Production of mRNA depends critically on the rate of RNA polymerase II (Pol II) elongation. To dissect Pol II dynamics in mouse ES cells, we inhibited Pol II transcription at either initiation or promoter-proximal pause escape with Triptolide or Flavopiridol, and tracked Pol II kinetically using GRO-seq. Both inhibitors block transcription of more than 95% of genes, showing that pause escape, like initiation, is a ubiquitous and crucial step within the transcription cycle. Moreover, paused Pol II is relatively stable, as evidenced from half-life measurements at ∼3200 genes. Finally, tracking the progression of Pol II after drug treatment establishes Pol II elongation rates at over 1000 genes. Notably, Pol II accelerates dramatically while transcribing through genes, but slows at exons. Furthermore, intergenic variance in elongation rates is substantial, and is influenced by a positive effect of H3K79me2 and negative effects of exon density and CG content within genes.DOI:http://dx.doi.org/10.7554/eLife.02407.001 Many different factors determine how quickly the DNA in genes is transcribed to produce molecules of messenger RNA. The start of the transcription process features two milestones: first, an enzyme called RNA Polymerase II starts the process; shortly afterwards, however, the process pauses and only starts again when other proteins are recruited. This provides two levels of control over the production of messenger RNA and, it also allows the transcription process to be interrupted in order to study the rate of transcription.Here, Jonkers, Kwak and Lis used two drugs to block either the start of transcription or the release from the paused state in mouse cells. Both drugs prevented new transcription and disrupted about 95% of the total number of genes. However, RNA Polymerase II that was already copying DNA could continue to copy, and did so at an average rate of 2000 bases per minute. Transcription rates were, however, shown to vary between different genes—highly active genes are transcribed faster. Transcription rates also varied within individual genes, with the enzyme accelerating as it moves along the gene. This suggests that the transcription machinery, including other proteins that improve the enzyme’s efficiency, are recruited or modified after transcription has already started, and that these proteins help the enzyme to reach its maximum transcription speed.Other factors also affected the transcription rate: the genetic code is written in four letters—A, C, G and T—and genes that contained more Cs and Gs were transcribed slower than those with lots of As and Ts. Genes also contain regions called exons that code for proteins, and regions called introns that do not: Jonkers, Kwak and Lis found that genes with lots of exons were transcribed slower. Furthermore, DNA is wrapped around proteins into a compacted structure, and genes that had certain chemical markings added to these proteins were transcribed faster.The work of Jonkers, Kwak and Lis is the first in-depth look at how transcription is affected by gene structure, and leads the way to uncovering how transcription rates throughout genes are regulated to influence production of messenger RNA.DOI:http://dx.doi.org/10.7554/eLife.02407.002 Drosophila causes an increase of promoter proximal Pol II at the majority of genes   can be regulated, and modulation of any step has the potential to alter the timing and output of mRNA production. After initiation of Pol II, transcription regulation is mediated mostly by the dynamics of Pol II elongation. For example, +20 to 100 nts downstream of the transcription start site (TSS), Pol II can be slowed down and paused by negative elongation factor (NELF), DRB-sensitivity inducing factor (DSIF) and core promoter components . The escof genes . The accof genes . However70 locus  and by ede (Trp) . Thus, DIn mammals, promoter proximal pausing also seems to be a P-TEFb dependent and rate-limiting step during early elongation for many genes . ExpressDownstream of the promoter proximal region, the rate of Pol II elongation has been proposed to influence (co-)transcriptional processes such as splicing , 3′ end The relationship of elongation rates, exons and other features of transcription units is still in dispute. Despite observations of Pol II accumulation at exons, three studies that directly measured elongation rates at multiple genes could not clearly demonstrate a correlation between exons and elongation rate . FurtherIn this study, we use Trp and FP, two highly specific drugs to block initiation or pause escape, in combination with the sensitive GRO-seq assay  to examiActB gene body using ChIP-qPCR with an antibody to total Pol II (not shown), and then used these concentrations, which were at the lower spectrum compared to previous studies  . The meaosophila . Thus, pPol II that is already transcribing when FP is added generates a clearly distinguishable wave as time progresses. We tracked the rate of this wave’s progress in an unbiased manner with a hidden Markov model HMM,  at more On average, Pol II travels about 100 kb during 50 min of FP treatment. This corresponds to an elongation rate of about 2 kb/min, which is comparable to Pol II rates from previous studies . The aveNext, we calculated elongation rates for genes that had two or more consecutive transition points. Since we do not include 0 min as a baseline, and start measuring transition points after 5 min when significant changes in Pol II distribution are observed, the lag time of the inhibitor action does not affect the elongation rate estimations. We directly measured 141 early (5–12.5 min), 938 mid (12.5–25 min), and 245 late (25-50 min) elongation rates, with average elongation rates of 0.5, 1.8 and 2.4 kb/min respectively . The varThus, the direct measurement of elongation rates after inhibition of Pol II gene entry by FP or Trp leads to two main observations. First, elongation rates vary considerably between genes, and second, the elongation complex seems to accelerate as it transcribes through the gene. We proceeded to confirm both observations independently.To verify our directly measured elongation rates, we compared the mid elongation rates group (n = 938), to an independent measurement of relative elongation rates , using iBecause the saw tooth pattern was more clearly distinguishable in larger introns and because intronic reads are much less abundant than exonic reads in typical RNA-seq datasets, we grouped introns and used pooled intronic read counts on all introns longer than 10 kb. Similar to what was shown in an individual gene example , we founNext, we explored the acceleration of Pol II within the gene body in independent ways: (1) Directly measuring elongation rates in different regions within genes, (2) Analyzing relative elongation rates within different regions of the gene body with intronic RNA-seq read gradients.First, our direct measurement of early, mid and late elongation rates after either FP or Trp treatment suggests that Pol II accelerates as it transcribes through the gene body , which iSecond, we examined the read density in introns, as described above, in the region from the TSS to 25 kb, and in introns 50 kb downstream of the TSS within the same genes. The slope of intron read density as a function of distance to the 3′ SS is higher in the upstream region compared to the downstream region , indicatThe acceleration is not constant, but decreases as transcription proceeds , suggestv−1) with the Pol II density (D) can be used to determine which model of Pol II elongation is more probable (v−1) does not fall below the density plot (D) in the gene body region . These highly expressed genes display a log–log slope of 2.2 . In contThe large number of measured elongation rates allows us to identify major factors that influence variation in elongation rates. We used genes for which we measured the large number of mid elongation rates  to increase statistical power, and to rule out major effects of intrinsic acceleration in the comparison between elongation rates. Existing genome-wide data of transcription factors, chromatin modifiers, and chromatin modifications were used to detect determinants of elongation rate  , left. ISomewhat surprisingly, promoter architecture seems to have an effect on downstream elongation rates. We found a striking positive correlation between CG content at promoters, that is CpG islands, and the downstream mid elongation rates , left. UTo assess if CG content within the gene body has an effect on elongation, we examined the DNA sequences in the average mid elongation rate 7.5–30 kb region by searching for differences in all possible 6-mer DNA sequences between the fastest and the slowest groups of genes. Interestingly, the top 20 6-mer sequences associated with slower elongation rates were enriched for repeats of CG dinucleotides , left. MAs described above, gene-to-gene differences of the elongation rates are associated with various features of genes. Many of these are tightly linked to each other; the first intron length is related to H3K79me2 mark and directly linked to the exon density; CpG methylation and H3K36me3 is enriched specifically in exons. To ascertain the primary from secondary determinants of the elongation rates, we used a multivariate regression analysis. For individual genes, each feature was scaled to a rank-order based z-score to assume a Gaussian distribution, making different metric types comparable. We then iteratively assessed how combinations of the features fit to the linear model, and determined the association network with our elongation rate measurements.Out of many features associated with the gene body and promoters of mid elongation rate genes , we examIn this study we emphasize the role of elongation rate in the modulation of transcription in mESCs. While transcription elongation rates often seem to be taken for granted, we show that elongation rates are surprisingly diverse, both at the promoter proximal region, within the gene body, and between genes. We definitively show that all genes have the potential of being regulated at the promoter proximal pause site, as all initiated Pol II undergoes a P-TEFb dependent step of escape into productive elongation. Furthermore, we find that the average half-life of paused Pol II is 7 min, indicating that Pol II pausing is remarkably stable, and not the consequence of fast, repeated rounds of initiation and termination. Finally, we measured elongation rates ranging from 0.5 to 4 kb/min at ∼1000 genes and within different regions of genes. Strikingly, Pol II accelerates as it transcribes through the gene body, and a large amount of variation in elongation rates occurs between genes, and is associated with chromatin and exon density. Overall, we are able to predict ∼30% of the intergenic variation in elongation rates with just three features, exon density, CpG content and methylation, and H3K79me2, providing a first quantitative assessment of how elongation rates are affected by gene structure.Drosophila Hsp70 locus without decreasing termination of paused