional inactivation. Some H3K27me3 coverage was nevertheless detected in the 5′-TAD and more substantially in the 3′-TAD, perhaps due to the presence of both the Hoxd9/lacZ reporter transgene and the Hog and Tog transcription start sites.Our results also provide some indications as to how PRC silencing propagates nce see , 52). Wi. Wiin-cid . Inr manner . In the HoxD cluster itself, i.e., in a region that is not particularly enriched in PRC2, exactly matched the extent of the 3′-TAD containing those Hoxd genes inactivated in distal cells and hence heavily covered by PRC2, PRC1, and H3K27me3. Such an effect was not scored in any other region in the 10 Mb surrounding the HoxD locus. This result suggests that the global inactivation of the 3′-TAD regulation in distal cells [Hoxd genes switched off in these distal cells and included into this TAD.The coverage by H3K27me3 marks in control distal cells outside the al cells  is accomal cells , 55). ThHoxD cluster is active and hence Hoxd9, Hoxd10, and Hoxd11 are devoid of H3K27me3 marks, whereas Hoxd12 and Hoxd13, which are located on the other side of the TAD boundary are silent and thus covered by H3K27me3 marks [During the replication of H3K27me3-labeled DNA sequences, daughter cells inherit this histone modification from their parental cell , 56, 57.e3 marks .Hoxd13 and Hoxd12, the major targets of 5′-TAD enhancers, which are transcribed at high levels. Hoxd11 and Hoxd9, which are devoid of H3K27me3 marks also become transcribed in distal cells, even though their genuine function in these cells has not been unequivocally demonstrated [inv(attP-Itga6) proximal mutant cells, the entire HoxD cluster is heavily covered by H3K27me3 marks since all Hoxd genes are silenced. When these mutant distal cells start to implement the 5′-TAD regulation, the H3K27me3 marks covering Hoxd13 and Hoxd12 are removed with the same kinetics as in wild-type distal cells, due to a comparable transcriptional context. However, Hoxd11 and Hoxd10 transcription onset is severely delayed when compared to control distal cells, as these genes were inherited in a silenced rather than active state, covered by H3K27me3 marks [Hoxd13 and Hoxd12 likely lead to a progressive removal of PRC silencing and a weak and delayed activation of both Hoxd11 and Hoxd10 in distal cells. This observation illustrates both the capacity for cells to memorize their coverage in H3K27me3 marks in a physiological context and the labile aspect of polycomb silencing, which can be efficiently removed through a strong transcriptional activation.When these cells start to implement the 5′-TAD distal regulation, H3K27me3 marks are erased from both nstrated . In the e3 marks . In thisHoxD cluster, were not dramatically affected neither in their activation nor in their specificities, when their target genes were deleted and the two TADs merged into a single chromatin interaction domain. However, in the fused TAD, the proximal regulation seems to take the lead over the distal regulation. Secondly, these results suggest a mechanism whereby the silencing of remote enhancers is accompanied by a far-cis spreading of polycomb group proteins after being recruited for the most part at the HoxD cluster itself. Finally, we conclude that active genes are more readily accessible to a subsequent enhancer regulation when compared to silenced genes, illustrating the potential importance of polycomb-associated chromatin marks in the proper timing of gene activation during development.From this study, we conclude that proximal and distal limb enhancers, which are normally segregated between the two TADs flanking the Genetically modified mice were kept on a (Bl6XCBA) background and crossed in heterozygosis. Distal and proximal forelimb tissues were dissected and processed from E12.5 mouse embryos. All mutant mice used in this study and their genotyping strategies have been previously described in , 37, 40.HoxDdel(1-13)d9lac and HoxDdel(attP-Rel5)d9lac were obtained from [https://vre.multiscalegenomics.eu/home/) [cis valid pairs on chr2 [C-scores were inverted when they began with positive values. All bedgraphs were then loaded in the UCSC browser.Hi-C original datasets from wild-type ned from  (GEO accned from  in chr2:u/home/) . Region u/home/) . Briefly on chr2  of the wp value below 0.05 were considered as significant ([HoxDdel(attP-Rel5)d9lac and their associated control samples, three biological replicates were used for each genotype and tissue. For plotting distal RNA-seq comparisons between wild type and HoxDdel(attP-Rel5)d9lac  RNA-seq, only one sample was used per tissue and genotype. Track profiles show the mean of the coverage of uniquely mapped reads normalized to the number of uniquely mapped reads. They were obtained with the UCSC browser. For qPCR, purified RNA was retrotranscribed with Promega GoScript Reverse Transcriptase (Promega). Custom SYBR probes were used for quantitative real-time PCR (qPCR) in a QuantStudio 5384-well block machine. Island3 primers were forward: TTCCATCACAGGAGAGTCGTTG and reverse: AGGTGGGAACATGGACTGAAAG. All other primers were described in [t test statistical analyses showed p value < 0.05.Limb tissue was dissected, placed in RNAlater (Invitrogen), and directly frozen at − 80 °C until further processing. After genotyping, RNA was extracted from individual samples using RNAeasy Micro Kit (QIAGEN). Libraries were prepared from 100 ng of total RNA using the TruSeq Stranded mRNA protocol and sequenced on a HiSeq 2500 machine . Sequencing data were treated using the facilities of the Scientific IT and Application Support Center of EPFL. The gtf file used for STAR and cufflinks, based on Ensembl version 94 annotations, is available on figshare . Adapterificant . The samples were then washed 3 times with working Washing Solution  and then snap-frozen in liquid nitrogen and stored at − 80 °C until further processing. After genotyping, the samples were pooled according to the required cell number. The total amount of tissue used for each line was different due to the size variations of the limb buds. Limb tissues were disrupted with a polytron device, lysed in RIPA buffer or Prep Buffer , and sonicated in Diagenode Bioruptor Pico. All H3K27ac ChIP experiments were processed as ChIP-seqs using the reagents from ChIP-IT High Sensitivity Kit (Active Motif). IPs were performed in parallel technical duplicates with 11 to 14 μg of chromatin on each. Antibody incubation was performed overnight on a final volume of 1.5–2 ml dilution buffer , including 2 μl of H3K27ac antibody (Diagenode C15410196) at 4 °C on a rotating platform. Agarose beads were added for 3 to 4 h at 4 °C. Washes were performed on column, and DNA purification was carried out by phenol-chloroform extraction. The technical replicates were merged and yielded 1.5 to 2 ng of chromatin, which were used to generate DNA libraries using the TruSeq ChIP library preparation kit. The number of biological replicates used for H3K27ac ChIP experiments is shown in the figure. RING1B ChIP experiments were processed as for ChIP-seq using 4 μl of RING1B antibody (Active Motif 39664) and following the protocol described in . Three a2, 10% dimethylformamide) and 1 μl of Tn5 transposase  and transferred to PCR tubes, which were then incubated at 37 °C for 5 min in a thermocycler. The samples were then resuspended and washed twice in 1 ml of RIPA-LS and twice in 1 ml TE buffer . The beads were magnetized, and DNA was eluted in ChIP elution buffer  with 2 μl of proteinase K (20 mg/ml stock) and then incubated for 1 h at 55 °C and 6 h to overnight at 65 °C. After de-crosslinking, the supernatant was recovered and the beads were resuspended again in 19 μl ChIP elution buffer with 1 μl of proteinase K and left 1 h at 55 °C. The two supernatants were combined and purified with MinElute kit (Qiagen) in 22 μl of EB buffer. Relative quantitation was performed using SYBR Green (as in [All H3K27me3 and EZH2 ChIP were performed following the ChIPmentation protocol . Around http://broadinstitute.github.io/picard/ version 2.18.14) [HoxDinv(attP-Itga6), and HoxDinv(Nsi-Itga6) alone d9lac was included in the comparisons .Analyses were performed using the facilities of the Scientific IT and Application Support Center of EPFL. Sequences were filtered, and adapters were removed using cutadapt (v1.16)  with par2.18.14)  using th2.18.14) . For theone Fig.  and chr2Hoxd4, Hoxd8, Hoxd9, Hoxd11, Hoxd13, and Evx2 WISH were performed following the protocol described in [Hoxd4, Hoxd8, Hoxd9, Hoxd11, Hoxd13, and Evx2 probes were as in [Island3, ribed in . The DNAribed in . Hoxd4, re as in .Additional file 1:HoxD locus in del(1-13)d9lac-mutant limb buds. (A) Hi-C map showing the presence of both TADs on either side of the HoxD locus in del(1-13)d9lac proximal limb cells and its associated genes (gray boxes) and regulatory regions (black and red boxes)  TADkit-derived 3D representation of Hi-C datasets [del(1-13)d9lac-mutant mice. The CS38-41 region is shown as a red disk in the 3D models to be used as a reference point. In this deletion allele, both TADs are still visible unlike in the larger del(attP-Rel5)d9lac deletion shown in Fig. D) A/B compartment distribution along chromosome 2. C-scores were calculated from Wt and del(attP-Rel5)d9lac E12.5 distal and proximal limb Hi-C data. Compartment A is represented as positive values (red) and compartment B as negative values (blue). Gene density is shown in the bottom panel and the HoxD locus is indicated as a blue bar. (PDF 814 kb)3D-representation of the datasets  obtainedus in del-13d9lac-Additional file 2:HoxD associated transcripts. (A) WISH of lacZ mRNA in del(attP-Rel5)d9lac and del(1–13)d9lac E11.5 forelimbs (center) and whole embryos (left). The proximal domain is shown by an arrowhead. Hoxd10 and Hoxd11 WISH of E11.5 wild-type forelimbs are shown on the right for comparison of their expression domains. (B) WISH of Island3 eRNAs in Wt and del(attP-Rel5)d9lac E12.5 embryos where the antisense probe was used (left) showing the specificity on the digital region. On the right, a probe control shows the lack of staining with the Island3 sense probe.  