Trans-acting regulators were not necessarily associated with genes coding for chromatin modifying enzymes. Strikingly, “labile” and “persistent” epi-polymorphisms were associated with poor and strong genetic control, respectively, showing that genetic modifiers contribute to persistence. These results estimate the amount of natural epigenomic variation that can be lost after transient environmental exposures, and they reveal the complex genetic architecture of the DNA–encoded determinism of chromatin epi-polymorphisms. Our observations provide a basis for the development of population epigenetics.Natural populations are known to differ not only in DNA but also in their chromatin-associated epigenetic marks. When such inter-individual epigenomic differences (or “epi-polymorphisms”) are observed, their stability is usually not known: they may or may not be reprogrammed over time or upon environmental changes. In addition, their origin may be purely epigenetic, or they may result from regulatory variation encoded in the DNA. Studying epi-polymorphisms requires, therefore, an assessment of their nature and stability. Here we estimate the stability of yeast epi-polymorphisms of chromatin acetylation, and we provide a genome-by-epigenome map of their genetic control. A transient epi-drug treatment was able to reprogram acetylation variation at more than one thousand nucleosomes, whereas a similar amount of variation persisted, distinguishing “labile” from “persistent” epi-polymorphisms. Hundreds of genetic loci underlied acetylation variation at 2,418 nucleosomes either locally (in  Chemical modifications of chromatin, such as DNA methylation, incorporation of histone variants, or post-translational modifications of histone proteins, constitute the “epigenome” and confer specific properties to genome functions. Epigenomes differ from one individual to another, opening the exciting perspective to decipher the origins of these differences and their impact on physiology. However, population epigenomics remains challenging because, unlike DNA mutations, epigenetic hallmarks are themselves regulated. They can change upon particular environmental conditions, they may be inherited epigenetically, or they may result from activities encoded in the DNA. Thus, estimating the stability of intra-species epigenomic variation and its dependence on DNA polymorphisms is essential. Using a chemical perturbation of yeast cells as an experimental model system, we found that acetylation variation was persistent at some nucleosomes and labile at other nucleosomes. By studying a segregating population, we mapped DNA polymorphisms that affected chromatin acetylation levels at numerous nucleosomes. Strikingly, nucleosomes showing persistent variation of acetylation corresponded to those for which acetylation was under genetic control. Thus, part of epigenomic variation is stabilized by a DNA–encoded determinism, and another part can be reprogrammed if environmental perturbations are experienced. These results provide a necessary basis for upcoming developments in population epigenomics. A. thaliana were found to differ in their methylation level at about 10% of all CCGG sites A. thaliana accessions were compared for their level of genome compaction in response to light S. cerevisiaeRecent studies have shown that individuals largely differ in their epigenomic chromatin signatures. This finding makes tracking epigenetic marks in natural populations attractive, including investigating their possible contribution to the variation of common physiological traits. So far, epigenomic intra-species diversity has been primarily studied at the level of the methylome (DNA methylation profile). Natural accessions of A. thaliana, it was found to be several orders of magnitude higher than the rate of DNA variation FLC locus, whose expression prevents flowering, becomes silenced by a well-described mechanism after several weeks of vernalization  on time scales ranging from seconds to multiple generations +-dependent manner Streptomyces platensis, or butyrate, a natural product of the intestinal flora In the particular case of chromatin acetylation, direct coupling between epigenetic signatures and energy metabolism (obviously related to diet) is known to happen at least at three levels. First, sirtuins are known to deacetylate histones and a number of other proteins in a NADcis  or in trans (i.e. distantly) cis-modifiers are transposon insertions FMR1 gene, where moderate expansions mediate hyper-acetylation of the locus and increased mRNA levels, resulting in Fragile X Tremor Ataxia Syndrome trans-acting genetic modifiers of chromatin states are sequence changes within chromatin modifying enzymes trans by affecting the activity of upstream regulators of chromatin modifying machineries. The numerous examples of DNA-encoded chromatin differences suggest that individuals may harbor distinct epigenotypes simply as a result of their different genetic content  Single Nucleosome Epi-Polymorphisms (SNEPs) as the intra-species variations of the level of an epigenetic mark