Drosophila developmental promoter motifs, the TATA box (TATA) and the Initiator (INR). Using live imaging in Drosophila embryos and new computational methods, we demonstrate that bursting occurs on multiple timescales ranging from seconds to minutes. TATA-containing promoters and INR-containing promoters exhibit distinct dynamics, with one or two separate rate-limiting steps respectively. A TATA box is associated with long active states, high rates of polymerase initiation, and short-lived, infrequent inactive states. In contrast, the INR motif leads to two inactive states, one of which relates to promoter-proximal polymerase pausing. Surprisingly, the model suggests pausing is not obligatory, but occurs stochastically for a subset of polymerases. Overall, our results provide a rationale for promoter switching during zygotic genome activation.Genes are expressed in stochastic transcriptional bursts linked to alternating active and inactive promoter states. A major challenge in transcription is understanding how promoter composition dictates bursting, particularly in multicellular organisms. We investigate two key  Drosophila embryos. TATA-driven promoters require one rate-limiting step while INR promoters need an extra step associated with Pol II pausing.Here the authors decode how core promoter elements regulate rate limiting steps of transcription using quantitative live imaging, genetics and modeling in early  This includes the sequential recruitment of general transcription factors to form the pre-initiation complex (PIC), followed by the recruitment of RNA Polymerase II (Pol II) at the transcriptional start site (TSS)4 of promoters. Among all these complexes, TFIID stands out as the primary core promoter recognition factor that triggers PIC assembly5. TFIID includes TATA-binding protein (TBP), which binds upstream of the TSS, as well as 13 TBP-associated factors (TAFs), known to bind downstream promoter elements such as the Initiator element (INR) and the downstream promoter element (DPE) motifs6.In all eukaryotes, transcription of active genes into RNA requires the controlled assembly of multiple protein complexes at promoters7. This step is regulated by the TFIID complex, as directly demonstrated in vitro8 and inferred from the over-representation of TFIID-bound core promoter motifs  in highly paused genes13. Pausing durations are highly variable among genes16. However, it is thought that exit from the paused state is a kinetic bottleneck in the transcriptional cycle17 and is often used as a checkpoint during development to foster coordination in gene activation, plasticity or priming21. How core-promoter motifs affect this rate-limiting step is still unknown, particularly in the context of a developing embryo.After initiation, Pol II transcribes a short stretch of 30–80 nucleotides before pausing22. Direct labeling of newly synthesized RNA with the MS2/MCP amplification system24 has been the method of choice to observe these bursts in real time in living cells27 or multicellular organisms29. In the context of a developing embryo, these studies revealed how enhancers regulate bursting during pattern formation32. However, relatively less attention has been given to the impact of core promoter motifs on transcriptional bursting.In parallel to these genomics approaches, single-cell imaging revealed that transcription is not a continuous process over time but occurs through stochastic fluctuations between periods of transcriptional activity and periods of inactivity, called bursting22. Indeed, depending on the gene and the cellular context, transcriptional bursting has been shown to occur at multiple timescales34, from seconds , to minutes  to hours . These different timescales can all occur at a single gene, and the term multiscale bursting was coined to describe such complex bursting kinetics37. This multiscale bursting might explain why the simple two-state model (random telegraph), whereby promoters switch from an active to an inactive state, does not always suffice to reliably capture promoter dynamics42.To build a mechanistic understanding of bursting beyond a qualitative description of burst size and frequency, it is critical to consider the various timescales of the transcription process and to employ mathematical modeling explicitly describing various promoter statescis-regulatory sequences must impact transcriptional bursting, with enhancers primarily affecting burst frequencies44, a detailed dissection of the impact of promoter motifs on promoter-state dynamics is lacking. In this study, we sought to examine the role of core promoter sequences on transcriptional bursting in Drosophila embryos. In particular, we focus on two core promoter motifs, the TATA box (TATAWAWR) and the INR (TCAGTY in Drosophila6) which represent pivotal core promoter contact points with the TFIID complex46, and are known to regulate both initiation and promoter pausing12.While it is well understood that Drosophila early embryo is an ideal system to decipher transcriptional bursting regulation since spatially distinct patterns of gene expression are deployed within a relatively short time frame in a multinucleated syncytium, rapidly dividing, that is highly amenable to quantitative imaging47. At this early stage of development, the zygotic genome, initially transcriptionally silent, awakens progressively while cell cycle durations lengthen, a process known as the maternal-to-zygotic genome transition (MZT)48. This zygotic genome activation (ZGA) occurs gradually through two waves, a major wave during nuclear cycle 14 (nc14) and a minor wave occurring at earlier stages. Moreover, Drosophila developmental genes show a clear promoter code with well-defined promoter elements49, with differential usage during ZGA50.The Drosophila embryos to detect all single polymerase initiation events. The waiting times between successive initiation events were further analyzed to infer the number of promoter states and the transition rates among these states. Our results show that TATA box-containing promoters are highly permissive to transcription through long ON durations and high Pol II firing rates. However, the presence of an INR in the core promoter necessitates the use of a three-state model, with a second inactive promoter state that is likely a consequence of Pol II pausing. We propose a renewed view of promoter pausing whereby only subsets of polymerases enter into a paused state.We employed the MS2/MCP system to monitor nascent transcription. We implemented a machine-learning method that deconvolves single-nuclei mRNA production from live Drosophila genome  are eliminated. Core promoters were inserted immediately downstream of the snail (sna) distal minimal enhancer (snaE)51. The core promoters were selected based on the presence of known core promoter motifs49, such as a TATA box in sna or an INR in kruppel (kr) and Insulin-like peptide 4 (Ilp4)  core promoter, which is devoid of any known canonical promoter motifs. None of these four promoters have a DPE, however, Ilp4 possesses a bi-partite bridge element49. These developmental genes are endogenously expressed during nc1453 and precise TSS positions were established using embryonic CAGE  datasets54  and then associated with their nearest nucleus. This generated individual 4D nuclear trajectories  of 11 min and 14 min, respectively while the INR-driven Ilp4 promoter was delayed with t50 of 21 min. The brk core promoter did not surpass 24% of nuclei activated throughout nc14.We hypothesized that differences in core promoter motifs would result in variability in gene expression independently of specific enhancer contacts. To test this, we characterized single-nucleus transcriptional activity Fig. , as wellles Fig. , definedIn addition to differences in synchrony, the overall mRNA production also varied between transgenes Fig. . Within Thus, we established an experimental setup and quantification pipeline that allows disentangling the contribution of minimal promoter sequences on transcriptional activation of individual, naturally synchronized nuclei within a well-defined, homogeneous spatial domain in live embryos. This initial quantitative comparison of four natural developmental promoters suggests that those with a canonical promoter motif (either TATA or INR) tend to produce higher levels of expression.Drosophila embryo. Live imaging of transcription typically shows spots comprised of several newly synthesized mRNAs resulting from the action of multiple polymerases. In order to calibrate fluorescent signals from live imaging, we used single-molecule hybridization experiments28. Using the fluorescence of a single mRNA molecule, we estimated the average number of mRNA molecules present at the TS within the nucleus at a steady state , the size of the transcript (5.6 kb), and the retention time of the mRNA at the transcription site .In order to detect initiation events, we considered that each trace results from the convolution between (i) the sequence of initiation events marked by a rise in GFP intensity plotted over time, and (ii) the signal produced by a single polymerase Fig. 33,59. Thody Fig.  and thusody Fig. . In this59. A multiexponential regression fitting was applied to the distribution of Δt, indicating the number of rate-limiting transitions required to best fit the data (“Methods”). We used confidence intervals and a Kolmogorov–Smirnov test to rigorously determine the smallest number of rate-limiting steps fitting our experimental data ON , kOFF , and kINI  for the simplest two-state model. However, kinetic estimates of more complex models (three or more promoter states) can also be derived from the Δt distribution. The accuracy and robustness of the deconvolution method were tested by applying it to artificial data with known positions of transcription initiation events and known kinetic parameters  fitting correctly fit the survival function of polymerase waiting times  that is bound by TBP50 . Surprisingly, the strong TATA mutation did not completely abolish the activity of the sna promoter, although this mutant promoter was devoid of any known core promoter motifs. In comparison to the sna promoter, the synchrony of the sna TATA mutants was reduced in a graded manner relative to the fidelity of the TATA box   Fig. . In contOFF Fig.  for the ter Fig. . The strter Fig. . The redDrosophila embryos is also in agreement with results from live imaging of HIV-1 transcription in human cells37, and with genomic studies in cultured mammalian cells, where TATA-driven promoters are associated with large burst sizes67. They differ from those obtained with mutations of the native actin promoter in Dictyostelium36, which may be due to differential behavior between induced genes and constitutive genes or to compensation by other genomic elements36.The impact of TATA on the duration of ON/OFF promoter states observed in Drosophila embryos, the TATA box largely controls gene expression through lengthening the ON state duration at the expense of the OFF state duration, but does not alter the number of promoter states.We conclude that in 3, and yet TATA-driven promoters can be modeled with a simple two-state model corresponding to one kinetic rate-limiting step in this complex process. We hypothesized that additional rate-limiting steps were likely to exist and could be identified using our imaging-based methodology. As the TATA box did not affect the number of promoter states for the sna promoter, we examined the effect of another core promoter motif, the INR. In Drosophila cells and embryos, the INR is associated with stably paused genes, genome wide68. Moreover, analysis in cell culture indicated that genes with increased pausing stability tend to harbor an INR motif in the core promoter, and in particular a preferential G at the +2 position12. We, therefore, reasoned that manipulating the INR motif in embryos might affect pausing and therefore may induce changes in rate-limiting promoter states.At the biochemical level, transcriptional activation is a multistep process requiring the orchestration of many factorssna core promoter does not have an INR, while the core promoter of kr has a natural INR sequence with a G at +2 and is stably paused18. Moreover, the kr promoter possesses a non-canonical TATA box . We also created a transgene . Interestingly, neither loss of the INR in the kr-INR1 transgene nor gain in the sna+INR transgene strongly affected synchrony  had similar synchrony and mRNA production (average instantaneous intensity) as in the wild-type kr promoter  led to a two-exponential fitting for the survival function   resulted in a reversion to a two-exponential fit , we reasoned that one of these states could be polymerase pausing. To test this hypothesis, we impaired the establishment of pausing by reducing the expression of the largest subunit of the pause-inducing negative elongation factor complex (NELF), NELF-A. Previous work demonstrated that depletion of NELF by RNAi globally reduced promoter-proximal pausing in 70  was obtained by