Volcano plots of all genes analyzed by RNA-seq in proximal (C) and distal (D) limb tissues comparing del(attP-Rel5)d9lac expression values to the control. All the genes located inside or in the vicinity of the 5′-TAD and the 3′-TAD are marked in red. Blue dots represent differentially expressed genes  that are located outside these regions. Hoxd9 and Gm28793 (a short antisense mRNA) are significantly expressed due to their presence inside the Hoxd9/LacZ transgene. (E). RNA-seq-normalized read counts of wild-type versus del(attP-Rel5)d9lac distal limb tissue. The ten genes were selected according to the highest fold induction values obtained when wild-type distal and proximal tissues were compared. Statistical significance was assessed as adjusted p values of the DESeq2 analysis. (PDF 14200 kb)Expression analysis around the Additional file 3:HoxD from its 3′-TAD regulatory landscape. H3K27me3 ChIP profiles from proximal limb bud cells derived from either wild type, inv(attP-Itga6), or inv(Nsi-Itga6) specimens. n indicates the number of replicates for each track. Below each mutant dataset, a comparison of mutant versus control is shown. A red asterisk in the control track indicates an artifactual signal at the position of island-3. (PDF 537 kb)H3K27me3 distribution after disconnecting the Additional file 4:A) H3K27me3 coverage outside the HoxD locus in distal limb bud cells from either control (Wt) or del(attP-Rel5)d9lac specimens. A corresponding Hi-C map is shown on top spanning ca. 10 Mb and centered around the HoxD cluster (blue box), with the related TAD structures (chr2:69600001-79440000). The flanking 5′ and 3′-TAD TADs are indicated. H3K27me3 ChIP profiles in control cells show a global coverage outside the HoxD cluster precisely restricted to the 3′-TAD. In del(attP-Rel5)d9lac-mutant distal limb cells, the enrichment is much weaker. Below is the difference in the ChIP datasets comparing mutant versus control signals. The red asterisks point to an artifactual signal. (B) Quantification of H3K27me3 ChIP signal of wild type, del(attP-Rel5)d9lac, inv(attP-Itga6), and inv(Nsi-Itga6) in distal (left) or proximal (right) forelimb cells. The plotted values are computed from the regions depicted in (A) as dashed boxes. (PDF 2145 kb) and proximal (bottom two tracks) limb bud cells, either in control (Wt) or in inv(Nsi-Itga6) mutant specimen. Below are shown the difference profiles. The increase of signal in Hoxd11 represents reads coming from the Hoxd11lac transgene included in the inversion allele (represented by a shaded gray box). (PDF 429 kb)H3K27me3 signal over the


Drosophila development. Specifically we have focused on the expression of decapentaplegic, wingless, stripe and patched. The transcription of these genes is believed to be controlled by enhancer modules able to interpret opposing gradients of the activator and repressor forms of the transcription factor Cubitus interruptus (Ci). This study is based on a thermodynamic approach, which provides expression rates for these genes. These expression rates are controlled by transcription factors which are competing and cooperating for common binding sites. We have made mathematical representations of the different expression rates which depend on multiple factors and variables. The expressions obtained with the model have been refined to produce simpler equivalent formulae which allow for their mathematical analysis. Thanks to this, we can evaluate the correlation between the different interactions involved in transcription and the biological features observed at tissular level. These mathematical models can be applied to other morphogenes to help understand the complex transcriptional logic of opposing activator and repressor gradients.This work provides theoretical tools to analyse the transcriptional effects of certain biochemical mechanisms (i.e. affinity and cooperativity) that have been proposed in previous literature to explain the proper spatial expression of Hedgehog target genes involved in  Drosophila melanogaster fly. In Drosophila’s wing imaginal disc the secretion of Hh from the Posterior compartment cells induces the expression of several target genes inside the cells in the Anterior compartment. Among them are decapentaplegic (dpp) and patched (ptc). Both give rise to the synthesis of their corresponding proteins, Dpp and Ptc, which are essential for the wing central domain development  and andtranss (dppD) , 8.We have to remark that the control of these Hh/Ci modules does not probably justify the absolute genetic expression of the target gene although they have been described to be essential for their proper genetic spatial patterns . Furtherdpp in regions of low signal. Secondly, it is possible that transcription factors that are already bound in some enhancers can modify the affinity of other binding elements. In this case, bound TFs may modify the free energy of a later binding reaction of either TF or RNAP. This process is generally termed cooperativity, however this can be positive or negative. If it facilitates the binding it is called  cooperativity and if it impedes it, is called anti-cooperativity. In wg and srn (h) in ). NevertIn order to discriminate between the mechanisms that could give rise to a differential spatial expression, in , 11 the The large amount of biochemical variables that are present in the system calls for mathematical models , 18 thatdpp, ptc, wg and sr. Among all the different frameworks deduced, we conclude that proper spatial expression of these genes is due to differences in affinities between their corresponding binding sites in combination with cooperativity between repressors (please refer to Section Results for more details). Our analysis confirms the results obtained in  and [CiR], will provide more or less gene expression than the basal. So, we define a threshold separating concentrations of both TFs that would produce net activated cells or net repressed cells using the BEWARE operators. Then, we can use the threshold between net activation/repression concentrations to determine the limit between the ranges of net activated or repressed cells. Once we have defined the ranges of activated cells we can predict how biochemical differences will affect them as well as the signal intensity. To do this analysis we need to assume that the opposing activator and repressor gradients are monotone and do not change over time  was also constructed. In this case, the range of net activated cells was wider than the range of net activated cells for (dppD-3xCiptc) and in consequence a broader, but attenuated, expression was observed for the single enhancer case than in the 3 high-affinity sites case. This comparison can be reproduced by using the BEWARE operators. It can be theoretically proved that the cooperativity between the TFs determines the effect of the binding sites reduction:In , a transIn the presence of total cooperativity or non-cooperativity between the TFs the NAC range would essentially remain unaltered although a reduction of signal intensity could be observed, that is, less repression/activation in the repressed/activated cells.dppD-3xCiptc would change to be net repressed for the gene dppD-1xCiptc.If the activators CiA only cooperate between them a reduction in the NAC range would be observed, so some net activated cells for dppD-3xCiptc and dppD-1xCiptc obtained in  and [R], i.e.,B is an empty regulatory region, a set of non occupied enhancers-promoter, the complexes BA, BR and BRNAP have concentration at equilibrium given byKRP, [A], [R] and [RNAP] are dissociation constants and concentrations of activators, repressors and RNA polymerase. So the quotients As a first step, we apply the ideas of the statistical thermodynamic method to a gene, BRA] = [BAR]. It is plausible to assume the same relation for later bindings, that is, j ≥ 2. In consequence of this sequential independence we denote the dissociation constants as KA and KR omitting the superscript. So, if all the TFs under consideration are non cooperative we easily deduce that the concentration at equilibrium, of a configuration with jA activators and jR repressors bound, isDrosophila’s wild type cis-regulatory elements involve a total number of 3 binding sites we are going to compare with experiments where these binding sites have been reduced to 1. Thus, we will consider in our model n ≥ 1 the number of TFs binding sites. In all cases, we have a restriction for the possible number of bound transcription factors. So, jA + jR ≤ n has to be verified, and in consequence j0 = n − jA − jR ≥ 0 denotes the number of free spaces in the configuration.We denote as non cooperative TFs, all those proteins whose enhancer affinity is not modified by any previously bound TFs, that is, they verify i, k = A, R, that is:c is a positive constant greater than 1 if proteins cooperate, and less than 1 if anti-cooperativity occurs. Since the only difference between cooperativity and anti-cooperativity is a threshold value for c, in the subsequent modelling we will refer to