carried on a nucleosome. The polymorphic mark may be any histone post-translational modification or the incorporation of a histone variant. A SNEP for one such mark then corresponds to the preferential presence of the mark at one nucleosomal position in some individuals or strains as compared to others. Consequently, SNEPs of various epigenetic marks may be carried on the same nucleosome. By tracking H3K14ac SNEPs, we describe here both an experimental reprogramming experiment and the genetic architecture of H3K14 acetylation variation. The results show that some epi-polymorphisms are reprogrammed after a transient perturbation of chromatin states whereas others persist, and this persistence can, at least partly, be explained by genetic determinants encoded in the DNA.We previously identified thousands of yeast nucleosomes carrying differential levels of H3K14 acetylation between two wild The present study focuses on one epigenetic mark, the acetylation of histone H3 at Lysine 14 (H3K14ac). For simplicity, the terms ‘SNEP’ and ‘epi-polymorphism’ are used here interchangeably to refer to H3K14ac epi-polymorphisms.S. cerevisiae strains (BY and RM). Here we assessed the stability of these epi-polymorphisms by transiently exposing the two strains to an extremely perturbing environment .BY and RM cells were treated with high concentrations of TSA for 4–5 generations. As expected, this treatment caused a bulk increase of H3K14 acetylation in both strains . Cells wNucleoMiner) to the newly generated dataset (see FDR) of 0.0001, we detected 2,379 SNEPs after recovery. Interestingly, 898 of them were new ones: for these nucleosomes, the level of K14 acetylation was not significantly different between the strains before treatment. They were unlikely false negatives, because detection power was higher in the initial search than after recovery from TSA (12 versus 6 microarrays used). Rather, these induced SNEPs illustrate that epi-polymorphisms may indeed result from new environmental exposures. Interestingly, 524 of the 898 induced SNEPs were ‘isolated’, i.e. their two flanking nucleosomes were not SNEPs after treatment and recovery. Of these, 436 were initially in a context where neither of the flanking nucleosome was a SNEP. This specificity illustrates that SNEPs can be induced at precise nucleosomes and not necessarily on consecutive ones.We performed two complementary statistical analyses on the data. First, we specifically searched for induced and persistent SNEPs. To this end, we applied our previously described SNEP detection algorithm . Among these, 1,076 belonged to the list of nucleosomes containing initial SNEPs and we therefore qualified these SNEPs as ‘labile’  and contained more labile SNEPs than expected . This suggests that epi-polymorphisms carried on specific single nucleosomes are less stabilized than those established on consecutive nucleosomes.We previously reported that for ∼50% of SNEPs, no acetylation variation was detectable on their flanking nucleosomes P = 0.003, see The mechanism(s) by which labile SNEPs are established and lost remain unknown. However, when confronting our data to a published map of histone turnover rates The reprogramming experiment presented here was designed to test the stability of SNEPs and not the effect of treatment in each strain. Assessing precisely the amount of reprogramming within each strain would require a dataset where all samples prior and post treatment are processed in parallel, by the same experimenter, using common batches of reagents. This was not the case here, and confounding experimental factors would likely bias any statistical inference of reprogramming within each strain. However, we made interesting observations when inspecting the fold change of acetylation between the levels before treatment and the levels after recovery. First, the mean fold change across all nucleosomes was similar between the two strains . This isaceQTL). A first scan was performed at a genome x epigenome scale. To do so, we selected 36,558 nucleosomes with H3K14ac heritability higher than 0.2, and for each of these we searched the entire genetic map for linkage. Calculations were done using a convenient platform called eQTNMiner, which was originally designed for the Bayesian Inference of nucleotide-resolution eQTLs eQTNMiner reports linkage evidence as a Bayes Factor (BF), which quantifies the relative support of the data in favor of the alternative hypothesis (there is a QTL) against the null hypothesis (there is no QTL). We recorded linkages at various Bayes Factor thresholds, and computed empirical significance of each threshold by a permutation test (FDR = 0.034), we found significant linkages for a total of 2,418 nucleosomes  and the usual large regions scanned for cis-eQTLs (10–50 Kb). At BF = 50 (corresponding to FDR = 0.0007), we found cis-linkages involving the control of 4,173 nucleosomes. There were 17% of SNEPs  for which an aceQTL could be found in at least one of the two scans. Given the rather small size of the segregating population examined, we can assume that some genetic