quantifying the Pol II binding at the promoter relative to the gene body70 Fig. . As show PI Fig. , consistsed Fig. . Mutatioing Fig. . Likewisnce Fig. . Both th73. We therefore initially tested if our data could be explained by a model consisting of three promoter states  where all productive polymerases undergo pausing prior to transitioning to the permissive ON state . The major difference between these two promoters was the existence of two distinguishable inactive states linked to the presence of the INR sequence. One of these was short-lived (17 s) and one long-lived (302 s) , but occurs infrequently. Interestingly, the sna promoter is also moderately paused in our ChIP assay and at its endogenous locus74, but this promoter is not regulated by a three promoter-state dynamic. We hypothesize that pausing is highly unstable for this promoter at this stage and does not constitute a rate-limiting step that we can capture with our live-imaging assay (see “Discussion”).In the case of ely Fig. . Pausingtif Fig. . Thus oukr transgene exhibited a highly probable permissive state (0.83) with a duration of 94 s , there was a significant increase in ON duration   and transition times between them (b). We applied this modeling framework to our data by only focusing on the distribution of waiting times between mitosis and first activation  nearly twice that of the snaTATAlight promoter . We, therefore, propose that the permissive state in Drosophila embryos corresponds to a state where promoter DNA is bound by the PIC. The inactive state, which we found to be very transient, could then possibly represent a TBP-unbound configuration consistent with TBP dynamics observed in human cells79.How could such a small number of states be compatible with the numerous promoter-binding events occurring during transcription initiation? Biochemical studies reveal structural states, while imaging-based approaches unmask key rate-limiting kinetic states. Whole-genome methylation footprinting disentangled five transcription initiation states in sna promoter as a model, we found that TATA box directly impacts promoter occupancy of the active state and allows large transcriptional bursts by promoting long ON durations. How could the presence of a TATA box permit these long ON durations? Slow TBP protein turnover at human TATA box-containing genes may foster stable long ON durations79. However, this hypothesis needs to be confirmed by quantification of TBP kinetics during Drosophila ZGA.By using the snail promoter is among the first genes to be transcribed during ZGA, in a particularly constrained environment with extremely short cell cycles (<15 min). Remarkably, the majority of genes expressed during this critical period are highly expressed, short, and intron-less with a canonical TATA box and are generally nonpaused50. Subsets of these, including snail, are considered “dual promoters”, as they gradually acquire pausing as development proceeds50. Thus, it is possible that the kinetic bottlenecks regulating transcription of developmental promoters evolve as developmental timing proceeds, with paused polymerase gradually emerging as a rate-limiting step. In our study, the promoter model sna shows a moderate level of pausing (as measured by ChIP) but is regulated by a simple two-state model in nc14. This could indicate that pausing occurs on a timescale indistinguishable from the OFF state and is thus embedded within it. Strikingly, early transcription in zebrafish embryos occurs in similarly constrained rapid cell cycles where a subset of zygotically activated genes also display a T/A-rich WW-box motif80. Thus, regulation of transcription via a unique rate-limiting step (OFF to ON transition) that is TBP-dependent might be conserved between fly and vertebrate embryos.In its endogenous context, the In this work, we provided quantitative evidence that INR-containing promoters are associated with a three-state model , contrasting with TATA promoters.80. Given the results of this study and those obtained in Drosophila cultured cells16, it is tempting to link the gradual emergence and stabilization of pausing during ZGA with the presence of an INR, in particular an INR with a G at +2 position12. In light of our results, we propose that the switch in promoter usage from TATA-driven to INR-driven during ZGA may lead to a change in transcriptional dynamics from two to three states, to include an elongation-mediated checkpoint. Acquisition of an extra rate-limiting step might help control cell-to-cell expression variability as well as fine-tune gene expression levels.Interestingly, genomics studies revealed that transcription initiation code evolves during ZGA in flies and vertebrates81 combined with this framework will help to establish a broader understanding of the nature of promoter states and the role of Pol II pausing in vivo.Taken collectively, this study establishes our promoter imaging assay and novel mathematical deconvolution and modeling methodology as a valuable tool to probe gene expression dynamics during development. Quantitative analysis of promoter dynamics at high temporal resolution opens the door to a deeper insight into the molecular mechanisms underlying transcriptional regulation in vivo. Future studies involving direct manipulation of pause initiation or duration in living embryos using approaches such as optogeneticsMCP-eGFP-His2Av-RFP construct. For smiFISH, homozygous flies were crossed to yw in order to facilitate single-molecule detection. nos:GAL4-VP16 was recombined with MCP-eGFP-His2Av-RFP57. UAS:white RNAi (#35573) and UAS:Nelf-A RNAi (#32897) were obtained from the Bloomington Stock Drosophila Centre .All crosses were maintained at 25 °C. Transgenic lines were maintained as homozygous stocks. For live imaging, homozygous males carrying the transgene of interest were crossed with homozygous females bearing the sna distal enhancer-24xMS2-y minigene has been previously described57. Promoters . Stocks are available upon request.The Embryos were permitted to lay for 2 h prior to collection for live imaging. Embryos were hand dechorionated and mounted on a hydrophobic membrane prior to immersion in oil to prevent desiccation, followed by the addition of a coverslip.Live imaging was performed with an LSM 880 with Airyscan module (Zeiss). Z-stacks comprised of 30 planes with a spacing of 0.5 µm were acquired at a time resolution of 3.86 s per stack in fast Airyscan mode with laser power measured using a ThorLabs PM100 optical power meter (ThorLabs Inc.), and maintained across embryos at 3.8 μW for constitutive MCP-GFP/His2A-RFP expression, and 5.0 μW for RNAi analyses. All movies were performed with the following settings: GFP excitation by a 488-nm laser and RFP excitation by a 561 nm were captured on a GaAsP-PMT array with an Airyscan detector using a ×40 Plan Apo oil lens (NA = 1.3) and a 3.0 zoom on the ventral region of the embryo centered on the presumptive ventral midline. Resolution was 512 × 512 pixels with bidirectional scanning. Airyscan processing was performed using 3D Zen Black v3.2 (Zeiss).TM that permits visualization of each analysis step and manual correction if necessary  was expressed as µ +  THR * σ, where µ and σ are the average and the standard deviation of the pixels values of the filtered image respectively, while THR is a user-defined value. The threshold value was in this way rescaled with respect to statistical properties of the filtered image, making THR a value independent of the particular data acquisition. All detected spots were filtered to remove (1) all the spots with a volume less than a user-defined volume threshold, and (2) spots present in only one z-frame. For each time frame, detected spots were associated in 2D to the overlapping or closest nucleus, inheriting the tracking from them; a user-defined distance threshold between nucleus and spot was used in order to avoid mis-associations.GFP puncta representing transcription sites were analyzed in 3D. Because the duplication of DNA occurs relatively early in nc14 and because of the immediate proximity of sister chromatidsFinally, each nuclei-puncta pair passing filtering was described as a time series of intensity, volume, and position. To eliminate intensity variation within the Z-series, spot intensity values were divided by the background fluorescence of the average intensity value of the pixels surrounding the independent spots. Analysis was restricted to the region 25 µm on either side of the center of the gastrulation furrow present at the end of nc14 as positioned using a maximum intensity tile-scan of the entire embryo to determine the coordinate position of the Z-stack. From this data, it is possible to extract: the timing of activation measured as the first timepoint GFP fluorescence crosses the software detection threshold for >1 Z-stack; cumulative activation; intensity profiles for individual nuclei; and individual nuclei burst trajectories. Integral amplitude was calculated using R to determine the surface area under the curve of each individual nuclei and analyzed with Prism (Graphpad 8.0.1) using a Kruskal–Wallis test for significance with multiple comparison adjustments. The calibration method has a minimum detection threshold of >3 transcripts per transcription site. All figures report the number of nuclei and movies used for analysis in figure legends. Movies of genotypes not supplied as Supplementary Movies available upon request.yellow (y) reporter gene were designed using Oligostan85 with FLAP-Y for secondary probe recognition . Probe sequences are provided in Supplementary Table y targeting primary probes were hybridized to the secondary FLAP-Y probes as described83 and maintained at −20 °C in the dark prior to use.Embryos heterozygous for the transgene of interest were fixed in 10% formaldehyde/heptane for 25 min with shaking before a methanol quench and stored at −20 °C in methanol before use. smiFISH probes targeting the −1E. coli tRNA (New England Biolabs), 15% formamide (Sigma), 5-µL probe duplex, 0.2 µg µL−1 RNAse-free BSA, 2 mM vanadyl-ribonucleoside complex (New England Biolabs), and 10.6% dextran sulfate (Sigma) in RNAse-free water. The equilibration mixture was removed and replaced with probe mixture, and embryos were incubated overnight in the dark at 37 °C. The following day, embryos were rinsed twice in equilibration mix and twice in PBT, followed by DAPI staining and three PBT washes before mounting in ProLong Gold mounting media (Life Technologies).Embryos were prepared for smiFISH as briefly follows: embryos were dehydrated with 2 × 5 min washes in 100% ethanol, followed by rehydration in PBT for 4 × 15 min and equilibration in 15% formamide/1 × SSC for 15 min. During equilibration, the smiFISH probe mixture was prepared with a final concentration of 1 × SSC, 0.34 µg µLFixed sample imaging was performed on an LSM 880 with Airyscan module (Zeiss). Z-planes were acquired with 0.20 µm spacing to a typical depth of 80–100 Z-planes from the apical surface of the embryo, using laser scanning confocal in Airyscan super-resolution mode with a zoom of 3.0. DAPI excitation was performed with a 405-nm laser and Cy3 excitation with a 561-nm laser, with detection on a GaAsP-PMT array coupled to an Airyscan detector. Airyscan processing was performed using 3D Zen Black v3.2 (Zeiss) prior to analysis. Embryos were staged based on membrane invagination. Z-stacks were taken at both the center of the presumptive mesoderm as well as at the border region.Images were analyzed . The reporter construct transcript was divided into three sections consisting of the pre-MS2 fragment (41 bp), 24xMS2 loops (1292 bp), and post-MS2 fragment containing the yellow reporter (4526 bp). The retention time was assumed to be small in relation to the time needed to produce a transcript, and so was fixed at 0 s. The temporal resolution of each movie was 3.86 s per frame. This frame rate is sufficient to detect processes that occur on the order of seconds.Before the initiation of the analysis algorithm, several key parameters were established. The Pol II elongation speed was fixed at 45 bp sThe possible polymerase positions were discretized using a step of 30 bp . This step was chosen, as it is smaller than the minimum polymerase spacing and large enough to have a reasonable computation time. For a movie of 35-min length, this choice corresponds to a maximum number of 3150 positions.The algorithm was implemented in Matlab R2020a using Global Optimization and Parallel Computing Toolboxes for optimizing Pol II positions in parallel for all nuclei in a collection of movies. The resulting positions are stored for analysis in the further steps of our computational pipeline. At this step, the density of Pol II initiation events can be visualized by binning time and checking the occurrence of Pol II activation in each bin. This was rendered as a heatmap in which rows represent a single-nucleus time series and the number of activation events per 30-s bin  is indicated by the color Fig. .59.The deconvolution step is