the constant c and not distinguish between both cases. If cooperativity occurs it would be necessary to know which TFs are affected by other TFs since the equilibrium concentration will depend on these relationships. In previous literature, total and partial cooperativity have recently been proposed to play an important role in the Hh/Shh target genes by means of the Ci/Gli TFs  − [R] into two parts that we can denominate activation region if c and n, depends on the TFs affinities through the ratio KR/KA, it increases with respect to a and decreases with respect to r (since r < 1). This justifies the behaviour of the net activated cellular ranges in the case of non/total cooperativity stated in We can see that in the case of Drosophila system. Hh secreted from the posterior into the anterior compartment of the wing imaginal disc results in opposing gradients of activator and repressor Ci. The A/P boundary is located at around 60% of the dorso-ventral (D/V) axis. The influence of Hh gradient can be appreciated in the middle of the anterior compartment, specifically the cells located in the region between the 30% and 60% on the D/V axis, approximately. In order to model these TFs concentration distributions we are going to assume that they do not change over time and both are monotonic along the tissue,x, the distance from the A/P boundary. See example in inset in Panel B of Drosophila development. It is well known that CiA concentrations depend on the Hh gradient secreted from the posterior compartment. Hence, we will consider that this concentration decrease with the distance from the A/P border, that is, [A](x) is decreasing. On the other hand, the levels of Ci transcripts are high at the positions of A compartment distal to the A/P boundary whereas are low at the positions proximal to the A/P boundary. Assuming the proportionality between transcription levels and protein concentrations this would imply that the total amount of Cix. Hence, the concentration of CiR must increase with the distance from the A/P border. A particular case of this situation is the conservation of the total amount of TFs proposed in  − [R] plane  , verifying A] < [A]th. For activated cells this would be [A] > [A]th. In consequence, they would express transcription rates lower/higher than the basal. Due to the monotonic nature of the TFs distributions, xth given byA]th the larger is the NAC. That is,We can take this information and by considering appropriate gradients of activators and repressors we can define the tissular regions of net activated and net repressed cells, which are, regions of cells expressing more or less than the basal expression level (see posed in  corresponcreasing6in terma) and represented in n or the cooperativity c and depends on the TFs affinities in terms of the ratio KR/KA. Thus, these regions do not change  requiere some simple monotonicity properties that have been checked with Lemmas C and D in 1), 2) and 3), have been proven to verify thatFreg which allow us to extrapolate these estimates to expression rates. These three results have been interpreted as a signal weakening. Biochemical differences 1), 2) and 3) can not modify the character of net activation/repression but are able to make signalling less efficient. That is, they do not change the NAC range but they cause less activation in the activated region and less repression in the repressed region (↓Sig). In consequence, we can say that in situations 1), 2) and 3) the expression rates will decrease in the net activated cellular range and increase in the repressed cells, which will attenuate the cellular expression range. See The rest of the assertions in 3) in Lemma D in In contrast, assertion A is a weaker transcriptional activator in gene1 than in gene2, exhibiting lower cooperativity between the activators and the RNA polymerase (ag1 < ag2), then expression of gene1 will be smaller than in gene2 becausegene1 than for gene2.If R is a weaker transcriptional repressor in gene1 than in gene2, exhibiting lower anti-cooperativity between the repressors and the RNA polymerase (rg2 < rg1 < 1), then expression rate of gene1 will be higher than gene2 expression becausegene1 than for gene2.If n = 3 and cA, cR ≥ 1, this threshold is determined by an unique increasing function f, verifyingR]/KR < f([A]/KA), and those which provoke net repression, when [R]/KR > f([A]/KA)) (see Section E in f). Note that the threshold of a BEWARE operator with partial cooperativity is not, in general, a straight line although it shows a linear asymptotic behaviour for large concentrations  in Cooperativity only between repressors, that is cA > 1 and cR = 1. The counterpart results in this other case shows that expression rates are increasing with cooperativity between activators since it increases activation effectivity (see Lemma F 1) in Cooperativity only between activators, that is 2b) and 2c) and represented in Panel D in These result have been summarised in f with the linear relation When both TFs cooperate simultaneously we have compared the thresholds given by functions If If h), the binding affinities, KA, KR as well as the activation/repression intensities. A detailed explanation can be found in Section E in In all other cases: An increase or decrease of the net activated cellular range can occur depending on the total amount of TFs considered  and 5c) can be verified easily from statement 3) Lemma F, in The assertions in S1 FileThis file contains all the mathematical details of the theoretical analysis. Furthermore, it contains the discussion of the results that can be deduced for the single gradient case.(PDF)Click here for additional data file.S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S4 Fig(PDF)Click here for additional data file.


POU5F1 gene and genes previously identified as being POU5F1 enhancer-interacting, namely, CDYL, TLE2, RARG, and MSX1 , in human pluripotent stem cells (hPSCs) and their early differentiated counterparts. As a control gene, RUNX1 was used, which is expressed during hematopoietic differentiation and not associated with pluripotency. To reveal how these long-range interactions between POU5F1 and the selected genes change with the onset of differentiation and upon RNAP II inhibition, we performed three-dimensional fluorescence in situ hybridization (3D-FISH) followed by computational simulation analysis. Our analysis showed that the numbers of long-range interactions between specific genes decrease during differentiation, suggesting that the transcription of monitored genes is associated with pluripotency. In addition, we showed that upon inhibition of RNAP II, long-range associations do not disintegrate and remain constant. We also analyzed the distance distributions of these genes in the context of their positions in the nucleus and revealed that they tend to have similar patterns resembling normal distribution. Furthermore, we compared data created in vitro and in silico to assess the biological relevance of our results.The eukaryotic nucleus is a highly complex structure that carries out multiple functions primarily needed for gene expression, and among them, transcription seems to be the most fundamental. Diverse approaches have demonstrated that transcription takes place at discrete sites known as transcription factories, wherein RNA polymerase II (RNAP II) is attached to the factory and immobilized while transcribing DNA. It has been proposed that transcription factories promote chromatin loop formation, creating long-range interactions in which relatively distant genes can be transcribed simultaneously. In this study, we examined long-range interactions between the  Human pluripotent stem cells (hPSCs), including both human embryonic stem cells (hESCs)  and humaIt has been shown that transcriptionally active genes associate with TFs, described as discrete nuclear sites of nascent RNA molecules wherein transcription components are concentrated –11. ThisChromatin loops are responsible for long-range interactions defined as crosstalk between enhancer elements and distally positioned genes, thus regulating the transcription of relatively distant genes –18. As hThe transcription of active genes in TF is carried out by RNAP II. Transcription itself is a multistep process, starting with the inactive unphosphorylated form of RNAP II binding to DNA. For transcription initiation, RNAP II phosphorylation at the Ser5 and Ser7 positions of the C-terminal domain (CTD) by cyclin-dependent kinase 7 (CDK7) is required. Elongation factor (P-TEFb) containing the CDK9 kinase subunit is mandatory to progress into the next stage of transcription; thus, inhibitors of the CDK9 kinase result in the inhibition of transcription elongation. Today, many RNAP inhibitors that target different stages of the transcription process are available . Many coPOU5F1) has a huge impact not only on pluripotency maintenance but also on differentiation by directing the cell fate toward a primitive endoderm and mesoderm [Recently, long-range interactions and their role in the pluripotency and differentiation of hPSCs have been evaluated . It has mesoderm . Using cmesoderm –31. ThesPOU5F1 that encodes the transcription factor Oct4. We performed three-dimensional fluorescence in situ hybridization (3D-FISH) analysis to reveal long-range interactions between POU5F1 and the genes CDYL, TLE2, RARG, and MSX1, previously identified as possible interacting partners [RUNX1, was chosen. This gene is believed to play a role in hematopoietic differentiation [In the present study, we focused on the pluripotency master gene partners . As a contiation . We sougβ inhibitor CHIR 99021 (4 μM)  for three consecutive days.The human ESCs employed in this study were derived from blastocyst-stage embryos obtained with the informed consent from the donors. A well-characterized hESC line , CCTL14 Escherichia coli carrying plasmids with sequences CTD-2534O14, RP11-624J6, RP11-346E12, RP11-268O21, RP11-1006L1, and RP11-620A17 were chosen from http://www.ncbi.nlm.nih.gov and acquired from Life Technologies BAC library  that is specifically used for the isolation of genomic DNA-free BAC DNA according to the manufacturer's instructions. The isolated BAC DNA was resuspended in TE buffer and quantified with the NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific). For BAC DNA precipitation, 2 μg of DNA was mixed with 6 μl of Cot DNA and 1.4 μl of DNA . The mixture was incubated at room temperature for 5 min, followed by the addition of 1.5 μl of 3 M acetic acid and 22 μl of cold 70% ethanol and incubation at -80°C for 30 min. After incubation, the samples were centrifuged at 12000 rpm at 4°C for 30 min, the supernatant was removed, and the pellet was allowed to air-dry. Precipitated BAC DNA was resuspended in 3 μl of PCR water and stored at -80°C.