linkages were missed. This fraction is therefore a lower-bound estimate of the ‘genetically encoded’ class of SNEPs. All further analysis was done on results obtained from the first scan only, as they reflect both cis and trans regulators, with effects strong enough to pass a stringent genome-by-epigenome significance level.We then applied a second scan to specifically search for trans-acting aceQTLs varied greatly , which encodes different transcriptional co-factors in BY(MATα) and RM(MATa). Of the 148 nucleosomes controlled by this locus, 83 had a marked acetylation difference between BYα and RMa that could be detected without replicated experiments. To directly test if MAT accounted for the associated acetylation variation, we performed two additional ChIP-chip experiments on strains having reversed mating types (BYa and RMα) and we tested for acetylation variation between isogenic strains differing only at MAT. The expected difference was observed for 69 of the 83 nucleosomes tested . This suggests that many other causes for acetylation variability exist. Intuitively, trans-regulation could result from sequence variants targeting chromatin modifying enzymes. To examine this possibility, we analyzed relevant Gene Ontologies (GO). We saw that eight of the seventeen master-aceQTLs did not contain any gene annotated to participate in chromatin regulation  do not necessarily correspond to transcription factors Only a small fraction (16%) of the nucleosomes controlled in gulation . Among ance only . Thus, taceQTLs  corresponded to loci previously identified as master eQTLs GPA1-S469I polymorphism targets a G-protein α subunit and underlies expression variation of many pheromone-responsive genes aceQTL affecting 24 nucleosomes that reside within or near these target genes. GPA1-S469I is therefore a likely regulator of both expression and acetylation at these loci. For similar reasons, a transposon insertion altering the HAP1 transcription factor is likely a regulator of both expression and acetylation of target genes . For every linkage between a genetic marker m and a nucleosome ν, we examined if a significant eQTL could be found between m and a gene located within 10 Kb of ν. For 31% of aceQTLs, no such concordance could be found. Note that statistical power was much higher to detect eQTLs than aceQTLs because many more segregants were used. It is therefore unlikely that these cases corresponded to false negatives. Overall, the strength of linkage was poorly correlated between aceQTLs and eQTLs  across extreme environmental perturbations because their causative variants do. We sought to test this principle by comparing the results obtained on SNEP persistence through temporary TSA exposure with the genetic properties of leosomes . Note thse SNEPs . We therle SNEPs . Consist mapping . In addi mapping .Finally, genetic linkage results alone may sometimes not reflect the strength of genetic determinism. For example, if numerous QTLs with small individual contribution altogether control the acetylation value of a nucleosome, then none of them may be found despite a complete overall genetic determinism. Similarly, a complete control by epistatic or antagonistic genetic loci may not be detected. However, even in such complex genetic cases, the overall determinism can still be estimated by the genetic heritability of the acetylation trait in the segregating population. We therefore examined heritability itself, and found that increasing heritability values were unambiguously associated with gradual shifts towards higher persistence . Thus, geQTLs, with both cis and trans regulators and the presence of master regulators affecting numerous targets.This study reveals that H3K14ac epi-polymorphisms are not equally sensitive to environmental reprogramming. Some of them can be lost after temporary perturbations while others persist. This persistence clearly correlates with the presence of genetic determinants that encode epi-polymorphisms in the DNA. This genetic control is complex and resembles architectures previously described for is quantitative, because it depends on the number of cells that carry the acetylation mark, which corresponds to an equilibrium state of the population resulting from many biochemical reactions. The fact that this level varies as a complex trait shows that aceQTLs change the proportion of cells that are acetylated at their target nucleosome. In other words, aceQTLs are genotypes that modify the probability that a given nucleosome is acetylated in a given cell at a given time. How this happens will probably remain unknown until new technologies are developped to interrogate single nucleosome states in single cells. Also, the quantitative variability studied here is different from several epimutations described in plants where strong silencing of large chromosomal domains is established by a combination of many molecular and structural changes.Importantly, our results further highlight the quantitative nature of the variation of acetylation levels. At any given time, a nucleosome of a given cell is or is