common to all of the MS2 data analysis pipelines. A detailed description of the algorithm can be found in ref. Data from several movies corresponding to the same genotype was first pooled together. The entry and exit of each trace corresponding to a unique nucleus were defined using a threshold representing 1/5 of the maximum intensity for the specific trace, in order to restrict the analysis to the stable part of the signal . The regression procedure was initiated with multiple initial guesses and followed by local gradient optimization of the following objective function59:Then, a multiexponential regression fitting produced a set of 2N of exponentials in the regression: we progressively increase N starting with N = 2 until an acceptable regression is reached.The optimization resulted in a best-fit solution with additional suboptimal solutions . A multiexponential regression is considered acceptable if the predicted survival function is within the confidence bounds of the experimental survival function. This provides a method to select the number N − 1 distribution parameters can be computed from the 2N − 1 kinetic parameters of a N-state transcriptional bursting model. Conversely, a symbolic solution for the inverse problem was obtained, allowing computation of the kinetic parameters from the distribution parameters and reverse engineering of the transcriptional bursting model. In particular, it is possible to know exactly when the inverse problem is well-posed, i.e., there is a unique solution in terms of kinetic parameters for any given distribution parameters in a domain.The 259 for a detailed description):The transcriptional bursting models used in this paper are as following . Artificial traces were generated by simulating the model using the Gillespie algorithm with parameter sets similar to those identified from data. The simulations generated artificial polymerase positions, from which a first version of the signal was computed by convolution. The results are provided in Fig. The entire computational pipeline was tested using artificial data . Although relatively small (in terms of the objective function), the resulting errors on short times are large enough to be considered significant by the KS test for all models. In order to be able to distinguish between models, we have limited the analysis to times larger than 10–20 s.A one-sided one-sample Kolmogorov–Smirnov (KS) test was used to check if the waiting times follow the parametric fitted distribution. The output of this test is a Distribution parameters result from multiexponential regression fitting using gradient methods with multiple initial data. These optimization methods provide the best fit  but also suboptimal parameter values. Using an overflow ratio  to restrict the number of suboptimal solutions, we define boundaries of the error interval as the minimum and maximum parameter value compatible with an objective function less than the best-fit times the overflow.The distribution of the postmitotic gap was estimated using the equation below. The fitting suggests that the timescale parameters of the postmitotic gap are even, i.e., 16) or normal serum. A second incubation overnight at 4 °C with Protein G-magnetic Sepharose beads  was used to pull down protein:DNA complexes prior to washing in low salt  and high salt  buffers, elution, incubation with protease K and RNAse A, and DNA retrieval using the QiaQuick PCR cleanup kit (Qiagen). qPCR analysis was performed using Light Cycler 480 SYBR Green I Master Mix (Roche) using primers listed in Supplementary Table Homozygous embryos were collected and fixed in 1.4% formaldehyde for 20 min prior to dry storage at −80 °C. Embryos were dissociated on ice in RIPA buffer  supplemented with protease and phosphatase inhibitors (Roche). Chromatin shearing was performed in a pre-chilled Bioruptor Pico (Diagenode) for five cycles of 30 s/30 s. Samples were divided into equal volumes and incubated overnight at 4 °C with either rabbit anti-Rbp3 (10 μg) or rabbit anti-Nelf-E (10 μg)  using primers listed in Supplementary Table t test to determine significance.To test RNAi-mediated knockdown of Nelf-A expression, 0–2 h embryos were homogenized in Trizol (Invitrogen) and RNA was extracted per the manufacturer’s directions. Reverse transcription was performed using the Superscript IV system (Invitrogen) with oligo d(T)http://www.igmm.cnrs.fr/segment-track/ along with a video tutorial. Code for the mathematical analysis of burst parameters and multiexponential regression fitting is available59.Live imaging analysis software is available at Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2Supplementary Movie 3Supplementary Movie 4Supplementary Movie 5Supplementary Movie 6Supplementary Movie 7Supplementary Movie 8Reporting Summary


PRC2 deposits the H3K27me3 repressive mark, which facilitates transcription repression of developmental genes. The decision of whether a particular gene is silenced at a given point during development is heavily dependent on the chromatin context. More than just a simple epigenetic writer, PRC2 employs several distinct chromatin reading capabilities to sense the local chromatin environment and modulate the H3K27me3 writer activity in a context-dependent manner. Here we discuss the complex interplay of PRC2 with the hallmarks of active and repressive chromatin, how it affects H3K27me3 deposition and how it guides transcriptional activity. They can catalyze histone or DNA modifications (writing) and the removal of already present modifications (erasing) [reading functions of the repressive chromatin modifier polycomb repressive complex 2 (PRC2).Chromatin structure and epigenetic context are crucial regulatory factors for gene expression in eukaryotes. Chromatin modifiers can shape chromatin structure and change epigenetic states in order to change gene expression profiles. These protein complexes have modular functional centers that provide chromatin ‘reader', ‘writer', and ‘eraser' functions . Chromaterasing) . RepressPRC2 is critical for the stable transcriptional repression of polycomb-target genes . PRC2 isAs a chromatin writer, PRC2 catalyzes the mono-, di- and tri-methylation of lysine residue 27 on histone H3, giving rise to the H3K27me1, H3K27me2, and H3K27me3 epigenetic marks, with the latter facilitating transcriptional silencing . While HPRC2 can recognize its own catalytic product, H3K27me3. Binding to H3K27me3 allosterically activates the methyltransferase activity of PRC2 . This mein vitro data showing that PRC2 preferentially modifies neighboring nucleosomes, which requires its allosteric activation [The function of allosteric activation in H3K27me3 domain formation has been studied using mutations in the EED aromatic cage . The auttivation . Cryo-EMtivation ,18. The Besides interacting with its own product, PRC2 also interacts with the catalytic product of the polycomb repressive complex 1 (PRC1) . PRC1 ubAfter initial recruitment to target genes, the synergy between PRC1 and PRC2, promoted by positive feedback loops between H2AK119ub and H3K27me3, maintains transcriptional repression. The mechanisms by which PRC1 and PRC2 are initially recruited to their target genes are still not fully understood. The following sections discuss evidence for a potential function of active chromatin modifications and DNA methylation in restricting PRC2 to its target genes by preventing its recruitment at other genomic contexts.kcat rather than a KM effect, meaning catalysis is affected, rather than substrate binding [Methylation of lysine 36 on H3 is associated with actively transcribed chromatin, and di- and tri-methylation of H3K36 (H3K36me2/3) inhibits PRC2 activity ,26. In v binding . A H3 in binding : A hydro binding . This po binding . Interes binding ,28.A cryo-EM structure of the catalytic core of PRC2 in complex with a di-nucleosome, determined using a PRC2–AEBP2 complex, showed that the H3 tail does interact with EZH2, however the residues around H3K36 could not be resolved . A more A recent study highlighted the relevance of H3K36 methylation for PRC2 regulation in cells . The autin vitro via an aromatic cage that confers methyl-lysine binding specificity [The polycomb-like proteins PHF1, MTF2 and PHF19  are mutually exclusive subunits of PRC2. Both PHF1 and PHF19 have been shown to specifically bind to H3K36me3 cificity . The Tudcificity , but witcificity , and strcificity ,35. PHF1cificity ,35. Simicificity . Collectcificity . Based ocificity .in vivo [Of note, broad co-localisation of PHF1 and PHF19  with H3Kin vivo ,37, whicin vivo ,34. StruThe PRC2–PHF1  and the in vitro [MLL methyltransferases are parts of COMPASS complexes and catalyze the mono-, di- and tri-methylation of lysine 4 on H3 (H3K4me1/2/3), a histone modification associated with active genes (reviewed in ). While in vitro ,25, it hin vitro ).Recent findings clarified the interplay between the H3K4me3 methyltransferase MLL2 (KMT2B) and PRC2 in the regulation of bivalent developmental genes. MLL2 and PRC2 appear to interact competitively. Knockdown of MLL2 in embryonic stem cells leads to accumulation of polycomb group proteins and H3K27me3 at bivalent promoters . As a coWhile negative regulation of PRC2 at H3K4me3-decorated promoters could be attributed to the COMPASS machinery , structu5-methyl-cytosine (5mC) is a DNA methylation catalyzed by DNA (cytosine-5)-methyltransferases (DNMTs). 5mC is largely considered a repressive epigenetic modification that inhibits transcription of target genes (reviewed in ). In embOne structural study suggests that non-methylated DNA is specifically recognized by the winged-helix motif of the polycomb-like proteins MTF2 and PHF1 . Somewhain vitro [The preferred binding of PRC2 to linker DNA in vitro  agrees win vitro . Furtherin vitro . Polycomin vitro . This coin vitro ,64,65.In actively transcribed genes, nucleosomes are partially disrupted by the passing RNA polymerase II (PolII) but are immediately reassembled after PolII passage . During in vitro [Phosphorylation of a serine residue unique to H3.3 (S31) promotes SET2 activity in vitro . In cellin vitro ,75. Thisin vitro [PRC2 is preferentially recruited to CpG islands with low nucleosome density . This obin vitro . There iin vitro . This suSeveral molecular ‘fail-safe' mechanisms prevent PRC2 from establishing H3K27me3 domains at actively transcribed genes. At genes marked for silencing, several positive feedback loops promote PRC2 activity .At actively transcribed genes , PRC2 caWhen transcription is shut off , nascentAfter being seeded, H3K27me3 can spread in three dimensions, allowing it to reach genomic regions that would otherwise be too distant . The H3KThe mechanisms discussed so far suggest that accurate transcriptional control relies on a tight balance between activating and repressive chromatin signals. Upsetting this balance can play an important role in cancer development and progression, which makes chromatin modifiers, including PRC2, attractive drug targets . Here wein trans [Histone variant H3.3 is mutated at residue K36 (K36M) in 95% of chondroblastomas . This muin trans . As discin trans  and restin trans . In agrein trans . This rein trans .Mutations of H3.3 at residue G34 are frequent in paediatric gliomas (G34V/R) ,93 and gin vivo [The H3K27M mutation is found in over 80% of diffuse intrinsic pontine gliomas (DIPG) cases . H3K27M in vivo ,100 and in vivo . Others in vivo . Remodelin vivo .Another work suggests that H3K27M has a long-lasting effect on PRC2 that persists after PRC2 has dissociated from H3K27M-containing chromatin . This streads multiple chromatin signals at a given genomic site and a given point in time. PRC2 then expresses this information by writing its H3K27 mono-, di- and tri-methyl mark in a context-dependent manner. Therefore, the H3K27 methylation at a specific genomic region integrates information about nucleosome density, levels of activating chromatin modifications (H3K4me3 and H3K36me2/3), levels of repressive marks  and transcriptional activity. At a certain point in time, the chromatin state — including all its activating and repressive factors — will set the probability for specific molecular events to take place. Specifically, the presence of H3K27me3 [PRC2 H3K27me3 , exposedH3K27me3 ,41,58, pH3K27me3  and highH3K27me3 ,79–83, hH3K27me3  and presH3K27me3 ,25, highH3K27me3  and H3.3H3K27me3  will lowPRC2 is central to embryonic development and is dysregulated in cancer and congenital disorders. Emerging evidence indicates that PRC2 has the ability to read molecular cues in its surroundings, which in turn regulate its activity.PRC2 is regulated by histone modifications, RNA, nucleosome positioning, chromatin structure, and possibly also DNA methylation and DNA sequence-coded features such as CpG density. These different types of molecular cues allow for context-specific regulation of PRC2.Future development of strategies to alter the reading functions of PRC2 might open paths for epigenetic drugs to target PRC2 in a context-specific manner.