μg of template DNA was mixed with 4 μl of NICK translation mix and double-distilled water and incubated at 15°C for 90 min. The reaction was stopped by adding 1 μl of 0.5 M EDTA and heating at 65°C for 10 min. Prior to adding EDTA, the proper length of fragments was verified with 3 μl of NICK-translated DNA on a 1% agarose gel. DNA probes were aliquoted and stored at -80°C.NICK translation for BAC DNA was carried out using a mixture of DNA probes labeled with digoxigenin-11-dUTP DIG-NICK Translation Mix and biotin-16-dUTP Biotin-Nick Translation Mix (both purchased from Sigma-Aldrich) according to the manufacturer's instructions. Briefly, 1 μg/ml, Qiagen) at 37°C for 1 hour. After washing the cells again in 2× SSC and PBS, they were incubated in 0.1 N HCl, permeabilized with 0.2% saponin/PBS and 100 mM Tris-HCl, and briefly rinsed in 2× SSC. Cellular DNA was treated with a hybridization mixture (70% formamide/2× SSC) at 75°C for 5-6 min and dried in an ethanol series. After DNA probe denaturation (75°C for 7 min) and reannealing (37°C for 30 min), the probes were mixed with Hybrisol VII , applied to cells, sealed under coverslips with rubber cement, and allowed to hybridize overnight. After hybridization, the slides were washed in 50% formamide and 2× SSC at 45°C and then incubated with anti-digoxigenin-rhodamine Fab fragments and avidin fluorescein conjugate (both purchased from Sigma-Aldrich) for 1 h at 37°C. After rinsing the cells with 2× SSC/0.1% Tween, the coverslips were mounted in DAPI-containing Mowiol (Sigma-Aldrich).To perform 3D-FISH, hPSCs and their differentiated counterparts were cultured on coverslips, fixed with 4% paraformaldehyde (Sigma-Aldrich) for 10 min at room temperature (RT), washed in PBS (3× for 5 min), permeabilized with 0.5% Triton X-100 in PBS for 30 min, equilibrated in 2× SSC, and treated with RNase A , permeabilized with 0.1% Triton-X100 in PBS , and incubated with primary antibodies at 4°C overnight. The primary antibodies included goat polyclonal anti-Oct3/4 , rabbit monoclonal anti-Nanog , and rabbit anti-RNAP II Ser2 . The next day, incubations with secondary antibodies conjugated to Alexa Fluor 488 or Alexa Fluor 594  were carried out at RT for 1 hour. Coverslips were mounted in DAPI-containing Mowiol (Sigma-Aldrich). Microscopic analysis was performed using a Zeiss Axiovert 200M system .To determine the expression of cell surface antigens, we used flow cytometry. Briefly, cells were harvested using trypsin/EDTA, resuspended in PBS/0.5% BSA/2 mM EDTA, and incubated with fluorochrome-conjugated antibodies at 4°C for 10 min. The antibodies included SSEA-4  and Tra-1-60 and Tra-1-81 . For an isotope control, a mouse IgG3 antibody  was used. Samples were measured with a BD FACSCanto II flow cytometer . For data analysis, Flowing Software  was used.μm step interval. Thus, these images fully covered the 3D volume of the specimen, making the z resolution of the image slice sufficient for detecting two FISH-probed signal spots. The acquired image slices were saved in the red/green/blue (RGB) format. The 3D interphase nucleus was assembled from the volume of interest of the RGB image stack using the open-source software Acquiarium (https://cbia.fi.muni.cz/software/acquiarium.html).The specimen slides were imaged using a Zeiss Axiovert 200M system (Carl Zeiss) confocal microscope with a 40x oil objective lens. The imaged field of view (FOV) was acquired at a resolution of 1024 × 1024 pixels. A stack of 60 digital image slices was acquired with a 0.2 The simulated images were generated in a virtual microscope  using a POU5F1 and the selected genes in TFs formed in hPSCs, we used both hiPSCs and hESCs with typical undifferentiated morphology and expression of pluripotent markers , TLE2 (chromosome 19), RARG (chromosome 12), and MSX1 (chromosome 4). As a control, the RUNX1 gene (chromosome 21) was chosen, which is a transcription factor that regulates the differentiation of hematopoietic stem cells into mature blood cells [POU5F1 and CDYL are located on chromosome 6, which should naturally increase the percentage of close colocalizations. Interestingly, although these genes are positioned on the same chromosome, they can be separated by long distances , implying that this gene does not play a role in maintaining hPSC pluripotency , although they barely changed during different experimental conditions. Interestingly, only RUNX1 alleles displayed an increase in long-range interactions from 9.5% in pluripotent cells to 20.6% in their early differentiated counterparts  and the distance between allelic pairs of individual genes (ii). We demonstrated that long-range interactions between two of the four selected genes decreased upon the early differentiation onset, highlighting the role of these genes in pluripotency. In addition, we showed that once created, these long-range chromosome interactions remained stable and did not disintegrate upon RNAP II inhibition.Genomes are highly organized spatially within interphase nuclei. Although higher-order chromatin organization is increasingly linked to genome function and regulation of gene expression, this level of organization in hPSCs remains poorly explained. In our present study, we describe long-range interactions between the of hPSCs , 40–42. of hPSCs , 44. OurTo assess long-range interactions between the selected genes, we used 3D-FISH, a commonly used approach that allows direct visualization of the transcription and gene positions in single cells . Performμm was chosen. Although this distance may seem too long, an open form of transcriptionally active pluripotent chromatin is a property of a pluripotent nucleus. Moreover, it has been shown that enhancer-promotor communication requires chromatin looping [As a criterion for long-range interaction between two FISH signals, a distance less than or equal to 2  looping . Loops f looping , 48. Nev looping –52.Hi-C analysis, which reveals the genome at the megabase scale, has been used to partition the genome into two main compartments, named A and B , correspRUNX1. Long-range associations with POU5F1 gene loci increase from 8 to 18% during early differentiation, suggesting its role in this process. Indeed, RUNX1 is a member of the core-binding factor family of transcription factors and is indispensable for the establishment of definitive hematopoiesis in vertebrates. RUNX1 is one of the most frequently mutated genes in a variety of hematological malignancies [β inhibitor that drives hPSCs into becoming mesoderm [POU5F1 and RUNX1 increase upon this type of differentiation. In addition, when spatial distributions and distances higher than 10 μm were compared, we observed large shifts in POUF51-RUNX1 associations to opposite nuclear regions.In this study, we showed that long-range interactions between the selected genes in pluripotent nuclei changed with differentiation. One of the genes in which this alteration is the most striking is gnancies . Moreovemesoderm . We confPOU5F1 and CDYL associations, we report a decrease in long-range interactions from 38.51 to 30% during differentiation. Interestingly, we found that being positioned on the same chromosome does not always guarantee close proximity of genes, and on the contrary, many genes are located at long distances apart, indicating transcriptionally active and open states of chromatin in pluripotent nuclei. The role of this gene in pluripotency remains unclear, although it has been implicated in chromatin remodeling and linked to X-chromosome inactivation during early embryo development. As shown in mouse embryonic stem cell lines, for its association with Xi, CDYL requires the process of differentiation and the presence of H3K9me2 and H3K27me3, which both become chromosomally enriched [−/− mouse fibroblasts can be reprogrammed into iPSCs with decreased spontaneous neuronal differentiation [For enriched . As demontiation .POU5F1-TLE2 combination follows an interesting course during the shift from pluripotency to differentiation. When analyzing POU5F1-TLE2 long-range interactions, we observed a remarkable 10% drop in long-range interactions between these two genes during differentiation, suggesting a role of TLE2 in maintaining pluripotency and undifferentiated hPSC growth. In contrast, it has been shown that TLE2 regulates ventral telencephalon formation [In addition, the ormation . Among iormation . On the ormation .POU5F1-RARG long-range interactions, our study showed no significant modifications during the onset of differentiation, which is notably interesting. In fact, it has been shown previously that RARG can favorably enrich the former transcription factor cocktail  used for reprogramming somatic cells into hPSCs, making this process more efficient [With regard to fficient . This cofficient .POU5F1, exhibited by approximately 10% of pluripotent nuclei and 20% of differentiated nuclei (twofold higher). As previously demonstrated, Oct4 plays a dual role in pluripotency and differentiation [POU5F1 remains stacked in TFs during pluripotency and differentiation.One of the most interesting outcomes of our study on interchromosomal associations is the observation of pairing between individual alleles of ntiation , 63, 64.ntiation . We concCollectively, we can summarize that long-range interactions and gene regulation are in a firm, causal relationship. Pluripotent nuclei exhibit unique features that are modified due to chromatin remodeling upon the onset of differentiation. Based on our data, we propose that upon differentiation, long-range associations between specific pluripotent genes associated with pluripotency decrease. RNAP II inhibition seems to have no impact on these ongoing long-range interactions, suggesting that the assembly of transcription factories remains constant and stable. Sophisticated high-resolution approaches analyzing the interactomes of the entire cell populations provide the same evidence.POU5F1 gene and genes previously identified as being POU5F1 enhancer-interacting, namely, CDYL, TLE2, RARG, and MSX1 , in human pluripotent stem cells (hPSCs) and their early differentiated counterparts using 3D-FISH followed by computational simulation analysis. We sought to elucidate how these interactions change over time and upon RNAP II inhibition. Our analysis showed that long-range interactions with the CDYL, TLE2, and RUNX1 genes change during differentiation, suggesting that transcription of the monitored genes is associated with pluripotency. In addition, we show that upon inhibition of RNAP II, long-range associations do not disintegrate and remain constant. Furthermore, we show that the pairing of individual alleles of the selected genes is affected neither by differentiation nor by RNAP II inhibition. Another interesting outcome of our study is that the number of long-range interactions between POU5F1 individual alleles in early differentiated cells was doubled compared to that in pluripotent cells. Furthermore, distance distributions between POU5F1 and the selected genes display a similar pattern and do not change during differentiation or upon RNAP II inhibition. As a subsequent step, we computationally constructed artificial nuclei using preexisting real data and randomly loaded signals to compare data created in vitro and in silico and confirm the biological relevance of our results of long-range interactions between POU5F1 and the selected genes.In this study, we examined long-range interactions between the


RSOsPR10) induced by drought, salt, and wounding. RSOsPR10 expression is strongly induced by jasmonate (JA)/ethylene (ET), but suppressed by salicylic acid (SA). Here, we analyzed the promoter activity of RSOsPR10. Analyses of transgenic rice lines harboring different‐length promoter::β‐glucuronidase (GUS) constructs showed that the 3‐kb promoter region is indispensable for JA/ET induction, SA repression, and root‐specific expression. In the JA‐treated GUS3K‐promoter:: line, GUS activity was mainly observed at lateral root primordia. Transient expression in roots using a dual luciferase (LUC) assay with different‐length LUCpromoter:: constructs demonstrated that the novel transcription factor OsERF87 induced LUC3K‐promoter:: expression through binding to GCC‐cis elements. In contrast, the SA‐inducible OsWRKY76 transcription factor strongly repressed the JA‐inducible and OsERF87‐dependent expression of RSOsPR10. RSOsPR10 was expressed at lower levels in WRKY76Os‐overexpressing rice, but at higher levels in WRKY76Os‐knockout rice, compared with wild type. These results show that two transcription factors, OsERF87 and OsWRKY76, antagonistically regulate RSOsPR10 expression through binding to the same promoter. This mechanism represents a fine‐tuning system to sense the balance between JA/ET and SA signaling in plants under environmental stress.Plant roots play important roles in absorbing water and nutrients, and in tolerance against environmental stresses. Previously, we identified a rice root‐specific pathogenesis‐related protein ( The seedlings were grown under the following controlled environment conditions: 27°C, 12‐h light (65.4 μmol m−2 s−1) /12‐h dark cycle ) were germinated in the same conditions , W76‐UpAsc‐R1 (CTGGCGCGCCGCTCTGGAGCTCGAGTAATCA), W76‐DwF1 (ATGCTGTACAGAATTCAGAAGCTGCCCGAATTCTAGCTTC), and W76‐DwR1 (TTACGCGTTTGAATTTGTGGTCTTCATTGTACATATCAAG). The two fragments were cloned into the binary vector for homologous recombination. The replacement of the OsWRKY76 coding region with the HPT cassette was confirmed by genomic sequencing of the OsWRKY76 locus. Seedlings (9 days old) were treated with JA and SA by dipping the roots into water containing 100 μM (+/−)‐JA (Sigma), 100 μM SA (WAKO), or a combination of these chemicals. In some experiments, seedlings were also treated with 100 μM ACC and 100 μM ACC + 100 μM SA. After treatments for appropriate time intervals, root samples, and, if appropriate, shoot samples (sheaths and leaves), were collected and frozen in liquid nitrogen.Rice  using genomic DNA prepared from rice leaves as a template and specific primers  to construct 4K‐pGEM. Three fragments  of the upstream region of RSOsPR10 were amplified, and each was inserted into the HindIII‐XbaI site of the pIG121‐Hm vector . These constructs were transformed into scutellum‐derived calli of cv. Nipponbare using Agrobacterium tumefaciens LBA4404 Electro‐Cells (TaKaRa Bio USA)  and 5′‐ CAACAGACGCGTGGTT‐3′ (reverse).To generate rs Table . The RSO2.3ubiquitin as the reference gene. All qRT‐PCR experiments were performed in biological triplicate and technical duplicate.Total RNA was extracted from rice roots or shoots using the RNeasy Plant Mini Kit (Qiagen) and used to synthesize cDNA with the High Capacity RNA‐to‐cDNA‐Kit  according to the manufacturer's protocol. The qRT‐PCR analyses were performed with a LightCycler 480  using SYBR Green I Master mix and the primers listed in Table 2.4RSOsPR10 2K‐, 3K‐, and 4K‐promoter::GUS lines  were treated with 100 μM JA for 12 h. To detect GUS activity, the roots were stained with 1 mM 5‐bromo‐4‐chloro‐3‐indolyl β‐D‐glucuronide (Wako) as described previously  region was inserted into the XbaI‐BamHI site of the pRL‐null vector  to construct Tnos‐pRL. The 2.6‐kb upstream region of the rice ubiquitin promoter was PCR‐amplified and inserted into the Tnos‐pRL to obtain pUbi‐pRL, which was used as an internal control.Each of the 4,087‐, 3,395‐, 3,005‐, 2,782‐, 1,975‐bp upstream regions of the 2.63K[G4 m], 3K[G2‐5m]) and the W box (3K[W2 m]) were generated using the PrimeSTAR Mutagenesis Basal Kit (TaKaRa Bio USA) with the modification that PCR‐amplified DNA fragments were treated with DpnI before insertion into Escherichia coli.Mutation constructs of GCC boxes  for each bombardment. Nine‐day‐old rice seedlings were placed on 1% agar (Wako 016‐11875) plates (3–4 seedlings/plate). Then, root tissue was bombarded twice at 1100 psi using the PDS‐1000 He Biolistic Particle Delivery System . After bombardment, the seedlings were kept on the plates for 30 min and then immersed in water containing JA and/or SA for 12 h at 27°C in darkness. After incubation, rice roots were homogenized in 200 μL cell lysis buffer (Promega). The homogenates were centrifuged, and the supernatants were used in the luciferase activity assay.2.8The luciferase assay was performed using the dual luciferase reporter assay system (Promega) according to the manufacturer's instructions. Luminescence was measured using a luminometer . The relative activity of firefly luciferase (FLUC)/renilla luciferase (RLUC) was recorded.2.9GUS sequence in pBI221 was replaced with the coding sequence of OsWRKY76. The plasmid expressing the GAL4 DNA‐binding (DB) domain was used as a control effector  with specific primers  and then recombined into pGWB502  using specific primers. The OsERF136 fragment was cloned into the SacI‐XbaI site of pBI221 using an In‐Fusion HD Cloning Kit . For cotransfection assays, 1 μg reporter plasmid, 1 μg effector plasmid, and 0.5 μg internal control plasmid were introduced into roots of 9‐day‐old rice plants as described above.The rs Table . Amplifi2.10OsERF87 ORF was fused into pGW505  and introduced into E. coli JM109 as described previously , m1 (5′‐CTCCACCGCCTTGAaCTATCGTCGCT‐3′) and m2 (5′‐CTCCACCGCCTcctaCTATCGTCGCT‐3′) (W‐box and mutated W‐box core sequences underlined). Gel mobility shift assays were performed using the DIG Gel Shift Kit 2nd Generation .The coding sequence of 2.12http://ricexpro.dna.affrc.go.jp/category-select.php) and the Arabidopsis Information Resource (https://www.arabidopsis.org/) databases under the following accession numbers: OsERF1 , OsERF83 , OsERF87 , OsERF136 , OsWRKY28 , OsWRKY62 , OsWRKY76 , OsPR10b , RSOsPR10 , ORA59/AtERF94 , PDF1.2 .Sequence data from this article can be found in the RiceXPro (33.1RSOsPR10 2K‐promoter::GFP did not show JA/ET‐induced or root‐specific expression of the green fluorescent protein (GFP) reporter. In this study, we searched for known