Pol II, arguing against a role for termination in the regulation of the accumulation and escape of paused Pol II.Inhibition of P-TEFb, like inhibition of initiation, affects >95% of actively transcribed genes, showing that escape from pause is an integral step in the transcription cycle. However, not all active genes show signs of promoter proximal accumulation of paused Pol II in mES cells . The balDrosophila , and spun down at 4°C. Cells were dounced 50x in 5 ml fresh cell lysis buffer on ice and spun down, after which supernatant was discarded and nuclei were taken up in ∼250 μl of glycerol storage buffer  and snap frozen.Cell culturing of the V6.5 mES cell line was done as in 7 nuclei were mixed with an equal volume of reaction buffer . The NRO was performed at 30°C for 5 min, and a population of ∼100 different in vitro transcribed Arabidopsis thaliana spike-in RNAs with and without Br-UTP was added to the nascent RNA. The RNA was fragmented to ∼150 nts with 0.2N NaOH and BrU-RNA was isolated three consecutive times with BrdU-antibody beads , with enzymatic TAP and PNK treatments to remove the cap and 3′-phosphate and to add a 5′-phosphate, as well as Illumina adaptor ligations between the BrU-RNA isolation steps. The three consecutive isolation steps lead to an approximate 500.000x enrichment of BrU-RNA over background RNA. BrU-RNA was reverse transcribed, amplified, barcoded and Illumina sequenced. Each dataset was done in replicate.For each nuclear run-on (NRO), 10https://code.google.com/p/cutadapt/) and aligned uniquely with two mismatches with bowtie to the mm9 reference genome. Replicates were highly correlated and were pooled for further analysis . The genes for analysis of FP and Trp sensitivity are the top 75% active genes larger than 3.5 kb present in both the FP as the Trp control dataset, without genes that have an annotated TSS within 1000 bp on the opposite strand  and genes that have an annotated polyA site upstream of its TSS within 10 kb (tandem genes) , with pause peak read density R, decay rate λ, and Trp treatment time t) with each of the seven points. The mean of the regressions is the decay rate and the standard deviation of the decay rate is the standard deviation of the 1000 individual regressions.Decay rates were calculated by selecting seven points randomly of the seven Trp datasets for 1000 times and doing non-linear regression using an exponential decay equation , that have corresponding transcription units at the annotated TSS, but do not contain intragenic transcription units defined by the genome-wide transcription unit calling algorithm (described below in this section). Also, genes that have premature termination before the annotated 3′ ends and/or the 60 kb/150 kb mark are removed using a regional transcription unit calling algorithm (described below in this section). After filtering, the number of selected genes are n = 4461, 2769 and 571 for genes longer than 30 kb, 60 kb, and 150 kb, respectively. The transition points from the drug affected (inhibited) region to the drug unaffected (uninhibited) region of the gene body were determined by a regional transition point calling algorithm (described below in this section) for each replicate of FP or Trp GRO-seq time courses. The following is the description of the custom made HMM algorithms in c++.B, where n = 20 and e is the emission probability. We assumed two hidden states, ‘inhibition affected’ and ‘inhibition unaffected’, with two emission probabilities e1 and e2. The transition probabilities between the ‘affected’ and ‘unaffected’ states are p11, p12, and p21, and are unidirectional. The Baum-Welch algorithm is used to estimate the transition and emission probabilities, by iterative calculations until the probabilities converge. If the iteration is over 200 cycles without convergence, we dropped the gene from further analysis. The transition point is calculated from these probabilities.For the selected genes, GRO-seq read counts from the TSS to 60 kb or 150 kb positions are binned for each time-point, and were divided by the untreated read counts at the same bins . The binB. Second, the full length of each chromosome was used rather than individual genes. Third, the Baum-Welch algorithm was allowed to run up to 1000 iterations. Finally, a Viterbi path was calculated to define transcriptionally active regions.The untreated GRO-seq data is used similarly as the regional transition point calling algorithm with some modifications. First, instead of using ratios relative to the reference dataset, we used binary observation values for each 200 bp bin of the Markov process; 1 if there is a GRO-seq read within the bin and 0 if there are no reads. In this case, the binomial distribution becomes Using this de novo transcription unit (TU) calling, we selected TUs that have both sense and divergent pairs starting within 2 kb from each other. These paired TUs can indicate annotated TSSs, unannotated TSSs, or other regulatory transcription activities such as lncRNA or enhancer transcripts. We compared these TUs to the annotated long genes and removed the genes that did not have paired TUs near the annotated TSS (<2 kb). Also, we dropped genes that contain divergent TUs within the gene body, since these paired sense TUs can indicate alternative start sites that may interfere with detection of the inhibition wave by the regional transition point calling algorithm.Using untreated GRO-seq data, we generated binary bins from TSSs defined by the genome-wide transcription unit calling algorithm to 50 kb downstream of the annotated 3′ end in each individual gene, and used these values to estimate the probability parameters of the HMM. This is similar to the genome-wide transcription unit calling algorithm in that it uses binary observation values, but also similar to the regional transition point calling in that it is done in individual genes. One difference is that it starts from the active region and detects the transition point into the inactive region or in other words the end of the TU, which is opposite of the regional transition point calling algorithm. Genes that have the transition point before the 60 kb/150 kb point are dropped, as this may interfere with detection of the inhibition wave by the regional transition point calling.that is 10–20 kb, 20–30 kb, 30–40 kb groups, etc. We used up to 50 kb for the estimation of elongation rates (up to 80 kb are plotted). Third, introns are aligned at the 3′ splicing sites (3′SS), and intronic reads are counted in 100 bp windows in each intron length subgroup. To normalize for differences in the transcription level in each group, the read counts in windows are normalized to the read density 1 kb upstream of the 3′ SS to the 3’SS in each group  as a function of time. For the steady state assumption, r is a constant over time (t), while for the simulation of the inhibition wave r is an exponential decay function of t.In detail, the dynamics of elongating Pol II in gene body is simulated using a newly designed modeling program to describe Pol II transcription through a gene. First, we modeled a Pol II transcription complex entering the gene body region with an entry rate , from 0 to 100 as a percentile. This activity parameter A is an intrinsic value that determines the relative elongation and the termination rates for each Pol II molecule. The termination constant (kt) and the elongation rate (v) are the functions dependent on the activity (A) as well as the position (x) within the gene body of the Pol II molecule. For instance, in a simple acceleration model where all Pol II molecules accelerate uniformly, kt = 0 for all A and x, while v is an increasing function of x but a constant function for A. In a termination model, intrinsically active Pol II molecules elongate faster while less active ones elongate at a slower rate and terminate more frequently. In this case, kt is a decreasing function of A, and v is an increasing function of A regardless of x.Each Pol II molecule was generated with the rate Δt. For each event, a pseudorandom number between 0 and 1 is generated and compared to the probability of initiation as described by 1-exp(-rΔt), termination as described by 1-exp(-ktΔt), and processive elongation as described by 1-exp(-vΔt) respectively. If the number is less than the probability of any of the processes, the status of the polymerase changes accordingly. For the approximation of the progression event, the polymerase can move k bases following the Poisson distribution if the pseudorandom number is in the range , F), where F is the cumulative Poisson distribution function and λ = vΔt. If there is a collision event between two polymerases, the leading polymerase terminates.When running a simulation, the entry, termination, and progression events are assessed after each time increment of D. Upon the simulation of the decay of entry, average Pol II distribution is recorded every 100 s over 100,000 bp region. The average distribution at each time point is analyzed using the HMM, and the transition points are estimated. From the time course of transition points, the apparent elongation rates (va) are calculated as a function of the position (x). The slope plot  = 5 bp/s, v(x = 60 kb) = 40 bp/s ; Pol II starts at 5 bp/s (300 bp/min) and accelerates to reach 40 bp/s (2.4 kb/min) at the 60 kb position and downstream. The interpolating v(x) values are generated using cubic Bézier functions. The termination rate kt is 0.v(A = 0) = 5 bp/s, v(A = 100) = 40 bp/s; the interpolating v(A) values are made with the cubic Bézier functions. kt(A = 0) = 0.002–0.0005 (/s), kt(A = 100) = 0; the interpolating kt(A) values are made with cubic Bézier functions. The kt(A = 0) values are chosen so that the simulated D curve reflects the observed D curve which gradually decreases in regions x <20 kb and becomes nearly a constant where x >20 kb. The less active (and slower) population of Pol II is mostly terminated within the first 20 kb region with selected kt parameters. Finally, combinations of v and kt functions are used.v is generated as a combination of the v(x) of the acceleration model and v(A) of the termination model. The kt functions of the simple termination models are used.Models with mixed acceleration and termination are also tested. kt) can also have an added dimension and can be treated as a function of both x and A. The interpretation of this is that termination takes place at some preferred positions along the gene. We adjusted the shape of the function so that slower Pol II is relatively stable near the 5′ side of the gene to make the apparent elongation rate slower at the beginning. The increased termination at more downstream position leaves only the faster polymerase populations and the apparent elongation rates are higher.The termination rate . Briefly, the percentile rank of a gene’s specific genomic feature is converted to a z-score through the inverse cumulative Gaussian distribution function. This conversion enables the comparison of different non-linear features, yet also allows us to use the linear modeling tools such as least square methods and principal component analysis. Genes with tied rank orders are randomly assigned to have different ranks. The major features taken into account have a p-value<0.01 from the simple linear regression (function lm in R). The z-score distribution between the elongation rate and a major feature is plotted in a  ×  range . The pri2 by the 1° feature was color scaled in a combinatorial manner to produce the heatmap in For the iterative linear modeling, we took the residual elongation rates after fitting to the linear modeling using a 1° feature , dounced 60 times on ice and centrifuged at 13,000 rpm for 5 min at 4°C. Supernatant was snap frozen as the unbound fraction, while the remaining pellet was resuspended in nuclei lysis buffer and sonicated to break up the chromatin and solubilize the pellet, and snap frozen. Western blot analysis was done in triplicate with antibodies against the Ser5  or Ser2  phosphorylated CTD, or N-terminal Pol II .Chromatin bound and nucleoplasmic/cytoplasmic free proteins were extracted after treatment of pre-plated mES cells for 50 min with 300 nM FP, 500 nM Trp or 0.0125% DMSO as no Trp control. Cells were rinsed twice in ice-cold PBS, pH 7.4, scraped off the plates, spun and resuspended in nuclei lysis buffer . Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent , Reviewer 2 added the following comment:The paper is in principle suitable for Was there any evidence for premature termination (in addition to pausing) at any genes? 7-8' retention of RNAPII is a stable pause, but how short-lived would RNAPII be at prematurely terminated genes? The authors see little evidence for this, but have HERV-H gene transcripts (which are reportedly high in ESCs and make lots of long noncoding RNAs) been checked and show any evidence of termination? Benkirane's Cell paper found that there is termination and Drosha-mediated cleavage at those genes (but in HeLa cells). Cramer also saw little evidence of premature termination in yeast in his Nrd1 paper, but HIV-1 LTR and HERV genes are thought to do this. The existing data should be checked for HERV-H genes, but obviously for the authors to reach their conclusions it is not essential to do this.Reviewer1:eLife. In essence, the paper is simple, using GRO-seq to map Pol II on a genome-wide scale under conditions where transcriptional initiation or Pol II pausing are blocked by drugs . Of course, the validity of the study hinges on the specificity of the drugs, but both appear quite specific. Many conclusions of this paper have essentially been made previously; e.g., pausing as a general feature of Pol II transcription in mammals and other  organisms; stability of paused Pol II; gene-specific elongation rates; increased elongation speed at more distal position; effect of exons. However, what is particularly important about this paper is that it addresses all these fundamentally important issues in the most comprehensive, genome-wide form, and it doesn't use unusual inducing conditions. In addition, the use of the intronic RNA-seq data as a way of obtaining drug-independent data to support the conclusions is clever. Some of these important issues have been controversial or unclear in the literature, and the results here are as definitive as one could expect. So, while one could question whether the paper is truly novel, it represents a significant advance on a very important subject. The paper is generally well written, although some of the specific results and figures take some time to understand what has been really done.This is a superb paper that should be published in can cause the same effect; e.g., a slow Pol II, 6-AU, or inactivation of an elongation factor (1) The authors make the interesting observation that the decrease in Pol II association at downstream positions may be due to increased elongation rate as opposed to defective processivity due to low levels of premature termination. While I believe this conclusion for the physiological situations tested, the authors should mention that conditions that decrease elongation rate n factor .2) The term “transition point” needs to be defined. I got the general idea, but not the definition.Reviewer2:This study provides a high-quality and quantitative assessment of transcription elongation rates in self-renewing mESCs from the Lis lab, inventors of the GRO-Seq technique. As generally is the case from this lab, the findings are interesting and conclusively supported, and should be of significant interest to the many investigators in this field. The main results provide strong support for numerous earlier studies arguing that elongation rates can vary significantly between genes, slow down through exonic regions, and correlates with CpG content and chromatin modifications like H3K79 methylation, while contradicting the idea that paused RNAPII complexes are rapidly terminated and replaced. The application of this technique to mouse stem cells is novel and well justified and will enrich existing datasets that for further studies seeking to correlate elongation rates with specific genic and epigenetic features.One obvious limitation is the reliance on chemical inhibitors (FP and Trp) as surrogates for inactivation of Cdk9/P-TEFb and TFIIH, respectively. The authors should more fully acknowledge in the text that FP eliminates the expression of many short-lived proteins, including other transcription factors, which could affect these results, and that all of the conclusions are subject to potential off-targets effects of either drug. FP has a potent effect on histone modifications, not all of which have attributed to P-TEFb, and the authors should also address whether these changes would influence the elongation rates, which obviously had to be measured in the presence of the drugs.In transformed cells FP induces cell cycle arrest and in some cases apoptosis – was there any effect on the cell cycle of these drugs in mESCs?Kindly address how increased elongation rates correlate with increased H3K79me2 within long first exon, yet the highest elongation rates are measured at the 3' end of the genes, which are relatively lacking for H3K79me2?The conclusion that paused RNAPII complexes are stable derives from their persistence for 7-8' after treatment with Trp, and leads the authors to conclude that premature termination is rare or undetectable in these cells – but it would be much more helpful to compare directly with a prematurely terminated gene – what did the paused complex look like at the highly active HERV-H element-containing, Drosha-sensitive, linkRNAs in these cells?Because developmental lineage-specific genes in mESCs are not regulated by TFIIH, they may have distinct patterns of elongation, as may many signaling genes, and so the authors may want to stress that the 'universality' of their findings applies only to self-renewing ESCs. Was there any evidence for premature termination (in addition to pausing) at any genes? 7-8' retention of RNAPII is a stable pause, but how short-lived would RNAPII be at prematurely terminated genes? The authors see little evidence for this, but have HERV-H gene transcripts (which are reportedly high in ESCs and make lots of long noncoding RNAs) been checked and show any evidence of termination? Benkirane's Cell paper found that there is termination and Drosha-mediated cleavage at those genes (but in HeLa cells). Cramer also saw little evidence of premature termination in yeast in his Nrd1 paper, but HIV-1 LTR and HERV genes are thought to do this. The existing data should be checked for HERV-H genes, but obviously for the authors to reach their conclusions it is not essential to do this.We have addressed this interesting phenomenon in the mESC GRO-seq data we generated by looking at the specific genes found to have Drosha mediated cleavage and termination in HeLa cells by Wagschal et al. We have also looked at GRO-seq density profiles at HERV-H-like LTR repeats genome-wide to investigate the role of microprocessor and Xrn2 mediated termination within gene bodies in mESCs. The results of our additional analysis are discussed below in our response to the comments made by Reviewer 2.Reviewer 1:1) The authors make the interesting observation that the decrease in Pol II association at downstream positions may be due to increased elongation rate as opposed to defective processivity due to low levels of premature termination. While I believe this conclusion for the physiological situations tested, the authors should mention that conditions that decrease elongation rate can cause the same effect; e.g., a slow Pol II, 6-AU, or inactivation of an elongation factor .We agree that this careful study by Mason & Struhl should be acknowledged in this paper and have included references and a model comprising this work to the main text. We would like to point out that we looked at a model that fits the observations made by Mason & Struhl in our Monte Carlo simulation. The mixed model in Textual changes related to this comment: sentence beginning “The decreasing pattern of gene body Pol II density…” in the Results section entitled “Poll II stably elongates in the gene body, while termination is negligible”.2) The term “transition point” needs to be defined. I got the general idea, but not the definition.We apologize for not clearly defining what transition points are in the text. The transition point is the middle of the inhibition wave from the affected to unaffected region within the gene body after Trp or FP treatment. We changed the text to make this clear in the manuscript as well  as surrogates for inactivation of Cdk9/P-TEFb and TFIIH, respectively. The authors should more fully acknowledge in the text that FP eliminates the expression of many short-lived proteins, including other transcription factors, which could affect these results, and that all of the conclusions are subject to potential off-targets effects of either drug. FP has a potent effect on histone modifications, not all of which have attributed to P-TEFb, and the authors should also address whether these changes would influence the elongation rates, which obviously had to be measured in the presence of the drugs.ActB gene to see what concentrations of FP and Trp clears Pol II from the gene body in a time dependent manner (not shown). We stress that both the concentration used for FP and Trp are at the lower spectrum of what is generally used for these drugs in the literature, reducing the risk of off-target effects. Furthermore, we use the drugs for short periods of time, 50 minutes is our longest timepoint, thereby minimizing secondary effects.We agree with the reviewer that this study relies on the specificity of the drugs FP and Trp. Therefore, when we set out to do the GRO-seq experiments we ensured that we were using the minimal effective concentration of each of these drugs by doing western blots on the fractions of chromatin bound and free Pol II before and after drug addition , as wellEven though we have taken considerable steps to perform the experiments at the minimal drug concentration possible, and