Oct4 promoter.A specific 3-dimensional intrachromosomal architecture of core stem cell factor genes is required to reprogram a somatic cell into pluripotency. As little is known about the epigenetic readers that orchestrate this architectural remodeling, we used a novel chromatin RNA in situ reverse transcription sequencing (CRIST-seq) approach to profile long noncoding RNAs (lncRNAs) in the Platr10 as an Oct4 - Sox2 binding lncRNA that is activated in somatic cell reprogramming. Platr10 is essential for the maintenance of pluripotency, and lack of this lncRNA causes stem cells to exit from pluripotency. In fibroblasts, ectopically expressed Platr10 functions in trans to activate core stem cell factor genes and enhance pluripotent reprogramming. Using RNA reverse transcription-associated trap sequencing (RAT-seq), we show that Platr10 interacts with multiple pluripotency-associated genes, including Oct4, Sox2, Klf4, and c-Myc, which have been extensively used to reprogram somatic cells. Mechanistically, we demonstrate that Platr10 helps orchestrate intrachromosomal promoter-enhancer looping and recruits TET1, the enzyme that actively induces DNA demethylation for the initiation of pluripotency. We further show that Platr10 contains an Oct4 binding element that interacts with the Oct4 promoter and a TET1-binding element that recruits TET1. Mutation of either of these two elements abolishes Platr10 activity.We identify Platr10 functions as a novel chromatin RNA molecule to control pluripotency in trans by modulating chromatin architecture and regulating DNA methylation in the core stem cell factor network.These data suggest that The online version contains supplementary material available at 10.1186/s13059-021-02444-6. Oct4-Sox2-Klf4-c-Myc (OSKM) [Terminally differentiated cells can be reprogrammed into a pluripotent stage known as induced pluripotent stem cells (iPSCs) by using a cocktail of stem cell transcription factors c (OSKM) , small cc (OSKM) , or by nc (OSKM) .Oct4, Sox2, and Nanog, is the culmination of critical epigenetic steps involved in the regulation of cell remodeling [It is now clear that there are strong epigenetic barriers that must be overcome before cells achieve full pluripotency. The initiation of cell reprogramming towards pluripotency requires appropriate expression of the core stem cell factor network , 7. The modeling . Self-reTo explore the mechanisms underlying reprogramming, we compared promoter DNA binding and chromatin architecture between iPSCs that have completed reprogramming and cells we referred to as “non-iPSCs,” which expressed lentiviral OSKM factors, but failed to complete reprogramming . We founin cis or in trans through multiple epigenetic mechanisms, including binding to regulatory elements (promoters and enhancers), inter-and intrachromosomal interactions, histone modifications, DNA methylation, chromatin remodeling [Oct4 promoter. Activation of this master stem cell factor is absolutely required for the establishment and maintenance of pluripotency [Oct4 promoter.Recent studies suggest that long noncoding RNAs (lncRNAs) are important structural components of three-dimensional nuclear architecture , 12. In modeling , and posmodeling . Recentlmodeling . In the ipotency . We hypoOct4 and Sox2 promoters [Platr10 is a lncRNA that is co-expressed with Oct4 and other pluripotency factors [Platr10 in reprograming. We demonstrate that Platr10 is primarily located in the nucleus, where it regulates pluripotency by binding to multiple stem cell core factors, including Oct4, Sox2, Klf4, and c-Myc, four factors that have been used to induce pluripotent reprogramming. Mutation assays demonstrate that Platr10 contains an Oct4 binding element as well as a TET1 binding element, both of which are required for the regulation of stem cell pluripotency and reprogramming.Using this approach, we have identified 27 differentially transcribed RNA candidates that interacted with the romoters . Among t factors . In thisOct4 promoter, a core stem cell factor that is essential for pluripotency maintenance. We hypothesized that components that interact with the Oct4 promoter, particularly those lncRNAs that are specifically transcribed during reprogramming, would participate in the regulation of pluripotency. We used a CRIST-Seq approach [Oct4 promoter  and an IgG immunoprecipitation control (IgG). To define the specific binding of RNAs, CRIST-Seq signal intensities were normalized over that of the non-targeting Cas9 gCT control and the IgG control using parameters of fold change ≥2 and p value < 0.05.We then mapped the RNA network in the Oct4 CRIST-seq data with the CRIST-seq data targeting Sox2 [LncRNAs are critical components of the regulatory chromatin complex. Like chromatin factors, some lncRNAs may regulate multiple gene targets. Thus, we proposed to identify those lncRNAs that bind to multiple pluripotent target genes, assuming that they would play more important roles in pluripotency than those that bind only to a single gene target. Thus, we integrated the above ing Sox2 , a seconOct4 and Sox2 CRIST lncRNA data with the RNA-Seq data  showed the largest fold increment when fibroblasts were reprogrammed into iPSCs. This lncRNA is located on chromosome 3, and RNA-seq data showed that it is specifically expressed in iPSCs  identified by Bergmann et al. [Platrs were clustered tightly with the expression Oct4 and other pluripotency factors. We thus focused on Platr10 and examined its underlying mechanisms in pluripotency.The lncRNA NONMMUT043505 , and “non-iPSCs” that expressed the lentiviral OSKM factors but failed to complete reprogramming. Platr10 expression correlated with pluripotency status, as it was silenced in fibroblasts and transcribed at only a very low level in non-iPSCs. The expression of Platr10 was greatly increased in cells that were fully reprogrammed (iPSCs)  Fig. . Using son Fig. S. The CpGPlatr10 became significantly downregulated during embryoid body differentiation, in parallel with core stem cell factors Oct4, Sox2, and Nanog  and vector control , the copGFP-positive cells maintained the same cell morphology as pluripotent stem cells . The Platr10-deficient cells became enlarged and flat, appearing more like fibroblasts.We also collected cells during embryoid body differentiation. Using quantitative PCR, we found that nog Fig. . We thenol Fig. SB. We exaPlatr10 shRNA knockdown, iPSCs became differentiated and lost the pluripotency-associated marker NANOG . Interestingly, in the shPlatr10 group, there are some “island” cells that escaped lentiviral infection and did not express the shPlatr10-copGFP track marker. These cells served as the “escaped” control and still maintained the original compact shape of iPSCs and expressed NANOG (yellow marked areas without copGFP fluorescence).We then examined the pluripotency of treated iPSCs by immunohistochemical staining of pluripotency-associated marker protein NANOG. The shCT control cells showed extensive expression of the pluripotency-associated marker protein NANOG  and the vector control (Vector) did not affect the activity of core stem cell factor genes , and empty vector (Vector). After puromycin selection, cells were incubated in reprogramming media containing the doxycycline (DOX) inducer and then stained for pluripotent marker NANOG. Compared with the vector (Vector) and DsRed (CTL) controls, ectopic expression of Platr10 was associated with increased reprogramming of MEF cells into pluripotency as quantitated by alkaline phosphatase (AP) staining  showed a change in morphology   Fig. S. Using aPlatr10 might control reprogramming by regulating a target gene network that is associated with pluripotency. To test this hypothesis, we utilized RNA reverse transcription-associated trap sequencing (RAT-seq) [Platr10  <0.1, we identified 416 Platr10 target genes. Ontology analysis showed that Platr10 bound to gene targets belonging to pathways that are closely related to stem cell maintenance and differentiation  , 22 to i10 Figs. . After cion Fig. .Fig. 3GPlatr10 interacts with multiple core stem cell factor genes, including Oct4, Sox2, Klf4, and c-Myc   assay  Fig. SA. After ay Fig. SB. This iOCT4 locus, we previously showed that there is a pluripotency-associated intrachromosomal loop in iPSCs that juxtaposes a downstream enhancer to the gene’s promoter, enabling activation of endogenous stemness genes to achieve reprogramming [Platr10 binds to the same regulatory elements that are known to be involved in chromatin three-dimensional structure, we hypothesized that Platr10 might be a critical factor that orchestrates intrachromosomal looping for reprogramming.Epigenetic remodeling plays a key role in cell-fate conversion. During chromatin remodeling, the genome undergoes major epigenetic alterations to reacquire the euchromatin characteristic of pluripotent cells. By comparing local chromatin structure of the gramming . Since PPlatr10 knockdown cells. Cells were fixed with 1% formaldehyde, digested with restriction enzymes BamH1/BglII, and then ligated with T4 DNA ligase. After reversal of the crosslinks and DNA purification, the chromatin interaction was detected by specific 3C primers located in the promoter and the enhancers of Oct4   to compact4 Fig. .Fig. 4PPlatr10 abolished these intrachromosomal interaction signals and caused the iPSCs to exit from pluripotency. In the control group that was transfected with the shRNA control (shCT), these intrachromosomal loops remained intact. As expected, none of these 3-dimensional interactions were detected in fibroblasts.As previously reported , we deteOct4, respectively  protein sequencing. We found that DNA demethylase TET1 was high on the list of the MS-identified proteins /2-oxoglutarate-dependent dioxygenases, have recently been identified as critical factors that induce the oxidation-deamination mechanism underlying active DNA demethylation in mammals [Nanog promoter accompanied by defects in self-renewal in ESCs [CpG DNA demethylation in the  mammals . Knockdo in ESCs . TET1-in in ESCs .Platr10 to the Oct4 promoter would guide this demethylation process in reprogramming. We used an RNA-chromatin immunoprecipitation (RIP) method to pull down TET complexes in iPSCs. The pulled-down RNAs were reverse transcribed and quantitated by PCR using primers for Platr10. Using this assay, we detected enrichment of Platr10 in the TET1 antibody-precipitated