stress‐responsive cis elements in the 4‐kb upstream region of RSOsPR10 using PlantPromoterDB (http://ppdb.agr.gifu-u.ac.jp/ppdb/cgi-bin/index.cgi). We found seven GCC boxes (GCCGCC) [AP2/ERF binding], eight W boxes ((T/C)TGAC(C/T)) [WRKY binding], two TGACG (as‐1‐like) motifs (TGACG) [bZIP type factor (TGA) binding], and four DREs ((A/G)CCGAC) [DREB (AP2/ERF) binding]  constructs, 4K (−1 to −4087 bp::GUS), 3K (−1 to −3005 bp::GUS), and 2K (−1 to −1975 bp::GUS)  reporter. Renilla LUC (RLUC) controlled by the rice ubiquitin promoter was used as an internal control. The ratio of FLUC activity to RLUC activity was calculated as a measure of promoter activity. Various‐length  fragments of the promoter region were fused to FLUC  was lower as that of 2.8K promoter   in the promoter ]. OsERF83, OsERF87, and OsERF136 mRNA transcripts were relatively abundant in roots and exhibited clear JA inductivity in roots [RiceXpro database (http://ricexpro.dna.affrc.go.jp/)]  are involved in regulating /)] Fig. .OsERF1, OsERF83, OsERF87, and OsERF136 and investigated the effect of these OsERFs on 3‐kb promoter activity by transient expression assays, co‐introducing the ERF genes as effectors into roots of rice seedlings harboring 3K::FLUC  in its 3‐kb promoter region.We cloned C Figure a. Transad Figure b, and nud Figure c. These 3.4RSOsPR10 transcription. Based on the results of our previous work, we presumed that SA induced some OsTGA or OsWRKY proteins to repress JA/ET‐dependent RSOsPR10 expression  may directly inhibit RSOsPR10 expression at the transcriptional level through binding to the W box(es) in its promoter. OsWRKY76 in rice was reported to exhibit transcriptional repressor activity in a W‐box‐dependent manner, and to suppress the induction of several PR genes, such as OsPR1, OsPR10b, and OsPR15, which have W boxes in their promoter regions  responsible for the SA suppression of JA/ET‐induced Escherichia coli and its binding activity was tested in a gel mobility shift assay. As shown in Figure RSOsPR10 promoter, as previously reported showing its binding to synthetic W‐box sequence  in RSOsPR10 in the roots of OsWRKY76‐knockout (KO) and OsWRKY76‐overexpressing (OX) rice lines using qRT‐PCR. The OsWRKY76 transcript levels in wild‐type plants were very low in mock and JA treatment, but apparently induced by SA, while the levels were about 10 times higher in OsWRKY76‐OX plants than in wild type, even mock and JA treatment ] ] Fig. . In the 44.1Arabidopsis  proteins in the model plant s Figure . Severals Figure . TherefoOsPR10 homologs  located in a gene cluster in chromosome 12 , these five genes are all induced by pathogen infection, but their expressions are differently regulated by plant hormones and in different organs. For example, OsPR10a/PBZ1 and OsPR10 are upregulated by both SA and JA, and expressed abundantly in aerial parts. In contrast, the OsPR10b expression pattern is very similar to that of RSOsPR10, but its expression level is about 1/40 that of RSOsPR10  and 15  groups  in group IXc were shown to activate transcription by binding to a component of the mediator complex   in the −3‐ to −2.8‐kb promoter region ) ) Fig. . Its imp4.3cis element known as the W box ((T/C)TGAC(C/T)) and mainly act as positive transcription factors, although group IIa WRKYs exhibit negative functions. In rice, the WRKY IIa subfamily has four members , at least three of which  function as transcriptional repressors in blast disease resistance  treatment, and therefore, it is probable that the regulation is downstream of the SA signaling pathway. However, it was also reported that OsWRKY76 was induced by wounding and MeJA in rice seedlings, indicating the involvement of JA signaling pathway  were previously observed in rice leaves  within the 2‐kb region upstream of the translation start site  other than WRKY(s) inhibits ORA59 expression or the ORA59‐mediator complex (Kazan, RSOsPR10 leaves enough space by making a loop structure. Because the 3‐kb promoter region contains many other cis elements, such as G‐box‐like, DRE, TGACG, and W‐box like motifs, it is possible that a complex combination of protein factors regulates the expression of RSOsPR10 according to developmental and/or environmental dynamic changes.There is a huge number of transcription factors in eukaryotes, but most have been studied one by one or in clusters of a few related factors (Song et al.,  Figures . As discx Kazan, . In the x Kazan, . CompareRSOsPR10 expression is regulated antagonistically by the novel OsERF87 activator and OsWRKY76 repressor in JA/ET and SA pathways, respectively. We propose the following model for the mechanism of action (Figure RSOsPR10 expression in the root, and RSOsPR10 enhances lateral root growth and development. The increased root mass leads to higher tolerance against biotic stresses. However, when rice plants are infected by pathogens, the SA level increases throughout the plant. The increased SA results in rapid induction of OsWRKY76 in the root, strongly suppressing the expression of RSOsPR10. By this process, rice plants can allocate more energy to defense against pathogen infection. This mechanism of antagonistic regulation is compatible with the concept a cost balance, because defenses are costly to produce (Ahmad et al., The results of this study show that T.K. conceived and planned the project. T.K., K.O., K.M., H.Y., and Y.N. designed the research. T.Y., A.G., K.N., M.T., Y.Y., H.S., T.O., T.N., N.Y., E.M., and K.M. performed the experiments. T.K., T.Y., A.G., H.S., K.M., and Y.N. wrote the article with contributions from all the authors. Click here for additional data file. Click here for additional data file. Click here for additional data file.


DNA methylation is a heritable epigenetic mark, enabling stable but reversible gene repression. In mammalian cells, DNA methyltransferases (DNMTs) are responsible for modifying cytosine to 5-methylcytosine (5mC), which can be further oxidized by the TET dioxygenases to ultimately cause DNA demethylation. However, the genome-wide cooperation and functions of these two families of proteins, especially at large under-methylated regions, called canyons, remain largely unknown.Tet1 increases DNMT3A1 binding capacity at and around genes with wild-type TET1 binding. However, deletion of Dnmt3a has a minor effect on TET1 binding on chromatin, indicating that TET1 may limit DNA methylation partially by protecting its targets from DNMT3A and establishing boundaries for DNA methylation. Local CpG density may determine their complementary binding patterns and therefore that the methylation landscape is encoded in the DNA sequence. Furthermore, DNMT3A and TET1 impact histone modifications which in turn regulate gene expression. In particular, they regulate Polycomb Repressive Complex 2 (PRC2)-mediated H3K27me3 enrichment to constrain gene expression from bivalent promoters.Here we demonstrate that DNMT3A and TET1 function in a complementary and competitive manner in mouse embryonic stem cells to mediate proper epigenetic landscapes and gene expression. The longer isoform of DNMT3A, DNMT3A1, exhibits significant enrichment at distal promoters and canyon edges, but is excluded from proximal promoters and canyons where TET1 shows prominent binding. Deletion of We conclude that DNMT3A and TET1 regulate the epigenome and gene expression at specific targets via their functional interplay.The online version of this article (10.1186/s13059-018-1464-7) contains supplementary material, which is available to authorized users. Dnmt triple knockout (TKO) embryonic stem cells (ESCs) progressively lose differentiation potential [DNA methylation at the 5-position of cytosine (5mC) on CpG dinucleotides is a heritable epigenetic marker in mammals that is critical for development, X-chromosome inactivation, silencing of transposons and repeat elements; aberrant DNA methylation is often implicated in carcinogenesis , 2. DNA otential , 7. In aotential  and canyotential , 9. The Ten-eleven translocation (TET) proteins have been identified as dioxygenases that convert 5mC to 5-hydroxymethycytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC) –12. 5mC The genome-wide DNA methylation landscape changes dynamically during mammalian development . Global In the present work, we have taken advantage of mouse embryonic stem cells, where both DNMT3A/3B and TET1 are highly expressed, to elucidate the binding behaviors of DNMT3A and TET1 around transcriptional start sites (TSS) or canyons. We demonstrated that DNMT3A and TET1 impact gene expression via alterations in the histone landscapes surrounding these regions. In particular, they regulate gene expression at poised bivalent genes through affecting Polycomb Repressive Complex 2 (PRC2)-mediated H3K27me3 enrichment.Dnmt3a or Dnmt3b. DNA methylation landscapes at single-base resolution were generated by whole genome bisulfite sequencing (WGBS) between wild type (WT), Dnmt3a KO, and Dnmt3b KO J1 ESCs [Dnmt3a had a much more dramatic impact than loss of Dnmt3b on DNA methylation genome-wide  compared to both WT (n = 9920) and Dnmt3b KO  cells  that 5hmC accumulates at the edges of canyons; we proposed that the TET family of proteins TET1/2/3), which catalyze conversion of 5mC to 5hmC, may be localized to these sites . To test/2/3, whiantibody . A stronFoxo1 locus, TET1 is seen binding in the canyon from edge-to-edge, whereas DNMT3A1 accumulates at the edges and outside the canyon  KO cells, resulting in significant loss of DNA methylation  previously described [Tet1 KO ESCs.The notable exclusion of DNMT3A1 binding to TET1-occupied