not acetylated. Thus, acetylation is sometimes considered a discrete variable. However, the average acetylation level of this nucleosome across a population of cells et al. did not find any consistent overlap between expression Quantitative Trait Loci (eQTL) modifying the transcriptome of brain tissues and Quantitative Trait Loci modifying the methylome of these tissues (methQTL) et al. reported a clear consistency between eQTL and methQTL in HapMap lymphoblastoid cell lines aceQTLs linkages overlap with eQTLs. The remaining fraction of aceQTLs could correspond to regulations of non-coding transcripts, which were not interrogated by our study. Alternatively, given our previous association between SNEPs and transcriptional plasticity aceQTLs modify the chromatin in a way that manifests only upon transcriptional stimulation. In other words, genetic modifiers could increase K14 acetylation of a locus, which would then become more responsive to transcriptional activation or repression upon specific conditions. In such cases, aceQTLs could participate in gene x environment interactions by creating epi-polymorphisms that personalize the way the genome responds to the environment.Whether the genetic control of chromatin variability also controls the level of nearby gene expression appears to be context specific. In humans, Gibbs MAT locus affects chromatin acetylation of many target loci. This locus determines the cell's mating type by dictating specific transcriptional programs. The MATα allele encodes two regulatory proteins: α1, which activates α-specific genes, and α2, which represses expression of a-specific genes. The MATa allele encodes the a1 protein only, which heterodimerizes with α2 in diploid a/α cells to form a repressor of haploid-specific genes. How specific transcriptional programs are established in a and α cells has been the focus of many studies, revealing the interplay with chromatin acetylation regulation at specific target promoters. In α cells, the cooperative binding of α2 and Mcm1 recruits the Tup1-Ssn6 repressor, which is known to interact with several histone deacetylases a cells, α-specific genes are occupied by Sum1 which is known to recruit the NAD+-dependent histone deacetylase Hst1 to repress transcription MAT displayed an epigenomic profile totally predictable given the known transcriptional control. This was the case for the BAR1 gene for example, which encodes a secreted protease specifically expressed in a cells. The chromatin signature of the entire locus was affected by the mating type. MATa strains displayed occupancy and acetylation intensities typical of highly expressed genes MAT displayed unexpected patterns of chromatin variation. One such example was the KAR4 locus, which encodes two forms of a transcription factor essential for nuclear fusion during mating. The long form is expressed in mitotically growing cells, and the short form is induced in response to pheromone from a transcriptional site about 30 nucleotides downstream the first ATG MATa and MATα growing cells in the 3′ part of the gene, which were not accompanied by differential transcriptional levels , or a specific set of nucleosomes in the promoter (SAG1) or the 3′ region (KAR4).We proved that the l levels . How a ccleosome . These taceQTLs were not preferentially found at sites coding for chromatin modifying enzymes may seem counterintuitive: one could expect that DNA polymorphisms affect chromatin states by modifying the sequences of enzymes directly involved in chromatin regulation. However, protein complexes that regulate chromatin are themselves highly regulated, and any DNA polymorphism affecting these upstream regulators has the potential to induce chromatin modification indirectly. In fact, this is what happens with MAT alleles: they do not code for chromatin remodelling enzymes but they determine distinct recruitments of chromatin modifiers at specific sites. This observation is very similar to results from eQTL mapping, from which we know that genetic modifiers of gene expression do not necessarily reside in direct transcriptional regulators AMN1, GPA1, IRA2 and MKT1 yeast genes were all validated as eQTL players but they do not encode direct regulators of transcription aceQTLs likely follow a similar rule: causative polymorphisms may reside not only within chromatin modifying complexes but also in their upstream regulators.More generally, the fact that S. cerevisiae, at least three HATs are known to acetylate Lysine 14 of Histone H3: Gcn5p We show that a transient environmental change imposed by TSA treatment can reprogram a subset of H3K14ac epi-polymorphisms: numerous new SNEPs were induced, and numerous initial SNEPs were lost. An important consideration is that TSA imposed a perturbation but did not necessarily saturate the acetylation of H3K14 on all nucleosomes. In normal conditions, H3K14 acetylation levels result from a balance between the activity of histone acetyltransferases (HATs) and deacetylases (HDACs). In The reprogramming observed preferentially corresponded to a gain of acetylation in the BY