complexes  that are also activated in reprogramming. We did not detect either of these two lncRNAs in the TET1 complex  identified from the RAT-seq dataset. The second TET1 binding site F9 was located at the 3′ end of Platr10.After confirming the role of ET1 Fig. . After cPlatr10 lncRNA was synthesized in vitro using T7 RNA polymerase and biotin-CTP. The biotin-labeled lncRNA was incubated with TET1 recombinant protein. The mixture was treated with RNase A to remove the unbound lncRNA. The TET1-interacting lncRNA fragment was recovered with streptavidin beads, ligated with short RNA library adaptors, reverse transcribed using an adaptor primer, and cloned into pJet vector for DNA sequencing , deletion of a 50 bp Oct4 binding element (OBE50D), deletion of a 58 bp TET1 binding element (TBE58D), and mutation of the 58 bp TBE with a random sequence (TBE58M)  activated these core stem cell factor genes. Deletion of the Oct4 binding element (OBE50) abrogated Platr10 activity. Deletion or mutation of the TET1 binding element abolished Platr10 activity as well.We then performed mutation assays to characterize the function of the identified ) Figs. SA-S16B. Tnog Fig. . NeitherPlatr10 in an Oct4 promoter-luciferase reporter system. The activity of the 4.2 kb Oct4 promoter was measured using a luciferase kit. As compared with the vector control, the full length Platr10 (F1041) activated the Oct4 promoter. In the OBE50D group, deletion of the Oct4 binding element completely abolished the function of Platr10. However, deletion and mutation of the TET1 binding element did not affect the function of Platr10 in this luciferase co-transfection assay . Thus, it is possible that by binding to these chromatin factors, Platr10 lncRNA may coordinate both the methylation status and chromatin looping at the Oct4 locus. Even more interestingly, the RNA pulldown MS protein sequencing data demonstrate that in addition to TET1, Platr10 also binds to DNA methyltransferase DNMT1. This finding suggests that by binding to DNMT1, Platr10 may also regulate stem cell fate by actively coordinating DNA demethylation in many other target genes as identified by RAT-seq. Further studies are needed to address these critical issues.This study demonstrates a previously undisclosed  factors . However factors , 27. Usiter Fig. . HoweverOct4 gene locus, for example, the intrachromosomal looping between the promoter and enhancer regulatory regions is specific for pluripotent stem cells. These intrachromosomal interactions have been demonstrated by several technologies, including 3C, Hi-C, and ChIA-PET [Platr10 was enriched in areas containing these regulatory elements, including the promoter, and 5′- and 3′-enhancers, where pluripotent transcription factors such as Oct4, Sox2, Nanog, and other chromatin factors are found [Platr10 covers huge areas in the promoter, enhancer, or exons. Our RAT-seq data also show that Platr10 binds to many targets that do not belong to the accepted classes of stemness genes. Currently, we are not sure whether those target genes are also involved in the establishment and maintenance of pluripotency. It is likely that Platr10 may have multiple functions in addition to its role of regulating pluripotent genes.At the ChIA-PET . This toChIA-PET . In thisre found , 9, 29. Platr10 is essential for the maintenance of intrachromosomal looping at the Oct4 locus. Knockdown of Platr10 abolishes this intrachromosomal loop structure and causes the exit of iPSCs from pluripotency. In addition to Oct4, the RAT-seq data also demonstrate that Platr10 binds to many other pluripotency-associated genes, including Sox2, Klf4, and c-Myc. These four transcription factors have been widely used to reprogram somatic cells. During reprogramming, Platr10 is actively transcribed and acts in concert with other chromatin factors to coordinate a topological architecture network that is necessary to initiate pluripotency. The Hi-C assay has been used to map the chromatin architecture in human [Oct4 locus. Thus, it will be important to delineate this lncRNA-chromatin interaction in greater detail using a high-resolution approach, like Micro-C, enhanced Hi-C, and Capture-C [We have demonstrated that in human  and mousin human  ESCs. Hoapture-C .Paltr10 recognizes its target genes, like Oct4. By searching the lncRNA-DNA interaction prediction website (LongTarget: http://lncrna.smu.edu.cn/show/DNATriplex) [Platr10 and the Oct4 promoter. To explore this issue, we have performed RNA pulldown-MS sequencing for Platr10 lncRNA. The MS sequencing data show that in addition to TET1, Platr10 also binds to a number of proteins that are involved in covalent chromatin modification, chromatin remodeling, and chromosome cohesion. Thus, it is possible that this lncRNA-chromatin interaction requires the participation of other chromatin factors, like CTCF and Cohesin. In addition, the RNA pulldown-MS sequencing data suggests that Platr10 binds to P53. Thus, it is possible that the nuclear Platr10 may enhance reprogramming, at least partially, by regulating the P53 pathway.Currently, we know very little about how Triplex) , we coulPlatr10 lncRNA also contains a short TBE fragment at its 3′ terminus, which can interact with TET1 demethylase. In fibroblasts, we show that viral expression of the full-length Platr10 upregulates the core stem cell factor genes Oct4, Sox2, and Nanog. When this TBE element was deleted or replaced with a 58 bp random RNA, the Platr10 mutants completely lose activity. These data suggest that the binding of TET1 demethylase may be an important step to activate core stem cell factor genes during the initiation of pluripotent reprogramming. It should be noted that in addition to its activity to catalyze hydroxylation of 5-methylcytosine to generate 5-hydroxymethylcytosine in DNA, recent studies show that TET1 and TET2 are also critical for RNA hydroxymethylation [Platr10. It is not known if all TET1-interacting RNA molecules have a consensus motif like the Platr10 TBE.hylation . The TETPlatr10 appears in both fRIP-seq and CLIP-seq databases. Using RNA pulldown-MS protein sequencing, we also detected the binding of Platr10 with multiple stemness markers, including SOX2. Thus, it would be interesting to examine if in addition to the role in coordinating intrachromosomal loop at the Oct4 locus, Platr10 lncRNA may regulate pluripotency through modulating the activity of these pluripotent markers at the post-transcriptional level.In addition to the TET family, a recent study by Holmes et al.  showed tPlatr10 in both the induction of cell reprogramming and the maintenance of pluripotent status in iPSCs. As a lncRNA, Platr10 does not encode a known pluripotent factor. However, it regulates pluripotency using unique mechanisms that cannot be fulfilled by pluripotency-associated protein transcription factors. Specifically, it helps maintain a pluripotency-specific chromatin architecture in the Oct4 promoter. By binding to the Oct4 locus, it facilitates a functional juxtaposition between the two Oct4 regulatory regions. With this intrachromosomal loop, the distal enhancer element is moved in close juxtaposition to the promoter, activating this stem cell core factor gene. After binding to Oct4, this lncRNA recruits the DNA demethylase TET1, which induces demethylation of the Oct4 promoter as an essential step to initiate reprogramming. By coordinating the necessary chromatin architecture and DNA demethylation, Platr10 may play an essential role in initiating pluripotency during reprogramming  were cultured from fetal mice, and MBW2 fibroblast-like cells were cultured from M. spretus-Balb/c F1 mouse bone marrow mesenchymal stem cells , and werOct4 promoter (Oct4-gRNA1: 5′-GAACATTCAATGGATGTTTT-3′ and Oct4-gRNA2: 5′-GTGTGAGGGGATTGGGGCTC-3′), respectively. The expression cassette was inserted downstream of the U6 promoter in the CRIST targeting vector. The same strategy was used to construct the Cas9-Sox2 gRNA vector. The Sox2 promoter guiding RNAs include: Sox2-gRNA1: 5′-GGGGTTGAGGACACGTGCTG-3′ and Sox2-gRNA2: 5′-GAGCCAATATTCCGTAGCAT-3′). A CRIST-Seq control vector was constructed using a Cas9 random gRNA (Cas9-gCT): GTGCGTTGTTAGTACTAATC.CRIST-Seq was performed to identify lncRNAs that bind to the Oct4 and Sox2 promoters Fig. S. SpecifiOct4-Sox2-Klf4-c-Myc-GFP (OSKMN) as previously described [-4 M non-essential amino acids [Reprogramming of mouse fibroblasts into iPSCs was performed by lentiviral escribed . Brieflyno acids . The selno acids . The fibno acids , 18.Oct4 promoter-interacting lncRNAs as descried [Oct4 promoter-interacting lncRNA, cells were cross-linked with 2% formaldehyde and were lysed with cell lysis buffer . Nuclei were collected by centrifugation and were suspended in 1× reverse transcription buffer in the presence of 0.3% sodium dodecyl sulfate (SDS) and incubated at 37°C for 1 h. Triton X-100 was then added to a final concentration of 1.8% to sequester the residual SDS. An aliquot of nuclei (3×106) was reverse transcribed at 37°C for 30 min in a 20-μl reaction containing 1μl random hexamer, 1μl 10 mM dNTP, 1μl 0.4 mM dCTP -biotin, 1μl RT enzyme, 0.5μl RNase inhibitors, 1μl 0.1M DTT, 4μl 5× cDNA synthesis buffer, 1μl Maxima Reverse Transcriptase, and RNase-free water to 20μl. The reaction was stopped by adding 4μl 0.5M EDTA. After nuclear lysis, the chromatin complex was subjected to sonication for 180 s (10 s on and 10 s off) on ice using a Branson sonicator with a 2-mm microtip at 40% output control and 90% duty cycle settings. The biotin-labeled cDNA/Cas9 complex was immunoprecipitated with anti-FLAG antibodies . The DNAs were released after cross-linking reversal and proteinase K treatment and were precipitated with ethanol. The biotin-labeled cDNAs were further purified from genomic DNAs with M-280 streptavidin beads . After purification, the Oct4 promoter-interacting cDNAs were quantitated by PCR using target gene primers . The double-strand cDNAs were digested by Dpn I for library construction by ligating with the NEBNext adaptors (NEBNext® ChIP-Seq Library Prep Master Mix Set for Illumina). Triplicate library DNAs were sent to Shanghai Biotechnology (Shanghai) for Illumina sequencing.For CRIST-Seq control, we performed a CRIST assay using a random gRNA (gCT) and constructed the control library for sequencing using the same protocol. An anti-IgG antibody was used as the background control for immunoprecipitation .http://hannonlab.cshl.edu/fastx_toolkit/index.html). After filtering, clean reads were mapped to the mouse genome  for mRNAs and lncRNAs using TopHat (version:2..0.9) software [p value < 0.05, with false discovery rate (FDR) <0.1. The adjusted CrIST-Seq data were then used for mapping the Oct4 and Sox2 RNA interactions [After CRIST sequencing, the adapter sequences were removed from the raw data using Illumina annotated adapter sequences with parameter ILLUMINACLIP: 2:30:10 and the low-quality data were filtered using Fastx software (software . The mapractions .ftp://ftp.ensembl.org/pub/release-83/fasta/mus_musculus/dna/Mus_musculus.GRCm38.dna.primary_assembly.fa.gz) for mRNAs and lncRNAs using the STAR software. Gene counts were normalized to the values of reads per kilobase of transcript per million mapped reads (RPKM). Cuffdiff was used to calculate the differentially expressed RNAs when the fold-change was > 2 and p < 0.05 with an unpaired two-sided t test [Total RNA was isolated from fibroblasts and iPSCs  using TRd t test .p<0.05. CRIST-Seq RNAs were selected by peak enrichment FPKM>50 as a cut-off threshold after adjusting over the IgG control and Cas9-gCT control. The RNA-Seq data were merged with the Oct4 and Sox2 CRIST-Seq data using VENN program (http://bioinformatics.psb.ugent.be/webtools/Venn/). Venn diagrams were used to visualize the overlap RNAs between the datasets. The overlapping RNAs identified by the datasets were chosen for further functional characterization.Reprogramming-associated RNA candidates were identified by RNA-Seq using a cutoff threshold of >2-fold, Platr10 cDNA, our PCR products indicated that the lncRNA underwent alternative splicing. Therefore, we characterized Platr10 lncRNA by cDNA 5′- and 3′-RACE following the method as previously described [Platr10-specific primer SJ938: 5′-CTGTTGAGC CAGGCAGCTG-3′. The PCR DNAs were diluted 500-fold and were used for the second nested PCR using 3′-RACE primer SJ772: 5′-GACTCACTATAGGAGACAGGCTCGA-3′ and a 5′-Platr10-specific primer SJ937: 5′-AGCTGGAGGAAGTGTGTCAC-3′. The racing PCR bands were cut and cloned into pJet vector for sequencing.During the cloning of full length escribed . For thePlatr10-specific primer SJ935: 5′-TCATGTCCGGGTTCGAGCCT-3′. The PCR bands were cloned into pJet vector for sequencing.For the 5′-racing, the iPSC RNAs were reverse-transcribed using Maxima Reverse Transcriptase with random hexamer oligonucleotides for 30 min. The poly G primer SJ774: 5′-CCAGATTCAGGACTGTCGACATCGAATTCGGGG-3′ was added into the mixture and the reaction was continued for another 30 min. After 10-fold dilution, cDNAs were amplified with 5′-adapter RACE primer SJ775: 5′-GATTCAGGACTGTCGACATCGA-3′ and Platr10 [Platr10-specific complementary primers in the presence of biotin-dCTP. After 50 min of reverse transcription of Platr10 lncRNA with Maxima Reverse Transcriptase  at 62C, the reaction was stopped by adding 4μl 0.5M EDTA. After nuclear lysis, the chromatin complex was subjected to sonication for 180 s (10 s on and 10 s off) on ice with a Branson sonicator with a 2-mm microtip at 40% output control and 90% duty cycle settings. The biotin-labeled cDNA/chromatin DNA complex was pulled down with biotin-streptavidin magic beads . After reversing the cross-links and washing with 10 mg/ml proteinase K at 65°C overnight and treatment with 0.4 μg/ml RNase A for 30 min at 37°C, the genomic DNA that interacted with Platr10 was extracted and digested by Dpn I, and ligated with the NEBNext adaptors (NEBNext® ChIP-Seq Library Prep Master Mix Set for Illumina) to construct the library. Triplicate library DNAs were sent to Shanghai Biotechnology for Illumina sequencing.A RAT assay was modified to map the genome-wide interacting target genes for Platr10 . SpecifiPlatr10 complementary primers with random primers and constructed a control library for sequencing using the same protocol.For RAT-Seq control, we performed a RAT assay by replacing http://hannonlab.cshl.edu/fastx_toolkit/index.html). Clean reads were mapped to the mouse genome (genome version: mm10) using the Bowtie (version:0.12.8) software with default parameters. Enriched regions of the genome were identified by comparing the RAT-Seq peaks to input samples using MACS2 (version:2.1.1), and q value of 0.05 was used as the initial cutoff threshold to minimize peak caller bias. The upstream 2k of the transcription start sites and the downstream 5k of the transcription termination region were defined as the gene regions. The significant GO terms of biological processes with a p value < 0.05 were selected. We also used the MEME suite [p value < 0.05, with false discovery rate (FDR) <0.1. The adjusted RAT-Seq data were used for mapping the lncRNA target gene interaction network [After RAT sequencing, the low-quality reads were filtered using Fastx (version:0.0.13) software  from cells and stored at −80°C. RT-PCR reaction was performed with a Bio-Rad Thermol Cycler. The target amplification was performed by PCR of 1 cycle at 95°C for 5 min; 33 cycles at 95°C for 20s, 62°C for 15s, and 72°C for 15 s; and 1 cycle at 72 °C for 10 min.Quantitative real-time PCR was performed using SYBR GREEN PCR Master  as previously described , 46. ThePlatr10 cDNA as the template, PCR primer JH4022: 5′-CACTGCTGGTTTGGAGCTCCAT-3′ and JH4023 5′-TGGGACAGTCTCTGGATGGCCT-3′ in a ratio of 1:50, with dig labeling dNTP MIX (Roche:11277065910). PCR probe products were purified by electrophoresis on 2% agarose gel and eluted in 20 μl TE buffer. For hybridization, 0.1 μg ssDNA probe and 10 μg salmon sperm DNA  were precipitated with ethanol and suspended in 10 μl RNA hybridization buffer , and 2mM VCR, 10% formamide). Slides were counterstained with DAPI and FISH signals. Images were captured and merged to confirm subcellular localization.RNA FISH was performed by a modification of the method as previously described . The RNAPlatr10 was knocked down by two separate shRNA lentiviruses. The shRNA vector was constructed by cloning four shRNAs into a pGreenPuro vector  under the control of the H1 and U6 promoters. Vector 1  contained shRNA #1: 5′-TTCTGTGTATCTGTTGAGCCAG-3′ and #3: 5′-CTGCCAGCATCTGACTAAGATA-3′. Vector 2 (shPlatr10-2) contained shRNA #2: 5′-CCTGCTGCCTGTCAATCCAAAT-3′, and #4: 5′-CCTGCTGCCTGTCAATCCAAAT-3′  and the pCMV-DsRed-Puro CTL (800 bp random sequence). OG2 MEFs were first transfected with the Platr10 and control lentiviruses and were selected by puromycin. MEFs were reprogrammed following the method as described [escribed . BrieflyImmunofluorescent staining was used to examine stem cell markers in iPSC colonies . BrieflyFor embryoid body (EB) formation, iPSCs or E14 cells were dispersed by collagenase IV (Invitrogen), and cell clumps were transferred to 60-mm dishes in ES medium without LIF. After being maintained in floating culture for 3 days, EB were seeded in 0.1% gelatin-coated 6-well plates in DMEM/F12 containing 20% FBS for spontaneous differentiation. Cells were collected at different time points and used for gene expression analysis using quantitative PCR.Platr10-binding proteins were mapped by RNA pull-down mass spectrometry sequencing . Sense biotin-Platr10 lncRNA was synthesized by T7 RNA polymerase using Biotin RNA Labeling Mix, treated with RNase-free DNase I, and purified with RNeasy Mini Kit (Qiagen). Antisense bitoin-Platr10 RNA was used as the control. Both strands were used to pull-down target proteins. Differential protein bands were excised and analyzed by mass spectrometry. Fragment sequences from MS were performed using PEAKS 7 at a false discovery rate (FDR) threshold of <5%. Platr10-bindnig proteins were mapped after adjusting over the signal of the antisense RNA as the PEAKS score (−10logP).Platr10 lncRNA. Briefly, iPSCs were fixed with 1% formaldehyde, treated with DNase I, and sonicated using a Branson sonicator. Sonicated samples were immunoprecipitated with antibodies against TET1 and TET3 . IgG was used as the experimental control. The precipitated RNA was released, and cDNA was synthesized. After proteinase K treatment, the TET-binding cDNAs were detected by PCR.A lncRNA-affinity binding precipitation assay (RIP)  was perfTo map the TET1 binding fragment, a longer sonication was used by extension to 30 min. The samples immunoprecipitated by the IgG antibody were used as the RIP control. The RIP samples were quantitated by overlapping qPCR primers  with biotin-CTP. The biotin-Platr10 lncRNA was purified using Streptavidin Magnetic Beads  following the protocol provided by the manufacturer. For TET1 binding mapping, biotin-Platr10 lncRNA (5 ng/μl) was incubated with TET1 recombinant protein (150 nM) in 150 μl Buffer  at 22°C for 10 min. After binding, 2 ng/μl RNase A was added to the reaction mixture and was incubated at 22°C for 5 min to remove the RNAs that were unbound or free from the TET1 binding. After RNase treatment, 500 μl TRIzol  was added to quench the digestion, and RNAs were purified following the manufacturer’s protocol. An RNA library was prepared using NEBNext Multiplex Small RNA Library Prep Set for Illumina . RNA library products were purified by gel extraction and were cloned into a pJet vector for DNA sequencing. The sequencing reads were aligned with the Platr10 lncRNA sequence to locate the consensus TET1 binding motif. The RNA motif structure of TBE was obtained by submitting the 58 bp consensus sequence to the RNA structure prediction website: https://rna.urmc.rochester.edu/RNAstructureWeb/Servers/Predict1/ResultsPages/20180916.191929-72078a8d/Results.html.An RNase A protection assay  was used6) was digested with 800 U BamH I/Bgl II at 37°C overnight. Chromatin DNA was diluted with NEB ligation buffer and ligated with 4000 U of T4 DNA ligase. After reversing the cross-links, DNA was purified and used for PCR amplification using primers that are derived from different regions of the Oct4 locus. The 3C PCR products were cloned and sequenced to validate the intrachromosomal interaction by checking for the presence of the BamH I/Bgl II ligation site. Each intrachromosomal loop had its own negative control site. The 3C interaction was quantitated by qPCR and was standardized over the 3C ligation control for the housekeeping gene Ercc3. For comparison, the relative 3C interaction was calculated by setting the 5′ or 3′ control as 1.The 3C assay was performed to determine long range intrachromosomal interactions . BrieflyPlatr10 and its mutants