genomic regions strongly suggests a functional relationship between TET1 and DNMT3A binding to DNA. Previous studies have shown that depletion of TET1 via RNA interference (RNAi) can lead to a slight global increase in the level of 5mC, as well as localized increase in 5mC at TSSs and the genomic regions flanking their proximal promoters , 28. To escribed . After cTet1/2/3 Triple KO (Tet-TKO) ESCs [Tet1 KO ESCs, ranking them by the magnitude of change in DNMT3A1 occupancy after Tet1 KO. The regions with the greatest change were also those with highest TET1 binding in WT ESCs , both in overall occupancy (peak height) and by invading into flanking regions  ESCs   in Tet1-FLAG ESCs  cells from WT J1 ESCs and assessed changes of expression by RNA-sequencing (RNA-seq).As discussed above, the patterns of histone marks and overall gene expression differ according to DNMT3A and TET1 binding in WT cells. To further elucidate the impact of these proteins on gene expression, we regenerated Dnmt3a KO, Tet1 KO, and DKO cells. Seven clusters of genes were classified (C1–C7) based on their expression changes compared to WT. Generally, these differentially expressed genes (DEGs) were either specific to Dnmt3a deletion  or Tet1 deletion (C2 and C6), or changed commonly by both, mostly in the same directions  of the two proteins. Compared with WT, many genes  were downregulated in Dnmt3a KO cells, suggesting the correlation between DNA methylation and gene repression is low. Enrichment analysis (Gene Ontology) showed that genes from Hippo and TGF-beta signaling pathway were over-represented in C1, while PI3K-Akt signaling pathway genes were enriched in C2  in the various KO cell lines at differentially expressed genes  compared to WT and Dnmt3a KO, respectively  supplemented with 15% fetal bovine serum , 1 × non-essential amino acids , 1 × GlutaMAX , 1 μM 2-Mercaptoethanol , 1 × sodium pyruvate , 1 × Penicillin/Streptomycin , and 1000 U/mL LIF .Dnmt3a1 ESCs were obtained by cloning Dnmt3a1 cDNA  into pENTR/D-Topo vector (Thermo-Fisher) followed by Gateway recombination into p2Lox and inducible cassette exchange as previously described [Tet1 in this cell line was achieved using pX330 and the guide RNA for exon 4 of Tet1 was previously used [Bio-escribed . The gensly used .Tet1-FLAG cells, WT J1 ES cells were transfected with 1.0 μg eSpCas9-Tet1 [Tet1 [Dnmt3a in established Tet1-FLAG ES cell line, exons 18–19 of Dnmt3a (Dnmt3a1) were deleted by dual sgRNAs-facilitated CRISPR/Cas9 system. Guide RNAs were cloned into pX459 vector and transfected into Tet1-FLAG J1 ES cells with Lipofectamine® 3000 reagent. The transfected cells were selected, cultured, and screened as above.To generate as9-Tet1 , 250 ng t1 [Tet1 , and 1.5Tet1 KO and Dnmt3a-Tet1 DKO J1 ES cells were obtained by deleting exon 4 of Tet1 alone or together with exons 18–19 of Dnmt3a (Dnmt3a1) using dual sgRNAs-facilitated CRISPR/Cas9. All guide RNAs and genotyping primers used in this paper are listed in Additional file 6 Bio-Dnmt3a1 ES cells by resuspension in CytoBuster Protein Extraction Reagent (Millipore) followed by 15-min incubation at room temperature (RT). Non-induced ESCs served as a negative control. Samples were spun at 20,000 g, 4 °C for 15 min and supernatant was isolated. Immunoprecipitation of biotinylated-DNMT3A1 was performed with M280-streptavidin beads (Thermo Fisher) using whole-cell extract from cultures with or without doxycycline induction. Equal amounts of protein were resuspended in Laemmli buffer and loaded for western blot analysis. The following antibodies were used: anti-DNMT3A , anti-TET1  induction, whole-cell extracts were obtained from 5 × 10iang Xu, ), and anBiotin-Streptavidin ChIP was performed as described, with some modifications . After aFLAG , TET1 , and SUZH3K4me3  and H3K27me3  ChIP were performed as previously described , with 3 For ChIP-seq, sequencing libraries were prepared using ThruPLEX DNA-seq 48D kit (Rubicon Genomics) following standard protocols. Samples with different dual-index barcodes were combined at equal molar ratios and sequenced as pools. Sequencing of library pools was performed on Illumina HiSeq 2000 or NextSeq 500 system according to Illumina standards, with 50-bp or 75-bp dual-end sequencing. Library de-multiplexing was performed following Illumina standards.WGBS library construction was done as previously published . For WGBAnti-cytosine-5-methylenesulfonate-immunoprecipitation (anti-CMS-IP) was performed as previously described  with slihttp://zymoresearch.com) using high-pressure liquid chromatography coupled with mass spectrometry.Measurements of 5mC and 5hmC were performed by Zymo Research  to trim the low-quality bases and the adapters. TopHat [genome.ucsc.edu/cgi-bin/ hgTables?command = start). SAMtools [Paired-end reads were sequenced for RNA-seq. We used Trim Galore (. TopHat  was usedSAMtools  was usedSAMtools  with cutDnmt3a KO), DNMT3A1 (WT and Tet1 KO), H3K4me3, and H3K27me3 across the flanking 5-kb region around gene TSSs, which were then subjected to TreeView to plot the heatmap figures; (2) calculated CpG density for each gene promoter (− 1 kb ~ + 0.5 kb); (3) calculated FPKM for each gene from RNA-seq analysis; and (4) plotted the average profiles of 5mC level and 5hmC level centered on TSSs.In order to measure the different binding properties of DNMT3A1, 3A2, and 3B1 around gene TSSs, we selected the longest isoform for each gene resulting in 22,766 unique gene TSS locations. We then retrieved the normalized occupancy values of DNMT3A1, 3A2, and 3B1 in WT across the flanking 5-kb region around gene TSSs and clustered all TSSs into five groups using the K-Means R package. Based on the same order from K-means result, we: (1) retrieved the normalized occupancy values of TET1 Additional file 2:Table S1. List of oligonucleotides: guide sgRNAs and primers. (PDF 52 Kb)


Drosophila germline-specific piRNA clusters ensure transcription and processing of piRNA precursors. TEs harbour various regulatory elements that could affect piRNA cluster integrity. One of such elements is the suppressor-of-hairy-wing (Su(Hw))-mediated insulator, which is harboured in the retrotransposon gypsy. To understand how insulators contribute to piRNA cluster activity, we studied the effects of transgenes containing gypsy insulators on local organization of endogenous piRNA clusters. We show that transgene insertions interfere with piRNA precursor transcription, small RNA production and the formation of piRNA cluster-specific chromatin, a hallmark of which is Rhino, the germline homolog of the heterochromatin protein 1 (HP1). The mutations of Su(Hw) restored the integrity of piRNA clusters in transgenic strains. Surprisingly, Su(Hw) depletion enhanced the production of piRNAs by the domesticated telomeric retrotransposon TART, indicating that Su(Hw)-dependent elements protect TART transcripts from piRNA processing machinery in telomeres. A genome-wide analysis revealed that Su(Hw)-binding sites are depleted in endogenous germline piRNA clusters, suggesting that their functional integrity is under strict evolutionary constraints.Piwi-interacting RNAs (piRNAs) control transposable element (TE) activity in the germline. piRNAs are produced from single-stranded precursors transcribed from distinct genomic loci, enriched by TE fragments and termed piRNA clusters. The specific chromatin organization and transcriptional regulation of  Drosophila, piRNA precursors are derived from distinct genomic regions termed piRNA clusters, which are enriched in TE fragments  (according to the dm3 genome assembly). The transgenic strain KG02245 (Bloomington Drosophila Stock Centre #12975) carries a P{SUPor-P} insertion in the 49E locus. Transheterozygous V/su(Hw)fsu(Hw) flies were used in the study.The transgenic strain eviously . Transgehttp://www.fruitfly.org/p_disrupt/TE.html) or to the piRNA clusters [Small RNAs 19–29 nt in size from total ovarian RNA extracts were cloned as previously described . The libclusters .KG10047;+/+, KG10047;V/su(Hw)fsu(Hw), KG09351;+/+; KG09351;V/su(Hw)fsu(Hw) ; KG02245;+/+ and KG02245;V/su(Hw)fsu(Hw) were deposited at Gene Expression Omnibus (GEO), accession number GSE125173.Ovarian small RNA-seq data for rp49 gene as a control genomic region. Standard error of mean (SEM) of triplicate PCR measurements for three biological replicates was calculated.ChIP was performed according to the published procedure . Chromatrp49. The primers used are described in RNA was isolated from the ovaries of three-day-old females. cDNA was synthesized using random hexamers or strand-specific primers and SuperScriptII reverse transcriptase . cDNA samples were analysed by real-time quantitative PCR using SYTO-13 dye on a LightCycler96 . Values were averaged and normalized to the expression level of the ribosomal protein gene p-value 1 × 10−5 was used as the threshold level.To estimate the frequency of the Su(Hw) insulator sites, the corresponding PWM profile (MA0533.1 from JASPAR_2016 database) was searched against the dm6 genome assembly or piRNA cluster regions . The p-vgypsy insulators and located within endogenous piRNA clusters. KG10047 and KG09351 transgenes were inserted into the 3′UTR of telomeric retrotransposon HeT-A and the major pericentromeric piRNA cluster in the 42AB locus, respectively fsu(Hw) mutations. These mutations cause the loss of Su(Hw) binding to the gypsy insulator [Both integrated loci were previously described as potent piRNA clusters able to adapt new insertions for piRNA production ,15,16,32th cases B. We sugnsulator ,34 and, nsulator   mutants are 21-nt