strain, with a majority of labile SNEPs corresponding to hypo-acetylated nucleosomes in the BY strain that returned to levels comparable to those of the RM strain. An intuitive interpretation of this asymmetry would be that TSA was more efficient to induce hyperacetylation in BY than in RM. The strains are probably not equally sensitive to TSA, given the two previously mapped QTLs of growth fitness in the presence of TSA that segregate in the BYxRM cross More generally, it will be essential to question the origin of the ‘labile’ SNEPs: those which gained but also those which lost acetylation in BY, and the few where the change happened in RM. Theoretically, the differences in these epigenotypes may have occurred any time between the initial divergence of the strains and the last hours before the stocks were frozen in our laboratory. In other words, our study identified their lability but not their origin and age. A related question is how stable are labile and newly induced SNEPs: how harsh a treatment is needed to reprogram them? If some ‘labile’ SNEPs are old, they have been maintained for a long time and one would expect them to be stable unless extreme environmental perturbations are experienced, like in our TSA-based assay. Likewise, it is possible that additional SNEPs could have been modified if we had applied a stronger or longer treatment. As mentioned above, class III HDACs such as Sir2p are not inhibited by TSA, and other SNEPs would probably be called ‘labile’ if an inhibitor of sirtuins was used instead of TSA. In contrast, some ‘labile’ SNEPs may be very unstable and might also disappear after a prolonged but unperturbed culture. It will therefore be interesting to monitor the dynamics of SNEP appearance and loss in unperturbed conditions. A time-course experiment tracking the H3K14ac epigenome of one strain over long culture periods would help determine its stability.How and for how long were new SNEPs induced despite the fact that the treatment applied was the same for the two strains? As mentioned above, this can possibly result from a difference in the way the strains respond to the treatment, and this difference might or not be genetically encoded. Although our experiments were not designed to address this, it is also possible that epi-polymorphisms arise stochastically in particular environments regardless of the genetic background. This has been suggested by a recent study where the methylome of isogenic mice fed with high levels of methyl precursors was tracked over generations We observed a clear correlation between environmental persistence and genetic control of acetylation variation. Importantly, the two datasets (reprogramming and QTL mapping) were generated and analysed independently: at different dates, by different experimenters, the former using the parental strains only and the latter using the segregants. Thus, we believe that this correlation truly reflects the robustness of DNA-encoded epi-polymorphisms to environmental reprogramming. However, our observations do not imply that all cases of epi-polymorphism persistence result from their anchoring in DNA. It remains entirely possible that specific cases have a purely epigenetic basis. For example, H3K14 acetylation may be more robust to environmental perturbation if it is accompanied by additional epigenetic marks that are commonly associated with it, such as H3K4 di- or tri-methylation, or H3K9 acetylation epigenetic processes might contribute to evolutionary change, at least in part by expanding the range of phenotypic variants on which natural selection can act” Given our observation that both labile and persistent epi-polymorphisms coexist abundantly in natural epigenomes, we emphasize the importance of the stability of epi-polymorphism in the current debate on whether and how epigenotypes contribute to evolutionary mechanisms. As outlined by B. Turner, this question is fundamental because epi-polymorphisms potentially enable environmental conditions to reprogram molecular events for a durable time. This way, “Importantly, loci harboring DNA-encoded epi-polymorphisms may remain highly susceptible to epigenetic regulations: as mentioned above, SNEPs represent small quantitative differences of molecular regulations, and it is likely that they do not prevent from switching between radically different epigenetic states. Thus, the prolonged duration of DNA-encoded epi-polymorphisms does not necessarily impair fitness in fluctuating environments, where adaptation requires rapid and profound chromatin remodelling at critical loci.In addition, chromatin changes may reveal the effect of cryptic genetic variations. For example, a mutation occuring at a silenced locus can remain cryptic until silencing of the locus is alleviated. Such epigenetic alleviation might also be either labile or persistent, with different consequences on the cryptic variation: the phenotype and therefore the cryptic variation itself may be exposed to selection for a longer period of time if alleviation persists.Altogether, our observations provide a necessary basis for the upcoming development of population epigenetics, where epi-polymorphisms of natural populations will be interpreted and possibly associated to the variation of common traits.MATα lys2Δ0  and BY4715 MATa lys2Δ0 derivatives of S288c, RM11-1a MATa leu2Δ0 ura3Δ0 hoΔ::KanMX wine strain MATα leu2Δ0 ura3Δ0 hoΔ::KanMX amn1-A1103T derivative  precipitation and hybridization on Affymetrix Whole Genome Yeast Tiling 4-bp resolution microarrays 600 = 0.15 using an overnight starter culture and was grown at 30°C until OD600 reached 0.5–0.6. 