measure within a relatively short period of time, we agree that the FP off-target effects may interfere with elongation, and therefore could hamper our elongation rate measurements. However, we would like to point out that we also measure elongation rates after Trp treatment. Trp blocks XPB helicase function, which is a vastly different mechanism of transcription inhibition compared to FP inhibition, and not likely to have similar potential off-target effects of FP. Although we could measure fewer transition points and elongation rates after treatment with Trp, the 683 transition points shared between the FP and Trp experiments did not differ significantly from one another, emphasizing that if there are off-target effects of FP that affect elongation rates, they are minor and within the error margins of our assay.To address the reviewers concerns, we have made textual changes regarding the specificity of the drugs within the Results and Discussion sections:In transformed cells FP induces cell cycle arrest and in some cases apoptosis – was there any effect on the cell cycleof these drugs in mESCs?Although we did not specifically look for the effects of FP or Trp on the cell cycle or cell death, we imagine that they are significant upon prolonged treatment with either drug, considering that both shut down virtually all Pol II transcription. However, within the 50 minutes of our assay, the ES cells were morphologically indistinguishable from the untreated samples. Moreover, other studies have used FP as a drug to block Cdk9 function for an hour or more, and at higher concentrations, without reporting major problems with the cells such as apoptosis.We added a sentence to the Results section clarifying this .Kindly address how increased elongation rates correlate with increased H3K79me2 within long first exon, yet the highest elongation rates are measuredat the 3' end of the genes, which are relatively lacking for H3K79me2?Based on our results we propose that both intrinsic and extrinsic factors determine Pol II elongation rate throughout the gene body. Intrinsic factors may consist of pausing factors that interact with the Pol II complex near the TSS and need to be removed or altered before the elongation complex reaches its full speed. This happens near the TSS, mostly within the first 15 kb of the gene body, based on the Pol II composite profiles and acceleration of Pol II within this region . ExtrinsTo investigate what extrinsic features of DNA and chromatin could influence elongation rate we used the 938 mid elongation rates that were derived from the 12.5 to 25 min FP treatments. We used these elongation rates for two reasons: 1. This is the biggest group of elongation rates, providing the greatest statistical power, and 2. We only used elongation rates measured between these two timepoints for all genes to minimize the variation of intrinsic acceleration of Pol II in these genes. The average transition points after 12.5 or 25 min drug treatment are 7 and 30 kb respectively, which often coincides with the H3K79me2 enrichment with the first exon and intron. After exon 2, we saw a significant drop in H3K79me2 levels , but thiTo clarify this in the text we made the following changes: “…to increase statistical power, and to rule out major effects of intrinsic acceleration in the comparison between elongation rates. Existing genome-wide data of transcription factors, chromatin modifiers, and chromatin modifications were used to detect determinants of elongation rate . Therefore, we made use of this information to answer two questions. First we asked whether the dynamics of promoter proximal Pol II is influenced on the potential Drosha target genes. Second is whether the Pol II termination is a general mechanism, taking place on sites with endogenous retrovirus sequences.For the first question, we looked at the genes that are proposed to be regulated by termination in HeLa cells by Wagschal et al.  and Dlgap1). We found that 3 out of 6 genes were actively transcribed in mESCs, and calculated decay rates and half times for the promoter proximal Pol II in these genes . Each deFor the second question, we identified the IAP LTR endogenous retrovirus elements proposed to trigger Pol II termination in the Li et al. paper, and examined the average GRO-seq profile relative to these sites. If there were general Pol II termination occurring, we expect to see a drop of GRO-seq density downstream of these sites. We did not find such a drop significantly different from the alignment bias pattern (‘mappability’) of the regions, suggesting that Pol II termination is not generally occurring .However, in the Polr1a gene discussed in the Li et al. paper, we observed the GRO-seq pattern indicative of premature nascent RNA cleavage and post-cleavage Pol II accumulation , making it difficult to assess the Erk kinase, Ercc3 and Ser5 and total Pol II ChIP-seq data ourselves. Therefore, we used the Ser5, Ser2 and N-terminal Pol II ChIP-seq datasets generated by Rahl et al. , as well as our own GRO-seq datasets, before and after 25 min Trp treatment to best mimic the 30 min Trp treatment used by Tee et al., to look at the patterns of expression of the genes insensitive to Trp. Surprisingly, we could not reproduce the results reported by Tee et al. All actively transcribed genes reported as being insensitive to Trp treatment by Tee et al. were clearly inhibited by 25 min Trp treatment in our study, or not actively transcribed . Thus, strain and growth condition differences could result in variation in gene expression. Indicative of this potential difference in gene expression, in our study and that of the Young lab, the Trp insensitive developmental genes were far less transcribed in V6.5 mESCs compared to the control genes Klf2 and Trim28 . In contrast, the level of transcription for these genes as measured by Pol II-Ser5 ChIP-qPCR in Alternatively, the antibody used in the Tee et al. study may target a different form of Pol II than detected in the GRO- and ChIP-seq data shown in the figure describing TFIIH sensitivity , below. Because of the clear differences in results between these two manuscripts, we are uncomfortable including a sentence regarding TFIIH insensitive genes in mouse ES cells or other cell types. We would need to address this issue in depth to make a sensible statement, including analyzing the Tee et al. data sets that are currently not available, as well as doing experiments where we combine Trp treatment with differentiation. However, we feel that this is beyond the scope of our current paper.


As a consequence, KSHV has evolved a way as to produce multiple SUMO regulatory viral proteins to modulate the cellular SUMO environment in a dynamic way during its life cycle. Remarkably, KSHV encodes one gene product (K-bZIP) with SUMO-ligase activities and one gene product (K-Rta) that exhibits SUMO-targeting ubiquitin ligase (STUbL) activity. In addition, at least two viral products are sumoylated that have functional importance. Furthermore, sumoylation can be modulated by other viral gene products, such as the viral protein kinase Orf36. Interference with the sumoylation of specific viral targets represents a potential therapeutic strategy when treating KSHV, as well as other oncogenic herpesviruses. Here, we summarize the different ways KSHV exploits and manipulates the cellular SUMO system and explore the multi-faceted functions of SUMO during KSHV’s life cycle and pathogenesis.Small Ubiquitin-related MOdifier (SUMO) modification was initially identified as a reversible post-translational modification that affects the regulation of diverse cellular processes, including signal transduction, protein trafficking, chromosome segregation, and DNA repair. Increasing evidence suggests that the SUMO system also plays an important role in regulating chromatin organization and transcription. It is thus not surprising that double-stranded DNA viruses, such as Kaposi’s sarcoma-associated herpesvirus (KSHV), have exploited SUMO modification as a means of modulating viral chromatin remodeling during the latent-lytic switch. In addition, SUMO regulation allows the disassembly and assembly of promyelocytic leukemia protein-nuclear bodies (PML-NBs), an intrinsic antiviral host defense, during the viral replication cycle. Overcoming PML-NB-mediated cellular intrinsic immunity is essential to allow the initial transcription and replication of the herpesvirus genome after  Like ubiquitination, SUMO conjugation occurs through an enzyme cascade. SUMO precursors are processed by SUMO-specific proteases (SENPs). Mature SUMO is activated by the SUMO E1 activating enzyme (SAE1/SAE2), transferred to the SUMO E2 conjugating enzyme (Ubc9), and then ligated to a lysine residue within SUMO consensus sequence inside the target protein . Althoughe cells  (RevieweSimilar to the Src homology 2 (SH2) domains and phosphotyrosine binding (PTB) domains that mediate selective protein-protein interaction with phosphorylated tyrosine, the SUMO-interacting motif (SIM) mediates the recognition of SUMO modification in both a paralog-specific and -non-specific manner . Via SIMDue to the involvement of SUMO in almost all cellular aspects, it is not surprising that viruses have evolved many different pathways to exploit the host SUMO system. In most cases, viruses target the SUMO pathway by encoding proteins that interact with various components of the pathway in order to modulate their enzyme activities. For instance, the avian adenovirus, chicken embryo lethal orphan (CELO), encodes Gam1 that inactivates the SUMO E1 activating enzyme . Human aKSHV, also known as human herpesvirus type 8 (HHV-8), is a γ-herpesvirus associated with Kaposi’s sarcoma (KS), primary effusion lymphomas (PEL) and multicentric Castlemen’s disease (MCD) . It primIn addition to chromatin remodeling, SUMO plays another important role in the herpesvirus life cycle, namely in the assembly and disassembly of PML-NBs or ND-10 (nuclear domain-10). PML-NBs are discrete subnuclear structures that contain multiple cellular proteins, including PML, Sp100, hDaxx, and ATRX. It has long been postulated that PML-NBs function as an intrinsic antiviral defense by repressing viral transcription and replication . DisruptThe PML-NB is a SUMO storage warehouse for the nucleus and it is here that a large number of sumoylated proteins congregate. Sumoylation of PML is a prerequisite for recruitment of Daxx, Sp100, and SUMO paralogs during PML-NB formation . De-sumoMoreover, KSHV targets SUMO because SUMO is capable of modulating interferon-related antiviral responses. Invading viruses are recognized by Toll-like receptors (TLRs), a type of pathogen recognition receptor (PRRs), and this then results in the production of type I interferon (IFN) and the subsequent activation of the host innate immune response. Transcriptional induction of the type I IFN genes is mainly regulated by the IFN regulatory factor-3 (IRF-3) and IFN regulatory factor-7 (IRF-7). Sumoylation of IRF-3 and IRF-7 brings about the negative regulation of type I IFN expression . As a rede novo infection or during the reactivation process. It is a potent transcription factor that is necessary and sufficient to trigger the full lytic phase of KSHV. Concomitant with its ability to induce lytic replication and break the virus latency, K-Rta expression remodels the viral chromatin and disassembles PML-NBs [K-Rta is the first KSHV protein expressed after  PML-NBs ,51. K-Rt PML-NBs . K-Rta h PML-NBs ,53 and h PML-NBs . Recentl PML-NBs   within the N-terminal domain and these preferentially bind SUMO-2 ,51 FiguC. Cai etng sites B and sumng sites A. Taken ng sites .vIRF-3 is another KSHV latent cycle gene that is encoded by K10.5. This protein is expressed exclusively in KSHV-infected B cells and is required for the survival of KSHV-infected primary effusion B-cell lymphoma (PEL) . vIRF-3 vPK is an early lytic gene encoded by Orf36. It is a serine/threonine protein kinase that is localized in the nucleus and can be autophosphorylated . K-bZIP Genome-wide profiling has shown that there is distinct dynamic to the chromatin-binding patterns of SUMO paralogs during viral reactivation. The SUMO-1 and SUMO-2/3 binding patterns are very similar in non-reactivated control cells. However, during KSHV reactivation, SUMO-2/3 binding, but not SUMO-1, is significantly increased in the human genome. This enrichment is focused on the promoters region that contain primary regulatory elements such as TFBSs. Annotation of SUMO sites with putative TFBSs identified potential SUMOylated TFs. It shows that potential SUMO-1 target TFs are decreased, while SUMO-2/3 targeting TFs are significantly increased during viral reactivation. Interestingly, three IRFs have been identified as top 10 most potent SUMO-2/3 target TFs after KSHV reactivation. Knockdown of SUMO-2/3 results in a higher induction of most those IRFs-regulated genes analyzed during viral reactivation. These findings suggest that one (or a few) of the KSHV lytic proteins are able to catalyze the sumoylation of these IRFs and attenuate their activity. Expression profiling revealed that these SUMO-2/3 targeted highly transcribed genes show no expression changes during viral reactivation. Gene ontology (GO) analysis showed that these genes are involved in cellular immune responses. Both TF identification and GO analysis indicates that SUMO-2/3 preferentially targets immune-related genes in order to make sure that the expression of these genes remains unaltered during viral reactivation .Sumoylation is a post-translational modification that is both rapid and reversible. Modulation of sumoylation has a profound effect on protein-protein interactions and chromatin assembly. A common property of herpesviruses is that these processes are involved in the biphasic euchromatin-to-heterochromatin transition and this helps to bring about the rapid lytic/latency switch. Most studies have indicated that many chromatin-remodeling proteins are SUMO modified, and such SUMO modified proteins can recruit more SIM containing chromatin-remodeling enzymes that help to regulate chromatin structure. The rapid and reversible character of SUMO modification is able to efficiently affect the local dynamic of euchromatization and heterochromatization. Therefore, this makes sumoylation an interesting process whereby herpesvirus is able to regulate their rapid entry into latency and their rapid reactivation as part of their life cycle.Sumoylation, like phosphorylation, is involved in nearly all cellular processes and viruses have evolved different strategies to manipulate the SUMO process to their own advantage. For herpesviruses, sumoylation is important to at least three steps of viral replication and pathogenesis. These are: firstly, modulation of the viral chromatin during the latent and lytic states; secondly, the disassembly of PML-NBs; and thirdly, the attenuation of interferon responses. To these ends, KSHV encodes at least five proteins that are involved in these processes. They are as follows. Firstly, K-Rta, a lytic gene product with STUbL activity, which preferentially catalyzes the degradation of SUMO-2/3 and sumoylated proteins including PML . Secondl


DNMT gene expression can be induced by Ras-c-Jun signaling pathway, Sp1 and Sp3 zinc finger proteins and virus oncoproteins. Transcriptional repression on DNMT genes has also been reported for p53, RB and FOXO3a transcriptional regulators and corepressors. In addition, the low expressions of microRNAs 29 family, 143, 148a and 152 are associated with DNMTs overexpression in various cancers. Several important post-translational modifications including acetylation and phosphorylation have been reported to mediate protein stability and activity of the DNMTs especially DNMT1. In this review, we also discuss drugs targeting DNMT protein expression and activation for therapeutic strategy against cancer.Cancer is a leading cause of death worldwide. Aberrant promoter hypermethylation of CpG islands associated with tumor suppressor genes can lead to transcriptional silencing and result in tumorigenesis. DNA methyltransferases (DNMTs) are the enzymes responsible for DNA methylation and have been reported to be over-expressed in various cancers. This review highlights the current status of transcriptional and post-translational regulation of the DNMT expression and activity with a focus on dysregulation involved in tumorigenesis. The transcriptional up-regulation of  Cancer is a leading cause of death worldwide, accounting for 8.2 million deaths in 2012 ,4. Develin vitrop27kip[Bis ligand . In conts ligand . Of note in mice ,65. Rest in mice . The lasDNMT3B promoter activity by interacting with the binding element FOXO3a (+166 ~ +173) of DNMT3B promoter [FOXO3a site (-249 ~ -242). Abundant FOXO3a represses DNMT3B promoter by establishing a repressed chromatin structure, while knockdown of FOXO3a results in an open chromatin structure and high DNMT3B mRNA and protein expression. Importantly, enforced abundant nuclear accumulation of FOXO3a could decrease expression of DNMT3B with synergistic inhibition of tumor growth and decrease in methylation status on TSGs in human lung tumor xenograft specimens [FOXO3a DNA element of the DNMT3B promoter to repress DNMT3B expression  are small, noncoding RNAs that regulate expression of many genes. Recent studies suggest that abnormal expressions of miRs are involved in pathogenesis of different types of human cancers . Previound DNMT3B. The expd in vivo. Enforcehylation . Of notehylation .DNMT1 mRNA was found to be a target of miR-148b and miR-152 [DNMT3B gene in breast cancer cells [BNIP3 and SPARC[DNMT3A or DNMT3B, possibly through their 3′-UTR post-transcriptional regulation [In addition to miR-29s, ectopic expression of miRNA-148a in lung cancer cell lines also results in a significant reduction in the expression of DNMT1 . Using l miR-152 . Antagomer cells . Furtherand SPARC. It is tand SPARC. Specifigulation . Table 2Several important post-translational modification including acetylation and phosphorylation have been reported to mediate protein stability and activity of the DNMTs especially DNMT1 Figures  and 3. Tin vitro and in vivo[DNMT1 has been shown to be destabilized by acetylation-mediated ubiquitination. DNMT1 physically interacts with acetyltransferase Tip60, herpesvirus-associated ubiquitin specific protease (HAUSP), ubiquitin-like containing PHD and RING finger domains 1 (UHRF1), HDAC1 and PCNA on chromatin . Tip60 pd in vivo. Using md in vivo. Deacetyet al. found that the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) increases DNMT1 protein expression and activity [FHIT, RASSF1A, and p16INK4A, DAPK1, RUNX3, RARβ and SFRP genes [et al. showed that GSK3β interacts with DNMT1 to phosphorylate DNMT1 at Ser410 and Ser414 and promotes binding of DNMT1 by βTrCP leading to proteasomal degradation of DNMT1. They also demonstrated that DNMT1 contains a domain, ESGXXS, similar to the conserved binding motif DSGXXS of βTrCP [Lin activity . Strong activity ,86. Cigaactivity . In addiRP genes -93. NotaRP genes -96. It hRP genes ,98. In aRP genes . Lin et in vitro[In addition to Ser410 and Ser414 of DNMT1, recent studies have suggested that the enzymatic activity of DNMT1 is possibly modulated by phosphorylation of Ser/Thr residues located in the N-terminal domain of the enzyme -102. Proin vitro  X protein (HBx) plays a key role in the molecular pathogenesis of HBV-related hepatocellular carcinoma. HBx expression increases total DNMT activities and selectively promotes regional hypermethylation of specific TSGs, including ed cells . Anotherpression .DNMT1 promoter [p16INK4A gene are found when infected with HIV-1 in Hut 78 lymphoid cells [FOXP3 gene [Human immunodeficiency virus type 1 (HIV-1) also has been reported to induce DNMT1 through the responsive element residing in the -1634 to +71 of promoter . The incid cells . HIV infXP3 gene . TherefoDNMT gene expression can be induced by Ras-c-Jun signaling pathway, Sp1 and Sp3 zinc finger proteins, wilms' tumour 1, homeobox B3 and various human viruses. Loss of transcriptional repression control on DNMT genes has also been reported. For example, p53 transcriptionally suppresses DNMTs through binding with Sp1 protein to the DNMT promoters. RB transcriptionally suppresses DNMT1/3A through binding with E2F1 protein to the DNMT1 and 3A promoters. FOXO3a binds to the FOXO3a DNA element of the DNMT3B promoter to repress DNMT3B transcription. In addition, overexpressed MDM2 may induce DNMT1, DNMT3A, and DNMT3B expression by negative control over p53, RB and FOXO3a. Low expressions of some miRs such as miR-29s, miR-143, miR-148a and miR-152 are associated with DNMT overexpression in various cancers. Several important post-translational modification including acetylation and phosphorylation have been reported to affect protein stability and activity of the DNMTs especially DNMT1. Therefore, drugs targeting DNMT protein inactivation and depletion, such as MDM2, AKT and CDKs inhibitors may prove to be a good therapeutic strategy for cancer treatment. Combined treatment with the known DNMT inhibitors such as decitabine could be a potential therapeutic strategy through epigenetic modulation warranting further investigation in cancer treatment.DNMTs are the enzymes which catalyze the CpG DNA methylation and have been reported to be over-expressed in various cancers. The mechanisms of DNMT over-expression are worthy of investigation. The transcriptional up-regulation on DNMT: DNA methyltransferase; FOXO3a: forkhead O transcription factor 3a; HBx: hepatitis B virus X protein; HAUSP: herpesvirus-associated ubiquitin specific protease; hnRNP-U: heterogeneous nuclear ribonucleoprotein U; LMP1: latent membrane protein 1; miR: microRNA; NNK: nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone; RB: retinoblastoma; RGS: regulator of G protein signaling; TSG: tumor suppressor gene; UHRF1: ubiquitin-like containing PHD and RING finger domains 1.The authors declare that they have no competing interests.RKL and YCW wrote the review. Both authors read and approved the final manuscript.