endogenous small interfering RNAs (endo-siRNAs) C. Indeedgypsy insulators inserted in Drosophila subtelomeric and telomeric piRNA clusters are incorporated in piRNA production and acquire chromatin properties of their surrounding regions [gypsy insulators prevent piRNA production from P{SUPor-P} transgenic sequences, even if the latter are inserted into endogenous piRNA-producing regions.Previously, it was reported that P{lArB}, pW8-hsp-pA and P{EPgy2} transgenes lacking  regions ,18,32. S regions . We showV null allele and the Su(Hw)f, which carry a defective zinc finger 10 [f protein demonstrated the loss of binding to gypsy insulator and the reduced occupancy of many non-gypsy Su(Hw)-binding sites [V/su(Hw)fsu(Hw) ovaries, shows a dramatic decrease of Su(Hw) binding to the gypsy insulator and P{SUPor-P} transgenes. As it was reported previously, mutant Su(Hw)f is retained at some insulators including site located in 62D locus [To learn more about the mechanism of the Su(Hw)-mediated prevention of piRNA production, we compared the chromatin state of transgenes in the wild type and Su(Hw)-mutant backgrounds. In our experiments, we used transheterozygous flies with two Su(Hw) alleles: the Su(Hw)inger 10 . Su(Hw)fng sites ,38. ChIP2D locus ,34. Inde42AB locus and telomeric retroelement HeT-A lack these chromatin hallmarks in the presence of Su(Hw) protein (in the wild type genetic background) but acquire them in Su(Hw)-mutant ovaries  mutation in KG09351 and only 1.5-fold increases in KG10047;V/fsu(Hw) ovaries  was not affected by Su(Hw) mutation (gypsy insulator complex is established upstream of the Piwi-dependent chromatin formation of piRNA clusters and Su(Hw) binding mostly affects local chromatin conformation.The data from ChIP using Rhi, HP1 and H3K9me3 antibodies show that P{SUPor-P} transgenes inserted in both the  ovaries C–E. At tmutation . Therefomini-white gene of the transgenes inserted into HeT-A (KG10047 strain) and 42AB (KG09351 strain) in the wild-type and mutant background using transgene-specific primers  mutants for both insertions  binding  and Modifier of mdg4 (Mod67.2) [Our data suggest that Su(Hw) binding to P{SUPor-P} transgenes inserted into piRNA clusters should block transcription of long piRNA precursors. To verify this suggestion, we compared expression of  primers A. It shosertions A. In addsertions A. Strandspecific B. We thespecific C. These  binding D. HoweveMod67.2) ,40, the gypsy insulators might impair the functioning of the cluster regions in the close vicinity of transgenic insertion. To verify this suggestion, we estimated piRNA production in 42AB regions located around the KG09351 insertion.Given the functional integrity of piRNA clusters, we suggested that 42AB locus  mutations restored the level of transgene-flanking piRNAs in the 7 strain A. We alsransgene C. This f1 strain B. Thus, in  binding results in a local decrease in small RNA production not only from the HeT-A 3′UTR at 2R telomere because the unique mapping of small RNAs to poorly assembled and highly repetitive telomeric regions was technically impossible.We could not perform the analysis of flanking piRNAs near the KG10047 transgene inserted in the 42AB was helpful for understanding of the transcription regulation of the major uni-strand flamenco (flam) locus that controls TE expression in ovarian follicular cells [flam locus produces primary piRNAs from single strand precursors [gypsy, ZAM and Idefix [flam transcription. It is believed that piRNAs complementary to the coding transcripts of these TEs are produced from the single strand precursors transcribed by the flam sense strand [gypsy, Zam and Idefix insulators do not interfere with the transcription of the flam piRNA precursors, likely due to a strand-specific mode of insulator influence on transcription.To a certain extent, insertion of P{SUPor-P} transgene in ar cells ,44. In cd Idefix ,23,24, aHeT-A, is a non-autonomous retroelement and reverse transcriptase (RT) activity is likely to be provided by TART or TAHRE telomeric retrotransposons. In Drosophila germline, telomeric regions are organized in the piRNA clusters, although telomeric elements are heterogeneous in piRNA production and Rhi binding: TART retrotransposons are less susceptible to piRNA production and Rhi deposition than HeT-A [TART transcripts may be protected by an unknown mechanism from piRNA biogenesis machinery to provide stable expression of RT essential for telomere elongation in the germline. Here, we present the data suggesting a role for Su(Hw) in this mechanism.The main structural telomeric element, an HeT-A . This imUsing small RNAseq data, we studied the genome-wide impact of Su(Hw) depletion on transposon-derived piRNA production. The mapping of small RNAs to a canonical set of TEs does not demonstrate global changes caused by Su(Hw) mutations .TART-B and TART-C subfamilies of telomeric retrotransposons fsu(Hw) strains. To this end, we performed PCR on genomic DNA and showed that the relative copy numbers of HeT-A, TAHRE, TART-A, TART-B and TART-C are very similar in both strains (TART-B/TART-C transcripts are protected by Su(Hw)-dependent border elements from the piRNA production. Next, we examined the RNA levels of telomeric retroelements in the ovaries of Su(Hw) mutants by RT-qPCR. We found an increased level of TART-A transcripts in the ovaries of Su(Hw) mutants, while HeT-A and TAHRE expression was not affected  mutants (TART-encoding transcripts in telomeres. Su(Hw) serves as a transcriptional repressor of coding genes in the ovary [TART transcripts are less abundant than upon Su(Hw) depletion. Thus, Su(Hw) likely mediates transcriptional repression of TART in the germline.However, piRNA production from few TEs was strongly affected . In partnsposons . To excl strains C. These affected D. Howeve mutants E. These he ovary . Notably42AB cluster -binding sites in the whole genome and in piRNA clusters . We found that the Su(Hw) site density was lower in piRNA clusters (one site per 45 kb) than in the genome . It is tempting to speculate that the spectrum of regulatory sequences associated with TEs in piRNA clusters is subjected to strict selection to provide functional integrity of piRNA-producing loci.What could be happened if the insulator is inserted into the piRNA cluster? To some extent, this situation is simulated by the insertion of P{SUPor-P} transgene into the  cluster . Interesactivity ,46. The TART and TAHRE retrotransposons  failed to identify the Su(Hw) binding sites in canonical copies of telomeric retrotransposons. Thus, the nature of Su(Hw) binding sites in telomeres is still to be determined.Indeed, mapping of small RNAseq reads to the annotated piRNA clusters  did not nsposons . HoweverAlthough the loss of Su(Hw) causes female sterility, its particular role in the female germline development is not well understood ,38. Su(HV/Su(Hw)fSu(Hw) mutations on the abundance of piRNAs derived from coding genes (V/Su(Hw)fSu(Hw) ovaries, suggesting that Su(Hw) might prevent the spread of piRNA production from piRNA clusters/TEs to neighbouring genes. Indeed, Su(Hw) depletion causes the appearance of piRNAs antisense to the transcripts of the Rab8 gene located next to the cluster #48  in the germline. We revealed a genome-wide effect of ng genes . Most ofster #48 B. PCR byster #48 . At leasTART and coding gene transcripts from spurious piRNA production in the germline.Genomic regions containing damaged transposon fragments were for a long time considered as waste dumps. Most of these regions are piRNA-producing loci that play an essential role in antitransposon defence. The complex regulation of piRNA clusters has evolved to provide piRNA production from the entire piRNA cluster. This mechanism ensures an adaptive response to insertions of alien transposons in a piRNA cluster. We show that Su(Hw) binding sites disrupt the integrity of endogenous piRNA clusters, indicating that the assembly of insulator complexes occurs upstream of cluster-specific chromatin formation. Considering that distinct TE families comprise insulator-binding sites and other regulatory sequences, the TE content of the piRNA clusters should be under strict evolutionary constraints. Moreover, Su(Hw)-mediated complexes likely protect telomeric retrotransposon


The imprinting control region (ICR) located far upstream of the H19 gene, in conjunction with enhancers, modulates the transcription of Igf2 and H19 genes in an allele-specific manner. On paternal inheritance, the methylated ICR silences the H19 gene and indirectly facilitates transcription from the distant Igf2 promoter, whereas on the maternal chromosome the unmethylated ICR, together with enhancers, activates transcription of the H19 gene and thereby contributes to the repression of Igf2. This repression of maternal Igf2 has recently been postulated to be due to a chromatin boundary or insulator function of the unmethylated ICR. Central to the insulator model is the site-specific binding of a ubiquitous nuclear factor CTCF which exhibits remarkable flexibility in functioning as transcriptional activator or silencer. We suggest that the ICR positioned close to the enhancers in an episomal context might function as a transcriptional silencer by virtue of interaction of CTCF with its modifiers such as SIN3A and histone deacetylases. Furthermore, a localised folded chromatin structure resulting from juxtaposition of two disparate regulatory sequences (enhancer ICR) could be the mechanistic basis of ICR-mediated position-dependent (ICR-promoter) transcriptional repression in transgenic Drosophila.