45 ml of the culture was pelleted and frozen for later Western blot analysis (sample t1). TSA (Wako 204-11991) was resuspended in ethanol 50% at 45.5 mg/ml and 3.9 ml of this stock was added to the remaining of the culture . The culture was kept at 30°C for 3–4 doubling times (OD600 = 3) and 20 ml was pelleted and frozen for Western Blot analysis (sample t2). Remaining cells were washed twice with 20 ml TBS1X  and 1% of the suspension was added to 50 ml of SDall and incubated at 30°C. The next day, 10 microliters of the overnight culture was transfered to 50 ml fresh SDall medium and incubated at 30°C for 6 hours. This culture was used to inoculate 200 ml fresh SDall incubated at 30°C until OD = 0.9. This procedure corresponded to about 20 generations post-treatment. 25 ml of the final cell suspension was pelleted and frozen for Western blot analysis (sample t3) and the remaining of the culture was used for chromatin immunoprecipitation.The following protocol was applied on 3 independent cultures for each strain. A 110 ml culture of SDall medium was inoculated at ODXart’ correspond to strain Xafter recovery from TSA treatment  were done at different dates, by different experimenters. We therefore preferred to use inter-strain log-ratios to ensure a consistent comparison of the inter-strain difference within each dataset.A matrix of raw microarray hybridization intensities was considered that contained the BY (6 arrays), RM (6 arrays), BYart (3 arrays) and RMart (3 arrays) ChIP-chip values for all probes having a single perfect match on both BY and RM genomes. Here ‘NucleoMiner on the BYart, RMart ChIP-chip dataset, together with the previously described BY and RM nucleosome mapping experiments FDR<0.001  after recovery from TSA. Note that fewer biological replicates were used after recovery (3 for each strain) than before treatment (6 for each strain), which explains the detection of fewer SNEPs . The intersection between the two lists of SNEPs corresponded to 1,481 nucleosomes that were called ‘persistent’ SNEPs (magenta dots on 2(RM/BY)before tratment−log2(RM/BY)post recovery|.We specifically searched for persistent SNEPs by running NucleoMiner with option -n lqq. We then computed estimates of nucleosome-level ChIP intensities. For every nucleosome, we considered signals from probes that were entirely contained in the overlap between nucleosome position in BY and nucleosome position in RM. These signals were further corrected by quantile normalization (to account for probe effects) and averaged using the eqmr-fdb command of eQTNminer-m qnorm.We generated an extremely dense genetic map by inferring, at every SNP, a probabilistic genotype given the genotypes previously described at marker positions h = (varS−varE)/varS, where varS is the variance across all segregants and varE the environmental variance, estimated by the pooled variance of parental replicates. We noticed that one BY experiment had very high variation, therefore varE was estimated by the pooled variance of 5 BY and 6 RM ChIP-chip experiments.For every nucleosome, heritability of acetylation level was then computed as aceQTL was performed using the eqmr-ftr command of eQTNMinereQTNMineri genotype at SNP j (gijk) on the acetylation level of the k-th nucleosome (yik) is assumed to follow a purely additive linear model: yik = μ+ajkg×gijk+εijk, where μ is the mean acetylation level of that nucleosome for individuals with g = 0, and where ajk is the additive effect of the minor allele at SNP j. The residual εijk is assumed to be normally distributed, with mean zero and variance 1/τ equal to the variance of acetylation levels within each genotype class. Let P0k denote the probability of the acetylation data Yk under the null hypothesis that there are no aceQTL controlling nucleosome k . Similarly, let P1jk denote the probability of the acetylation data Yk under the hypothesis that SNP j is an aceQTL of nucleosome k. In this case, the effect size ajk is modelled as being drawn from mixtures of normal distributions centered on 0 (see below). The Bayes Factor reflecting genetic linkage between SNP j and nucleosome k is defined as BFjk = P1jk/P0k and measures the relative support for the hypothesis that SNP j is an aceQTL of nucleosome k, versus the null hypothesis. As suggested by Servin & Stephens jk is drawn from mixtures of normal distributions centered on 0 with variance σa2/τ. Specifically, we assumed a mixture of 6 normal with σa2 = , we computed a Bayes factor for each value of σa2, and considered the mean Bayes factor as our summary statistics. We controlled the False Discovery Rate empirically by re-scanning 100 permuted datasets. On average, only 20,288 linkages were obtained at a Bayes Factor threshold of 1000 from a permuted dataset, while 592,368 linkages were obtained at this level from the actual data . In total, cis-aceQTLs were found for 4173 nucleosomes. 