and were treated with sodium bisulfate. Methylation PCR was performed, and PCR DNAs were cloned into pJet vector for sequencing. After treatment with sodium bisulfate, unmethylated cytosines were converted to uracils, which can be distinguished from the methylated cytosines by sequencing.Genomic DNAs were extracted from fibroblasts that express the full length Platr10 lncRNA, we constructed a series of lentiviral vectors that express the full length Platr10 and its mutants. The full-length Platr10 was amplified from iPSC cDNAs using primers JH4399 5′-CGCGTCGATATCCTCGAGGGAGCCTACACGTGGTCACCTG-3′ and JH6209 5′-GAATCGAAGAATTCGCATGGCAGCATGAAGGCAGACAT-3′. The OBE50D vector was synthesized by overlapping PCR using primers JH4399 and JH6212 5′-GGAAGAATCACAAGTCTGTGTTTCCTTCTCCGGTATGAAT-3′ for PCR fragment 1, and JH6213 5′-AGGAAACACAGACTTGTGATTCTTCCCATCTGCAGA-3 and JH6209 for PCR fragment 2. To construct TBE58D vector, the Platr10 insert was amplified by primers JH4399 and JH6214 5′-GAATCGAAGAATTCGTCGACAGGAAAACATTTTATTTGGGCTGGC-3′. The TBE58M vector was constructed by a two-step PCR using primers JH4399 with primer JH6210 5′-CAGTATCTGATCTACTATGTAGCATAAGATCATCAGTCCAGCATGGCAGCATGAAGGCAGACAT-3′ and JH6211 5′-GAATCGAAGAATTCCAGAGGATCATCCCACTTCAGTATCTGATCTACTATGTAGCAT-3. All PCR inserts were cloned into a lenti-DsRed vector by EcoRV/EcoR1.To define the function of The lentiviruses were packaged in 293T and were used to transfect fibroblasts. After transfection, cells were treated with puromycin, and stable cells were used for the measurement of gene expression of Oct4, Sox2, and Nanog.Platr10 in activating the Oct4 promoter was first examined in 293T cells by using a dual-luciferase reporter assay. A 3.9 kb genomic DNA fragment covering the Oct4 promoter and part of the exon 1 sequence was amplified by PCR using primers: SJ559 5′-TATCGATAGGTACCGTCTGTGAGGAGGTGGCTGAACT-3′ and SJ560 5′-atcgcagatCTCGAGCTCCTCGGGAGTTGGTTCCAC-3′. The DNA fragment was cloned into pGL3 vector by Kpn1/Xho1.The function of 4 cells/well in 96-well plates. The lentiviral expression vectors, including Platr10 full length lncRNAs (F947), OBE50D, TBE58D, and TBE58M were co-transfected with a pOct4-luciferase plasmid and Renilla luciferase control plasmid (Promega) using Lipofectamine 3000 . The empty lentiviral vector was used as the control. Forty-eight hours after transfection, firefly and Renilla luciferase activities were measured with the dual-luciferase reporter system (Promega) using a luminometer . The relative activity of the Oct4 promoter was calculated by standardized setting the untreated control cells as 1. All luciferase assays were repeated three times.For the luciferase assay, cells were seeded at a density of 5 × 10t test or one-way ANOVA (Bonferroni test) was used to compare statistical differences for variables among treatment groups. Results were considered statistically significant at p<0.05.The data were expressed as mean ± SD and were analyzed using SPSS software . Student’s Additional file 1:. Supplementary files include the Methods and additional Extended Data.Additional file 2:. Review history


E. coli F18 infections in piglets. However, the underlying molecular mechanism concerning the resistance of E. coli F18 in local weaned piglets in China is not clearly understood. In the present study, by a comparative analysis of the transcriptome, a-1,3-fucosyltransferase (FUT3) was evaluated as a key candidate correlated with resistance to E. coli F18 in Sutai and Meishan piglets. Functional analysis demonstrated that FUT3 acts as a key positive regulator of E. coli F18 susceptibility in newly food accustomed piglets. However, the core promoter of FUT3 was present at −500–(−206) bp (chr.2: g.73171117–g.73171616), comprising of 9 methylated CpG sites. Among these, the methylation levels of the two CpG sites  located in HIF1A and Sp1 transcription factor (TF) considerably associated with mRNA expression of FUT3 (p < 0.05). Our findings indicated that the methylation of mC-3 and mC-5 sites has certain inhibitory effect on FUT3 expression and promotes the resistance of E. coli F18 in piglets. The underlined study may explore FUT3 as a new candidate target in E. coli F18 infection in Chinese local weaned piglets.Post-weaning diarrhea (PWD) is frequently associated with  Among these, 5-mC is the most important methylation modification in mammals. DNA methylation is the main epigenetic mechanism in promoter regions of the eukaryotic genomes that regulate the expression of a gene by enhancing or attenuating the interaction of TF with sequences of DNA in the promoter region [DNA methylation widely existing in mammals can regulate gene expression and maintain genetic stability with transcription and cell division. Under the catalysis of DNA methyltransferase (DNMTs), S-adenosyl-L-methionine (SAM) as methyl group is added to DNA segments and is converted to 5-methylcytosine (5-mC), Nr region . It has r region ,3,4. DNAr region , growth r region ,10,11, ir region ,13. HoweEscherichia coli F18 (E. coli F18) is the main pathogenic microbe that results in post-weaning diarrhea [E. coli F18 in the small intestine of a piglet at the brush border of the epithelial cell, are potentially associated with the pathogenicity of E. coli F18 in terms of their expression levels. In addition, the mechanism being involved in E. coli F18 resistance in Chinese local weaned piglets still remains undiscovered. In this study, based on previously obtained Sutai (a new crossbred between Meishan and the Duroc strains) and Meishan piglets, i.e., resistant and sensitive to E. coli F18 [FUT3), that may have critically contributed in anti-E. coli F18 infection. FUT3, belonging to the fucosyltransferase family, regulates the formation of ABH and Lewis antigens and resistance to pathogen infection [FUT3 expression in regulating E. coli F18 resistance, this study systematically verified the linkage between the expression of FUT3 and infection of E. coli F18 at the tissue and cellular levels. Then, the FUT3 core promoter was determined by bioinformatics analysis and dual-luciferase assay, meanwhile, bisulfite amplicon sequencing (BSAS) was used to detect the level of methylation in FUT3 core promoter in intestinal tissues of piglets, i.e., sensitive and resistant to E. coli F18. Then we determined the impact of the methylation sites on the expression of FUT3 mRNA and evaluated considerable transcription factor in the core promoter region. Hence, this study conformed a candidate target for combating vulnerability to E. coli F18 in weaned piglets and further revealed the effect of DNA methylation on gene expression. Our findings aim to provide insights into the molecular mechanism of piglets’ anti-E. coli F18 infection and providing the basis for solving the key scientific problem of E. coli-resistant disease breeding in Chinese local pigs.Piglets’ bacterial diarrhea is one of the most common intestinal inflammatory diseases that leads to severe financial damages to pig farming on large scale. Enterotoxigenic diarrhea . Howevercoli F18 ,16, we cnfection ,18. To fE. coli F18 resistance in local pig breeds in Chinese indigenous pigs, we conducted a comparative RNA-seq analysis of duodenal tissues from Sutai and Meishan piglets exhibiting sensitivity or resistance to E. coli F18. In Sutai piglets, 238 differentially expressed genes (DEGs) were screened out between piglets that were sensitive or resistant to E. coli F18 | <2 (FUT3) is involved in glycosphingolipid biosynthesis (KO pathway: ko00601) correlated with the generation of E. coli F18 receptor [E. coli F18 infection in piglets.To determine the molecular mechanism of regulating nge)| <2 a. Likewinge)| <2 b. Interenge)| <2 c,d. Amonreceptor ,20,21, wFUT3 and E. coli F18 susceptibility in pigs, we analyzed the differential mRNA and protein expression of FUT3 between piglets that were sensitive and resistant to E. coli F18. qPCR evaluation revealed that the FUT3 gene’s expression level was considerably elevated in the duodenum and jejunum of piglets that were sensitive to E. coli F18 relative to those that showed resistance (p < 0.01), as depicted in FUT3 was significantly upregulated in a sensitive group, as depicted in To analyze the correlation between the expression of FUT3 regulated E. coli F18 invasion, the lentivirus-activated RNAi was used to facilitate the attenuation of FUT3 in the intestinal porcine epithelial cells (IPEC-J2). The expression of a GFP was determined in more than 90% of cells treated with shRNA vector. As indicated in FUT3 in shFUT3-n  treated IPEC-J2 cells were 39.9%, 71.6%, 23.1%, and 86.9%, accordingly, relative to non-treated cells (control) and shFUT3-4 treated IPEC-J2 cells were considered for the successive evaluation. The level of Protein expression showed consistency with transcription levels . Immunofluorescence assay bp, –1297 –(–1247)bp, –1848–(–1798)bp upstream of the transcription start site. Then, the 2000-bp upstream sequence was divided into four fragments, namely, –200–0 bp (control), –500–0 bp (P1), –1500–0 bp (P2), and –2000–0 bp (P3)  than that of the other transfected groups. We identified that the core promoter region of FUT3 was found at –500–(–200) bp (chr. 2: g.73171117–g.73171616). Based on sequence, we designed the methylation amplification region (To further investigate the molecular mechanisms of  bp (P3) a. Agarosn region d using tFUT3 promoter in intestinal tissues of individuals that were resistant and sensitive to E. coli F18 via bisulfite amplicon sequencing (BSAS). As shown in FUT3 core promoter. On the whole, the average methylation levels in the duodenum (78.25%) and jejunum (86.63%) tissues from E. coli F18-resistant individuals were considerably elevated than that in the duodenum (72.20%) and jejunum (75.15%) tissues from E. coli F18-sensitive individuals (p < 0.05). From single CpG sites, the methylation levels of mC-5 and mC-6 sites in intestinal tissues from individuals that were resistant to E. coli F18 have considerably elevated than that from E. coli F18-sensitive individuals , with considerable correlation coefficients being attained only for the mC-3 , mC-5  and mC-6 sites , indicating the methylation of CpG- sites probably inhibit FUT3 mRNA expression.Furthermore, we conducted the methylation analysis of the FUT3 expression, we presented the potential transcription factor binding sites (TFBS) found within CpG sites in the core