Escherichia coli, and showed that AYVV-NT AV3 promoter could specifically interact with single-stranded DNA-binding protein and sigma 70 of E. coli involved in transcription. Several AYVV-NT-encoded proteins were found to increase the activity of AV3 promoter. The transcription start sites downstream to AV3 promoter were mapped to nucleotide positions 803 or 805 in E. coli, and 856 in Nicotiana benthamiana. The eukaryotic activity of AV3 promoter and the translatability of a short downstream open reading frame were further confirmed by using a green fluorescent protein reporter construct in yeast (Saccharomyces cerevisiae) cells. These results suggested that AV3 promoter might be a remnant of evolution that retained cryptic activity at present.A cryptic prokaryotic promoter, designated AV3 promoter, has been previously identified in certain begomovirus genus, including ageratum yellow vein virus isolate NT (AYVV-NT). In this study, we demonstrated that the core nucleotides in the putative −10 and −35 boxes are necessary but not sufficient for promoter activity in  Geminiviridae are characterized by their single-stranded circular DNA genomes and the geminate-shaped virus particles. Geminiviruses are divided into seven genera, Mastrevirus, Curtovirus, Begomovirus, Topocuvirus, Becurtovirus, Eragrovirus, and Turncurtovirus based on host range, vector specificities and genome organization The members of the family Agrobacterium tumefaciens and Escherichia coliAgeratum yellow vein virus (AYVV) in the genus Begomovirus can be generated in E. coli harboring AYVV genome with only a single origin of replication (ori) cloned in phage M13 vector Previous studies have demonstrated that some geminiviruses could produce various DNA forms indicative of replication processes and express certain viral genes in E. coli constitutive promoter of ribosomal RNA, rrnB P1 promoter E. coli of a small ORF downstream to AV3 promoter were also confirmed. These findings further supported the prokaryotic origins of geminiviruses, and revealed that certain prokaryotic features in the geminivirus genomes are still retained and possibly functional in their infection cycles. However, these observations also raised certain key questions about the regulation and activity of AV3 promoter in prokaryotic and possibly in eukaryotic systems: Whether the putative core motifs (−10 and −35 boxes) found in AV3 promoter are truly functional? What are the factors interacting with AV3 promoter in E. coli? Whether the AV3 promoter is also active in eukaryotic systems? And if so, whether the small ORF downstream to AV3 promoter is translatable in the eukaryotic system?Recently, a novel cryptic prokaryotic promoter, designated AV3 promoter, was identified at positions near the 3′-terminus of coat protein (CP) open reading frame (ORF) in some monopartite begomoviruses genomes E. coli and suggested that AV3 promoter might exhibit a level of activity in plant and yeast cells.To address these questions, we further characterized the regulatory features of ageratum yellow vein virus isolate NT (AYVV-NT) AV3 promoter in this study. Several lines of evidence were presented confirming that AV3 promoter of AYVV-NT is active in AYVV-NT and tomato leaf curl virus (TLCV), which is another monopartite begomovirus, respective full-length clones, pAYVVNT and pTLCV, have been described previously To generate the AV3 promoter mutants, 5′-phosphorylated primer pairs listed in 6-tagged single-stranded DNA-binding (SSB) proteins, the plasmid pET21d-SSB was generated by inserting the E. coli SSB gene sequence (GI: 557274221) using the primer pair listed in 6-tagged SSB were over-expressed in E. coli BL21 (DE3) and purified by Ni-NTA purification system .For producing the HisSacI site downstream to the start codon of the lambda-cI gene, using IPCR with the primer pair pBT1634SacIF and pBT1634SacIR . The pBT vector was mutated to generate pBT-1634SacI by in-frame inserting a 634SacIR . Each ofSpeI and KpnI digested pYES2/NT-C vector to generate the pY762-889GFP and pY762-1062GFP. A positive control, pYES2-cycle3GFP, was also generated (using primer pair C3GFP-KpnIF plus C3GFP-KpnIR), in which the Cycle3 GFP gene was inserted under the control of the original GAL1 promoter.For yeast assays, the pYES2/NT-C vector  was modified to replace the original GAL1 promoter with two different AYVV-NT fragments comprising the same AV3 promoter region plus two downstream ORFs fused to the Cycle 3 GFP gene. Two plasmids described in our previous study, pGP762-889GFP and pGP762-1062GFP E. coli. Bacteria harboring each construct were cultivated in LB broth containing 100 µg of ampicillin ml−1 at 37°C for 16 h. The cultures were then diluted 200-fold and incubated at 37°C for 4 h to reach the mid-log phase. Aliquots of 150 µl liquid cultures were loaded into a 96-well plate with three duplicates, and the fluorescence were measured by using an FLx800 Multi-Detection Micro-plate Reader  at an excitation wavelength of 400 nm and an emission wavelength of 508 nm, with a sensitivity setting of 60. The optical densities of each bacterial culture at 600 nm (OD600) were measured by using a SpectraMax M2 microplate reader . Cultures were allowed to continue growing for an additional 1 h, and the GFP fluorescence and OD600 were measured again. The promoter activity (indirectly indicated as GFP synthesis rate per cell) of each samples were calculated with three biological duplicates as described by Davis et al. (2011) as follows: the changes in fluorescence between the two readings was divided by the average of OD600, followed by correcting for background auto-fluorescence by subtracting the per cell synthesis rate of the negative control (vector only).GFP-based promoter activity assays were performed and analyzed as described previously E. coli DH5α were harvested and resuspended in 500 µl PBS buffer, followed by sonication with 10 s pulse/5 s pause for 10 min. The products were then incubated with 10 µg of biotin-labelled AV3 promoter or rrnB P1 promoter, generated by PCR using specific primers (−1) to inhibit the extension of transcription Overnight liquid cultures (1 ml each) of E. coli RNA polymerase sigma 70 antibody (2G10) , followed by a rabbit anti-mouse IgG AP-conjugated antibody .The proteins in the gel were subsequently visualized by silver staining or analyzed by western blot assay with specific antibodies. In silver staining, the protein bands of interest were carefully sliced from the gel and subjected to protein identification analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). For western blot assay, the proteins were subsequently transferred to the PVDF membrane, and detected by using a monoclonal antibody against 6-tagged SSB proteins at RT for 1 h. The bound SSB proteins on the PCR fragments on NC membranes were detected by a monoclonal antibody against histidine tag , and followed a rabbit anti-mouse IgG AP-conjugated antibody.Aliquots of 20 or 200 ng PCR fragments corresponding to the indicated promoters were analyzed by electrophoresis through a 1% agarose gel, followed by staining with ethidium bromide (EtBr), or by South-western blot assay. For South-western blot, the PCR fragments in agarose gels were transferred to nitrocellulose (NC) membranes and incubated with 100 µg purified HisrrnB-P1 rrnB P1 promoter was cloned into the GFP-reporter vector pGlow-TOPO, into the E. coli XLI-BLUE MRF' strain. Individual colonies of each treatment were selected and cultivated at 30°C overnight. The overnight cultures were diluted 200-fold and incubated for an additional 7 h, followed by the addition of 100 µM isopropyl-1-thio-β-d-galactopyranoside (IPTG) into the medium to induce protein expression for 1.5 h. The promoter activities were analyzed with three replicates as described above, and the relative promoter activity was normalized to the GFP synthesis rate per cell of E. coli cells co-transformed with the respective reporter construct and pBT-1634SacI, which expressed a non-viral protein, lambda-cI.Each of the plasmids pBT-1634SacI, pBT-AV1, pBT-CP, pBT-Rep, pBT-TrAP, pBT-Ren, and pBT-C4 was co-transformed with the pAY-WT or pE. coli DH5α cells. The total nucleic acids were extracted and treated with RQI DNase  at 37°C for 30 min, and subsequently used as the templates for 5′ RACE, using a SMARTer RACE cDNA amplification kit . The primer AY1022R , and subjected to 5′ RACE as described above. For 3′ RACE, the primer AY868F . Individual colonies were selected and cultivated in SC-U medium containing 2% dextrose at 30°C for 16 h. The overnight cultures were pelleted to remove the medium and resuspended in SC-U induction medium containing 2% galactose to an ODN. benthamiana at 3 dpi was used as a positive and protein size control, in which the GFP gene was driven by the CaMV 35S promoter.For western blot assays, individual colonies of each plasmid were selected and cultivated in 1 ml SC-U medium containing 2% dextrose at 30°C for 20 h. The overnight cultures were pelleted and resuspended in 100 µl 1× SDS loading dye and boiled at 100°C for 10 min, followed by SDS-PAGE and transferred to PVDF membrane. The GFP proteins in the samples were detected by using a GFP monoclonal antibody , followed by a rabbit anti-mouse IgG AP-conjugated antibody. Transiently expressed GFP in E. coli. Nucleotides other than those in the −10/−35 boxes are also involved in their promoter activity.The −10 and −35 box sequences To further test the conservation of the AV3 promoter regions among different isolates and strains of AYVV from different geographical distributions, the corresponding AV3 promoter regions of 20 representative AYVV isolates were aligned using ClustalW E. coliE. coli. To identify the host factors recruited by AV3 promoter, a biotin-labelled double-stranded DNA fragment of AV3 promoter region was synthesized and used as the bait. The E. coli rrnB P1 promoter, which is a strong sigma 70-dependent promoter rrnB P1 promoters bind to a 75 kDa protein . The results of MALDI-TOF MS analyses , initiator element (Inr), and downstream promoter element (DPE) cis-elements in AYVV-NT AV3 promoter remain undefined, the activity of AV3 promoter in bacteria and plants