668 of these nucleosomes ( = 16%) were located within 20 Kb of a region known to affect nearby chromatin states .A second scan was performed on all 59,936 nucleosomes to specifically detect utations . We obseaceQTL for nucleosome i and marker m found in the first scan was called trans-aceQTL if m was at least 50 Kb away from any cis-aceQTL found for i in the second scan.Finally, an aceQTLs affect the acetylation level of a significantly high number of nucleosomes. To do so, we first reduced the results to the best linkage scores in trans. For each nucleosome for which a trans-aceQTL was found, the marker M with highest linkage score was recorded and all significant linkages to markers close to M were discarded. If additional significant trans-aceQTLs remained for this nucleosome, the procedure was repeated. We then segmented the genome in 20 Kb bins and counted the number of reduced trans-aceQTLs in each bin (P<0.05 after Bonferroni correction), which could be concatenated to 17 non-consecutive bins. We then searched each bin for the best candidate polymorphism regulating the set of target nucleosomes: for every nucleosome i having a trans-aceQTL in the bin, we computed at every SNP k the posterior probability Pi(k) that the SNP is causal. This probability can be directly computed from the output of eQTNminer. Let i,mB be the Bayes Factor for linkage between nucleosome i and SNP m, and iS the sum of i,mB across all m of the genome, then the probability is simply Pi(k) = Bi,k/Si. These probabilities were then sumed across all nucleosomes in linkage to the bin, and the best candidate was identified as the SNP maximizing this sum  and this search was then labelled as ‘non-significant’ . This corresponds to the usual 0.01 threshold divided by 8 which is the average number of genes examined within 20 Kb of the yeast genome . Following this criterion, 790 of the 2,530 aceQTL linkages (31%) did not correspond to eQTL. Note that the detection power was much higher for eQTL than for aceQTL, as more segregants were used. Thus, it is unlikely that we missed relevant eQTLs at this relaxed threshold.To then determine if ificant’ . We conseQTLs were aceQTLs. Redundant eQTLs supported by adjacent markers were removed as above. For each eQTL found at FDR = 0.035 between a marker m and a gene g, we considered all aceQTL scores between m and any nucleosome located with 10 Kb of g and recorded the best one. When no aceQTL was found at the relaxed threshold of BF = 1, then this search was called “non significant” . This number was then averaged across all target loci to define the “Average fraction per locus” indicated in aceQTLs were classified as being ‘also eQTL’, ‘aceQTL only’ or ‘partial’ based on whether this fraction was higher than 75%, lower than 25%, or in between, respectively.To estimate whether master trans-er eQTLs , we procaceQTL was found, as this corresponds to the expectation of a genetic control underlying persistence; ‘negative’ SNEPs were those for which no aceQTL was found. Fraction of positives and negatives were computed at increasing persistence values.http://www.ebi.ac.uk/arrayexpress/) under accession numbers E-MTAB-575 and E-MTAB-1025. Additional processed data files are available from our web site: http://www.ens-lyon.fr/LBMC/gisv/snep/All ChIP-chip raw data is available from ArrayExpress .Western-Blot of whole protein extracts from BY and RM strains. Times (PDF)Click here for additional data file.Figure S210(P) where P is the statistical significance. R: Spearman correlation coefficient. Red-circled dots: nucleosomes corresponding to labile SNEPs, i.e. being a SNEP because they have on the X-axis a P-value lower than the 9.27×10−6 cutoff defined in Nagarajan et al. 2010, and being labile because they have on the Y-axis a score corresponding to a q-value lower than the 0.001 cutoff used to call lability (see SNEP lability is not associated with poor significance. A) Dot plot of all nucleosomes representing their score (Y-axis) for having a different inter-strain ratio of K14ac before and after treament (ANOVA test described in methods) as a function of their score (X-axis) for being initially a SNEP . These scores are −loglity see . B) Rece(PDF)Click here for additional data file.Figure S3versus outside a region coding for an mRNA transcript. Higher persistence is seen for nucleosomes within coding regions (Wilcoxon Mann-Whitney P<2.2×10−16) B) Within versus outside a region of conserved DNA sequence . Higher persistence is seen for nucleosomes within conserved regions (Wilcoxon Mann-Whitney P<2.2×10−16).Persistence of different classes of nucleosomes. Each panel represents the distributions of persistence values as in  of all n(PDF)Click here for additional data file.Figure S4eQTLs