promoter region of pig FUT3 genes, such as SP1, HIF1A, AP2, USF, C/EBPα, and CREB  as a candidate target to battle the susceptibility to E. coli F18 in Chinese local piglets. FUT3 belongs to the family of fucosyltransferase genes and was found to be associated with the mediators of gastrointestinal disease, rotavirus, and bacterial infection [FUT3 expression on E. coli F18 resistance in piglets, qRT-PCR and immunoblotting were carried out to validate the differential expression of FUT3 in intestinal tissues of piglets that were resistant and sensitive to E. coli F18. The obtained results indicated a considerably downregulated expression in piglets that were sensitive to E. coli F18. Moreover, we performed an in-vitro functional analysis of the E. coli F18 adhesion via RNA interference, followed by demonstrating that FUT3 knockdown markedly enhanced the E. coli F18 adhesion level to intestinal porcine epithelial cells (IPEC-J2). Therefore, it can be speculated that FUT3 expression was involved in the formation of the E. coli F18 receptor and functioned as a positive regulator of enhancing the susceptibility to E. coli F18 in piglets.To date, no study has assessed the athogens ,23. In a piglets . Accordie-1 core ,20. ABH e-1 core . Herein,nfection ,26. To iFUT3 expression alterations in E. coli F18 infected pigs, the methylation of the FUT3 core promoter region in the jejunum and duodenum tissues of piglets (sensitive and resistant to E. coli F18) were evaluated through methylation sequencing. Promoters are often located at 5′flanking regions, DNA methylation in the regions is considered to be the most obvious epigenetic gene expression regulation. In common, the variations in DNA methylation take place in the CpG [FUT3 gene and observed that there were no CpG islands in this region. In this view, we evaluated the luciferase assay of the successively 5’-shortened sections of FUT3 promoter for the determination of the sequence in the core promoter region (–500–(–200)bp). Our studies showed the higher methylation levels in intestinal tissues of piglets (resistant to E. coli F18) and were found to be exhibited a significant negative correlation  between the average methylation level and the expression of mRNA, indicating that FUT3 methylation may inhibit its expression and enhance the immunity of piglets against E. coli F18 infection. Furthermore, multiple studies have revealed that the occurrence of many CpG sites in the promoter region of a particular gene, but some specific CpG sites can affect gene expression [FUT3 core promoter (p < 0.05). In view of these observations, the underlined sites might significantly regulate the transcription of the gene. DNA methylation modulates transcriptional factor (TF) activity by regulating TF binding sites (TFBS) located in the regions with specific CpG sites, leading to the activation or inhibition of gene transcription [FUT3 promoter CpG sites, which belongs to the methylation-dependent transcription factors and include hypoxia-inducible factor (HIF)-1α (HIF1A) [FUT3 expression were located in HIF1A, SP1, and USF, respectively. The dual-Luciferase assay showed, HIF1A and SP1 could promote FUT3 transcriptional activity, while USF caused the inhibition of transcriptional activity. Taken together, we revealed that the elevated level of methylation at mC-3 and mC-5 regions overcome the SP1 and HIF1A binding potencies to the FUT3 promoter to suppress the gene expression. In future studies, there is a need for validation of HIF1A and SP1 binding to the FUT3 promoter via electrophoretic mobility shift assays (EMSA) and chromatin-immunoprecipitation (ChIP), meanwhile, we will explore in-depth the function of a key transcription factor by RNA overexpression and CRISPR/CAS9-knockout.To further extensively evaluate the mechanisms that regulate the  the CpG ,11,22, apression . Analyse (HIF1A) , specifi (HIF1A) ,30, cAMP (HIF1A) , upstrea (HIF1A) , CCAAT/eFUT3 as a key target for combating susceptibility to E. coli F18 in Chinese local pigs based on comparative transcriptome analysis. Functional verification indicated that the low expression of FUT3 was linked with resistance to E. coli F18 in piglets. Besides, we determined the FUT3 core promoter region (–500–(–200 bp) by bioinformatics analysis and luciferase assay. Methylation analysis showed, two key CpG sites  probably decreased the binding activity of HIF1A and SP1 to the promoter of FUT3 for the inhibition of gene expression. Our obtained results may explore the regulatory mechanism of the pig FUT3 gene that affects resistance to the infection caused by E. coli F18 and involved in its application in molecular breeding against bacterial diarrhea in local piglets of China.In conclusion, the present study identified The IACUC of Yangzhou University provided approval for all animals conducted studies, under the permit number: SYXK (Su) IACUC 2012-0029. All piglets related experiments were conducted on the directions of administration and regulatory affairs regarding the approval of Experimental Animals by the State Council of the People’s Republic of China.E. coli F18 by challenging with the E. coli through feeding strains, i.e., F18ab and F18ac [E. coli F18) with similar birth weight, coat color, the shape of the body and weaning weight were chosen for the analysis of RNA-seq. All experimental piglets were euthanized via intravenous injection of pentobarbital sodium and duodenum, liver, heart, spleen, kidney, lung, stomach, kidney, muscle, lymph node, thymus, and jejunum tissues were collected, followed by storing in liquid nitrogen in situ for further use.Experimental pigs  were acquired from Kunshan Conservation Ltd. and Sutai Pig Breeding Center. In the previous study, the model animals, i.e., weaning piglets were used to check their vulnerability to nd F18ac . Based ond F18ac , three p® Ultra™ II Directional RNA Library Prep Kit (USA), as suggested by the manufacturer. Libraries quality and quantification were carried out via the BioAnalyzer 2100 system (USA). RNA Sequencing was conducted at the Novogene Bioinformatics Institute  on an Illumina Hiseq 2500 platform and 100 bp paired-end reads were constructed. The obtained raw RNA-seq data (high-throughput) were submitted to NCBI .Total RNA of duodenum tissues from 6 Meishan piglets  and 6 Sutai piglets  was isolated by TRIzol™ reagent  on the basis of suggestion provided by the manufacturer. The removal of rRNAs from total RNA was carried out via NEBNext rRNA Depletion Kit (USA), as suggested by the manufacturer. Libraries of RNA were formed via the NEBNextp < 0.05 and |log2(fold change)| > 1.Paired-end reads were collected from Illumina HiSeq 2500 sequencer, and their quality was controlled via Q30. Post 3′ adaptor-trimming and reads  removal by cutadapt (version 1.9.3), the clean reads with higher quality were aligned to the reference genome (SusScr11) with the software, i.e., hisat2 (version 2.0.4). Then, the cuffdiff software was employed to obtain the gene level FPKM as the expression profiles of mRNA, and a threshold for considerably variant expression was set as a FUT3 mRNA  and one off-target control (NC) sequence were designed  were grown in medium, i.e., DMEM/F12 in a 1:1 ratio provided with FBS (10%). For the IPEC-J2 control (Control), FUT3 knockdown cells (shFUT3), in vitro evaluation of F18ab fimbriae standard strain 107/86 (O139:K12:H1) and F18ac (8199) adhesion was performed as explained earlier . To estan method , bacterin method  were use2O. RT-qPCR instrument ABI7500 was employed for the evaluation of qPCR and the parameters were set as 95 °C for 30 and 5 s, accordingly, followed by 60 °C for 34 s, and then 40 cycles were carried out. The primers of amplified fragments of FUT3 and β-actin were indicated in Total RNA from IPEC-J2 cells and tissues was isolated with the help of Trizol Reagent. The purity, as well as total RNA concentration, were evaluated via agarose gel electrophoresis in formaldehyde (1%) and NanoDrop 1000 (USA), then RNA was kept at −70 °C. Synthesis of cDNA was carried out via 1 µL of 5 × qRT SuperMix II along with total RNA of 500 ng, and 10 µL of RNase free ddHFUT3 gene was obtained by NCBI and UCSC database. The prediction of CpG islands of the pig FUT3 upstream region was performed via the MethPrimer software. Besides, the prediction of the FUT3 core promoter region was carried out via BDGP software. Based on the above bioinformatics analysis, the 2000-bp upstream sequence was designed for the amplification of various promoter fragments truncated at the 3′ end of the sequence. Then, the resulted PCR products were evaluated via agarose gel electrophoresis, then sequencing was carried out. Recombinant vectors were labeled as FUT3-200bp (Control), FUT3-500bp (P1), FUT3-1500bp (P2), FUT3-2000bp (P3), and then co-transfected with pRL-TK vector into cells for dual luciferase assay.The 2000-bp upstream sequence of the transcription start site of pig 2O. The subsequent reaction conditions were as follows: 95 °C for 10 min, then 35 cycles of 95 °C for 30 s, 52 °C for 30 s, 72 °C for 35 s, and 72 °C for 10 min. The TIANquick Midi purification kit  was utilized for the purification of PCR products (209 bp), followed by cloning into the pMD19-T vector . A total of 30 positive clones were randomly chosen for sequencing of all samples  and sequence data for methylation level were evaluated via the quantification tool for methylation analysis (QUMA) software [Genomic DNA from duodenum and jejunum tissues was transformed via EpiTect Fast DNA Bisulfite kit , and the underlined PCR primers  were established on the basis of the sequence of the sulfite transformation via the MethPrimer software. Moreover, 25-μL PCR amplification reactions of bisulfite-treated DNA (BST-DNA) consist of 2 μL DNA template, 12.5 μL ZYMO Taq Premix, 1 μL forward primer (10 μM/L), 1 μL reverse primer (10 μM/L), 8.5 μL distilled DI Hhttp://www.gene-regulation.com/pub/programs/alibaba2/index.html?, accessed on 18 February2021) and JASPAR  were employed to evaluate transcription factor binding sites (TFBS), basing on the sequence of the FUT3 promoter region. Based on the CpG sites of methylation level significantly altering mRNA expression, we further screened out the important transcription factors and conducted validation experiments by dual-luciferase activity assay.Alibaba  was used. Relative quantitative results were examined via the 2t method . Results