was supported by the presence of these transcripts with proper 5′ termini.It has been well-known that cis-elements in the AV3 promoter region. The result of predictions by SCOPE cis-elements in AV3 promoter, located near nts 785–801 of AYVV-NT genome, which also overlap with the prokaryotic conserved −10 box (nts 792–797). As shown in E. coli. We thus tried to test the influence of these prokaryotic cis-elements on virus infection cycle in plants. We generated an infectious mutant, pAYAV3PM-DI, containing the mutated AV3 promoter as shown in cis-element in the AV3 promoter region in close proximity to, or overlapping, the prokaryotic core motifs.Computer assisted predictions were used to search for putative eukaryotic N. benthamiana induced by the wild type and the mutant AYVV-NT at 21 dpi were shown in N. benthamiana is an artificial infection process. Begomoviruses are transmitted in a persistent manner by whitefly vectors Ageratum spp.) remains to be elucidated.The symptoms of E. coliSaccharomyces cerevisiae) cells. The yeast cells do not harbor chloroplasts or other plastids, ruling out the complexity that the AV3 promoter and downstream ORF might be active in these prokaryotic organelles within the eukaryotic cells E. colip<0.001) and the negative control pYES2/NT-C (p<0.01) (N. benthamiana (indicated by the thin arrow).In the previous study, we have demonstrated that the AV3 promoter could drive the expression of the first short downstream ORF at nts 866–892 in (p<0.01) . To vericis- and/or trans-elements involved in AV3 promoter-driven transcription, and the TSSs were characterized in bacteria and plants. The expression of the first downstream ORF was also demonstrated in yeasts. These results hinted that AV3 promoter might still retain certain degrees of activity in the present-day infection cycles of certain begomoviruses.In this study, the features related to the regulation and activities of AYVV-NT AV3 promoter were further characterized in both prokaryotic and eukaryotic environments. The E. coli SSB protein is intriguing and might shed some light on the evolutionary history of geminiviruses. SSB proteins are mainly involved in the replication, repair, and recombination processes of prokaryotic DNAs E. coli SSB can activate the transcription of supercoiled double-stranded DNA of phage N4 by the virion RNA polymerase E. coli SSB may mediate the recycling of DNA templates during the transcription by phage N4 virion RNA polymerase The interaction between AV3 promoter and On the other hand, the interaction between AV3 promoter and SSB might also be involved in the replication process of AYVV genome, since some DNA viruses encode SSB proteins on their genomes N. benthamiana  that remain to be elucidated.Although the activity of AV3 promoter and the translatability of the downstream ORF are shown in yeast cells here, the actual biological functions require further explorations. The nucleotide sequences of AV3 promoter region are highly conserved among different isolates of AYVV from different geographical distributions  over theIn conclusion, the results presented in this study confirmed the activity of AV3 promoter in a prokaryotic system, and suggested that AV3 promoter might possess a low level of activity in certain eukaryotic systems. The observations revealed more details of a cryptic promoter residing in the genome of AYVV, and provided further hints to the evolutionary history of geminiviruses.


Dlk1-Dio3 imprinted cluster as examples of lncRNA mechanisms functioning in the epigenetic regulation of mammalian genes.Recent transcriptome studies suggest that long noncoding RNAs (lncRNAs) are key components of the mammalian genome, and their study has become a new frontier in biomedical research. In fact, lncRNAs in the mammalian genome were identified and studied at particular epigenetic loci, including imprinted loci and X-chromosome inactivation center, at least two decades ago—long before development of high throughput sequencing technology. Since then, researchers have found that lncRNAs play essential roles in various biological processes, mostly during development. Since much of our understanding of lncRNAs originates from our knowledge of these well-established lncRNAs, in this review we will focus on lncRNAs from the X-chromosome inactivation center and the  These RNAs were previously considered as transcriptional “noise” or by-products until the development of technologies allowing unbiased high throughput sequencing of transcripts in cells. In 2002, following large-scale sequencing of mouse cDNA libraries, Okazaki pt class . The recvs. random), how XCI evolved, and the involvement of XCI in cancer development. Those topics are reviewed elsewhere [Female mammals have two X-chromosomes and therefore potentially a two-fold excess of X-linked genes relative to XY males. Such an imbalance in X-linked genes would lead to female early embryonic lethality. To overcome this problem, female mammals silence one (Xi) of the two X chromosomes to equalize X-linked gene dosages between the sexes during early development, a process known as X-chromosome inactivation (XCI) ,4. A larlsewhere ,6,7,8,9;Xist, which is expressed exclusively from the inactivated X-chromosome and essential for the establishment of XCI in early development [Xist is expressed at low levels from two active X-chromosomes. During the initiation stage of XCI, Xist is upregulated and begins to “spread” along one of the X-chromosomes and converts that allele into heterochromatin characterized by: (1) genome-wide loss of euchromatic marks; (2) gain of heterochromatic marks; (3) increased DNA methylation; and (4) silencing of gene expression. This very dynamic stage requires Xist. Upon establishment of XCI, the inactive X remains silenced throughout subsequent cell divisions. During this maintenance stage, Xist remains highly expressed from the inactive X. However, deletion of Xist RNA does not result in chromosome-wide gene reactivation [Xist RNA is not required at this stage of XCI [Early investigators discovered an X-linked locus, the X chromosome inactivation center (Xic), required to trigger X chromosome inactivation ,11,12. Aelopment ,14,15. Xtivation ,17,18. Te of XCI . Xist RNA contains six different repeat regions (A to F)  revealed at least two independent mechanisms for the silencing function of the A-repeats. One study suggests that the region is required for proper splicing of Xist RNA by directly interacting with splicing factor ASF/SF2 [Xist locus is transcribed through the RepA region in mESCs and we named it RepA RNA [RepA transcript drastically decreased Xist levels, similar to the phenotype observed following in vivo deletion of the repeat A region of Xist, suggesting that RepA RNA is an important regulator of Xist expression. We found that both Xist and RepA RNA can bind the chromatin repressor Polycomb repressive complex 2 (PRC2) through repeat A region and such interactions are required for the establishment of the chromosome-wide H3K27-3me heterochromatic mark during the initiation of XCI. Like proteins, lncRNA also exhibits functional domains. (A to F) B. The moA 5’-end . Transgeilencing . The funxpressed , making  ASF/SF2 . In anotRepA RNA . Knockdoin vitro transcribed 26-mer showed that only the first predicted hairpin is formed, while the second predicted hairpin mediates duplex formation among different repeats [Several laboratories have analyzed the structure of the repeat A domain in order to understand the molecular basis for RNA-protein interaction. The A-repeat region contains 7.5–8.5 tandem repeats (variable among different species) of a conserved ~26-mer sequence. Computational analysis indicates that each repeat has a double stem loop structure . However repeats ,25. One Xist repeats are not well understood. Nevertheless, Repeat regions C and F have shown to regulate Xist RNA localization, potentially through interacting with the transcription factor YY1 [Unlike A repeats, the structure and function of the other ctor YY1 ,27,28,29Xist upregulation is crucial for XCI, much effort has been made to elucidate cis-elements and trans-acting factors that control its expression. The following sections describe how lncRNAs and pluripotency factors regulate Xist expression.Since Xist, the XIC harbors several lncRNAs  [Tsx (Testis Specific X-linked Gene) [Xist expression through Tsix activation, while Jpx ) [Ftx (Five prime to Xist) [Xist RNA through unknown mechanisms. In addition to  lncRNAs A. One ofst locus ,32,33,34nstructs ,36,37, aate Xist . Another pathway . Althougin mESCs , no micrproteins . Further of Xist . (This mElement)  and Tsx ed Gene)  repress f Xist))  and Ftx to Xist)  activateXist from both, it has long been thought that X-inactivation is coupled to the pluripotency state of mESCs. Recent studies support this hypothesis by showing that pluripotent factors play a repressive role in Xist regulation. Conditional knockout of Oct4  or Nanog in male mESCs, where Xist is expressed at low levels and then silenced after differentiation, results in unexpected Xist up-regulation during differentiation [Xist is seen in female differentiating ES cells following Oct4 knockdown [Xist locus exhibits binding sites for Oct4, Nanog, and Sox2 [Xist expression, suggesting these factors may alter Xist function by binding other genetic elements [Tsix and Xite to repress Xist [Xist RNA expression [Since undifferentiated female ESCs have two active X chromosomes and express low levels of ntiation . Furthernockdown . The firand Sox2 ,47,48. Helements . Indeed,ess Xist . In addiXist, a different set of factors activates Tsix. For example, expression of Klf4, c-Myc, and Rex1 promotes Tsix expression [Tsix elongation. Factors such as RNF12 (Ring finger protein 12), an X-linked E3 ubiquitin ligase that targets Rex1 for degradation, can activate Xist expression even in male mESCs [Tsix and pluripotency factors act synergistically to repress Xist in undifferentiated ESCs. Interestingly, while one set of pluripotency factors represses pression , and Rexle mESCs  and is ele mESCs . TherefoXist is its ability to “coat” almost an entire X-chromosome. How Xist RNAs coat and spread to inactivate the X chromosome remains an open question. Interestingly, naturally occurring or induced X:autosome translocations show different degrees of XCI spread from the X into the autosomal DNA segment, suggesting that specific sequences facilitate spreading [Xist RNA [Xist transgene [Xist RNA and that a particular type of active LINEs may participate in local propagation of the XCI into regions that would otherwise escape [The most extraordinary feature of preading ,53. Thespreading . The theXist RNA . A transe escape . NonetheXist RNA loading [Xist RNA to the inactive X [Xist onto the X-chromosome rather than autosomes lies. Factors mediating this activity remain to be identified. In terms of trans-acting factors hnRNPU , a known nuclear scaffold protein, is known to be enriched on the inactive X chromosome  and to f loading ,58. A reactive X . HoweverXist RNA accumulation on Xi leads to chromatin changes, such as DNA hypermethylation, enrichment of macroH2A, loss of the euchromatic mark H3K4-3me and chromosome-wide establishment of heterochromatic mark H3K27-3me and mono ubiquinated H2A (H2AK119u1) [Xist lead to these global changes? Since Xist coats an entire X, it has long been postulated that Xist RNA binds and carries silencing factors, which are deposited as it coats regions during XCI. Thus, much effort has been applied to identifying Xist-interacting proteins.H2A H2AK1u1 [19,59AK119u1) ,61,62,63Xist-interacting trans-factors are Polycomb group proteins. These proteins are highly enriched on the inactive X-chromosome during XCI establishment [Xist RNA-dependent manner [Xist/RepA lncRNAs via repeat A region [Xist mutant lacking the A-repeats retains the ability to recruit PRC2 and PRC1 to Xi [Xist sequences can recruit Polycomb proteins directly or indirectly. Interestingly, in cells with the depletion of a key component of PRC2, some PRC1 proteins can localize to induced Xist RNA while others cannot, suggesting Xist recruits PRC1 by both PRC2 dependent and independent mechanisms [Xist, suggesting that either Trithorax proteins also function in gene repression or that Xist RNA can activate specific genes [The best-studied lishment ,61,64. Dlishment . Howeverlishment . Polycomlishment . Upon ret manner ,69. As dA region ,26,70. FA region . NotablyC1 to Xi ,69, indichanisms . Surprisic genes . Xist RNA in the past two decades have greatly advanced our understanding of how lncRNAs regulate gene expression epigenetically. However, many questions remain unanswered. For example, it is unclear how Xist specifically spreads along the future Xi but not along the activated X. It is also not yet understood how Xist RNA interacts with so many different proteins and what determines the specificity of those interactions. And since Polycomb proteins do not function in establishment of XCI in embryos, the mechanisms used to establish the repressive state of the Xi are not yet identified. Studies of http://www.mousebook.org/catalog.php?catalog=imprinting). Genomic imprinting is another dosage regulation mechanism used by mammalian cells. While most autosomal genes are expressed from two parental alleles, some genes are expressed monoallelically in a parent-of-origin manner. This epigenetic phenomenon is termed imprinting. To date, over 100 imprinted genes have been validated in mouse , the maternally expressed lncRNA at the Dlk1-Dio3 locus, to regulate imprinting at this locus. Like X-inactivation, genomic imprinting is tightly controlled by epigenetic mechanisms such as DNA methylation and chromatin modification . InteresGtl2 was discovered following an insertional mutagenesis gene trap screen to isolate genes differentially regulated during mouse embryonic development [Gtl2 promoter caused dwarfism in mouse offspring only through paternal inheritance, not via maternal transmission [Gtl2 gene suggested that its product was a non-coding RNA (ncRNA) based on the observation that the Gtl2 contained no significant open reading frames [Gtl2 was mapped to a region of mouse chromosome 12 (12qF1) thought to contain imprinted genes, due to the observation that in that region uniparental disomy led to embryonic lethality [Gtl2 expression levels in parthenogenetic embryos led to the hypothesis that Gtl2 is paternally imprinted [Gtl2 is in fact expressed exclusively from the maternal allele [elopment . The gensmission ,79. Subsethality . The patl allele ,82,83. Tl allele ,85.Gtl2, other imprinted genes that form a cluster and are co-regulated with Gtl2 were also identified [Dlk1, Rtl1, and Dio3 . Three DMRs, located between Dlk1 and Gtl2 (hence intergenic DMR or IG-DMR), at the Gtl2 promoter, and downstream of Dlk1 have been identified [Not long after the discovery of entified ,87,88,89and Dio3 , whereasicroRNAs . All matanscript . Imprintentified . While IGtl2 knockout mice suggests that Gtl2 regulates genomic imprinting. One study showed that mice with maternal deletion (300 bp of the promoter and exons 1–5) of the Gtl2 gene show bidirectional loss of imprinting of all genes in the Dlk1-Dio3 locus, whereas no effect was detected when the deletion was transmitted paternally, suggesting that Gtl2 controls genomic imprinting at this locus [Gtl2 knockout mice phenocopy IG-DMR knockout mice [Gtl2 (and/or its downstream ncRNAs) potentially regulates Dlk1-Dio3 imprinting. Indeed, the same study showed that maternal deletion of Gtl2 resulted in increased IG-DMR methylation on the maternal allele [Gtl2 and/or its downstream ncRNAs may function to maintain the unmethylated status of the maternal IG-DMR through an unknown mechanism. Interestingly, an earlier study deleting ~4Kb of the Gtl2 promoter plus exons 1–5 yielded significantly different results [Dlk1, Rian, and Mirg was detected when deletion mutation was transmitted paternally. The difference between these two studies could lie in the variable size of the deletion of the Gtl2 promoter (300 bp vs.~4 Kb). Since the region flanking the Gtl2 promoter is a well-established DMR, these discrepant results suggest a functional role for the Gtl2 DMR and underscore the importance of studying Gtl2 function using approaches that minimally perturb the DMR, such as RNAi. Genetic evidence from is locus . Gtl2 knout mice ,93, impll allele . Thus, G results . The autGtl2 and its downstream ncRNAs were aberrantly silenced contributed poorly to chimaeras and failed to generate mice in which every cell is contributed by an iPSC  [Gtl2 promoter [Gtl2 and downstream lncRNAs [Gtl2 in preserving the developmental potential of iPSCs during reprogramming.A recent study showed that mouse induced Pluripotent Stem Cells (iPSCs) in which SC mice) . In contSC mice) . Furtherpromoter . In a su lncRNAs . These fGTL2/MEG3 is seen in many tumor types, including human pituitary adenoma, brain tumors, and liver tumors [GTL2/MEG3 overexpression inhibits tumor cell proliferation in vitro [Gtl2 knockout and wild-type mice revealed an upregulation of genes correlated with angiogenesis in knockout mouse [Gtl2 may function as a tumor suppressor in part by inhibiting angiogenesis. Furthermore, it was suggested that a postulated tumor-suppressing function of Gtl2 might stem from its ability to induce p53 accumulation, thereby activating expression of some p53 target genes [Loss of r tumors ,98,99. Gin vitro ,101,102.ut mouse , suggestet genes ,101. Gtl2 to regulate genes within the Dlk1-Dio3 locus. The modes of regulation considered are not mutually exclusive: Gtl2 function might be exerted through combinatorial mechanisms or carried out differentially in response to specific environmental cues.lncRNAs employ diverse mechanisms to regulate gene expression at both the transcriptional and post-transcriptional level (reviewed in ). Here, Dlk1-Dio3 locus caused loss of imprinting when the deletion occurred at the maternal rather than the paternal allele demonstrated that the maternally-inherited unmethylated DMR is essential for the imprinting status of the locus [Gtl2 knockdown results in hypermethylation of the maternal IG-DMR suggests that Gtl2 is required to maintain its unmethylated status. Potential mechanisms include Gtl2 RNA interaction with and sequestration of positive DNA methylation regulators (such as DNA methyltransferases) or by Gtl2 actively recruiting negative regulators of DNA demethylation (such as Tet proteins) to keep IG-DMR unmethylated  in the maternal allele in midgestation mouse embryos [The role of histone modification in regulating imprinting of the e IG-DMR . The Gtl embryos . It is nGtl2 directly binds PRC2, and that Gtl2 knockdown in mouse ESCs results in a reduced Ezh2 occupancy at the Dlk1 promoter and increased Dlk1 expression [Gtl2 can silence gene expression from the maternal allele of the Dlk1-Dio3 locus through chromatin modification (Gtl2 recruits Ezh2 to chromatin and whether Gtl2 uses the same mechanism to silence genes other than Dlk1 within the same imprinted locus.Our recent studies demonstrate that pression . This dafication B. It is Gtl2 deletion abolishes expression of downstream lncRNAs and that expression of these RNAs is coordinated suggests that Gtl2 functions to maintain expression of other maternally-expressed ncRNAs from the Dlk1-Dio3 locus [Gtl2 may serve as a ceRNA to titrate away microRNAs targeting other maternally-expressed transcripts at the same locus (Gtl2 and those maternally-expressed transcripts. It will be of interest to determine whether lncRNAs regulate each other through this novel mechanism. The observation that o3 locus ,93. The o3 locus . It has o3 locus . Indeed,o3 locus . Therefome locus C. HoweveSince the completion of the Human Genome Project, our perception of the mammalian genome has undergone a dramatic shift. The number of non protein-coding transcripts identified over the past decade has increased exponentially. We now realize that lncRNA is far from the “dark matter” of the genome, but instead plays a critical function in gene regulation. Since XCI and genomic imprinting are two well-defined molecular activities, lncRNAs from XIC or imprinted loci provide ideal systems to understand epigenetic control of how genes are regulated. The mechanisms identified will likely be applicable to newly discovered lncRNAs.