to aceQTLs −log. n.s.: very low, non significant scores were grouped together.Comparison of (PDF)Click here for additional data file.Figure S5BAR1 locus. Color on the upper lane reflects MNase-chip intensity logratio between RM and BY, indicating differences of nucleosome occupancy. Color on all other lanes reflects H3K14ac ChIP-chip intensity relative to BY MATalpha. In all cases, low and high values correspond to dark blue and orange, respectively, at every informative probe (many per nucleosome). The 60 segregants are separated by their mating type. Region labelled ‘1’ is depleted of nucleosome in RM-MATa as compared to BY-MATalpha (upper lane), which explains the low signal of H3K14ac ChIP in MATa strains in this region. Regions ‘2’ and ‘3’ have a more precise positioning of nucleosomes in RM than in BY (periodicity of orange bands in upper lane). MATa strains show a pronounced H3K14 acetylation in region 2 and a remarkably low H3K14 acetylation in region 3.Epigenomic profiles of nucleosome occupancy and H3K14ac at the (PDF)Click here for additional data file.Figure S6SAG1 locus. Color on the upper lane reflects MNase-chip intensity logratio between RM and BY, indicating a difference of nucleosome occupancy in the region labelled ‘1’. Color on all other lanes reflects H3K14ac ChIP-chip intensity relative to BY MATalpha. In all cases, low and high values correspond to dark blue and orange, respectively, at every informative probe (many per nucleosome). The 60 segregants are separated by their mating type. Arrow: transcription start site. A nucleosome is labelled ‘2’ and corresponds to a SNEP in genetic linkage to MAT. We see that the mating type affects both nucleosome occupancy in region ‘1’ and H3K14 acetylation of nucleosome ‘2’.Epigenomic profiles of nucleosome occupancy and H3K14ac at the (PDF)Click here for additional data file.Table S1Standard deviations of probe-level intensities among the BY and RM triplicates post recovery.(DOC)Click here for additional data file.Table S2Numbers of genetic linkages found in the genome x epigenome scan at various False Discovery Rates (FDR).(DOC)Click here for additional data file.Table S3aceQTLs found in dedicated scan at various FDRs.Numbers of cis-(DOC)Click here for additional data file.Table S4GO terms used to extract genes related to chromatin modifying activity.(DOC)Click here for additional data file.Text S1Additional detailed methods.(DOC)Click here for additional data file.


IL2RA locus, encoding the interleukin-2 receptor CD25. We report differential, allele-specific binding of the transcription factors RUNX1, LEF1, CREB, and TFAP4 to IL2RA SNPs rs12722508*A, rs12722522*C, rs41295061*A, and rs2104286*A and demonstrate the functional influence of RUNX1 at rs12722508 by reporter gene assay. Thus, PWAS may be able to contribute to our understanding of the molecular consequences of human genetic variability underpinning susceptibility to multi-factorial disease.A causative role for single nucleotide polymorphisms (SNPs) in many genetic disorders has become evident through numerous genome-wide association studies. However, identification of these common causal variants and the molecular mechanisms underlying these associations remains a major challenge. Differential transcription factor binding at a SNP resulting in altered gene expression is one possible mechanism. Here we apply PWAS , a methodology based on quantitative mass spectrometry that enables rapid screening of SNPs for differential transcription factor binding, to 12 SNPs that are highly associated with type 1 diabetes at the  Genome-wide association studies (GWAS) are a powerful approach to identifying genes contributing to risk of disease. However, individual mapped single nucleotide polymorphisms (SNPs) may not map close to a gene, and it can be difficult to distinguish marker SNPs from causal SNPs. Furthermore, the molecular mechanism responsible for disease association is usually not clear. Here we develop a method termed “proteome-wide analysis of SNPs” (PWAS) that identifies differentially binding transcription factors (TFs) and thereby helps to unravel the molecular mechanisms by which the SNPs may exert their effect on gene regulation. We use quantitative interaction proteomics to identify proteins with allele-specific binding. Applied to fine-mapped SNPs conferring risk in type 1 diabetes, PWAS revealed preferential binding of common transcription factors to certain disease-associated SNPs, suggesting they could be causal. In general, a proportion of causal SNPs are likely to function by mimicking binding motifs for transcription factors, increasing their occupancy and modulating gene expression. In addition, PWAS is streamlined and can be used as an informative follow-up approach to GWAS results. IL2RA or CD25 locus.Genome-wide association studies (GWAS) of common diseases typically result in the identification of genomic susceptibility loci, in which several single nucleotide polymorphisms (SNPs) showing strong inter-marker linkage disequilibrium (LD) are equally associated with disease predisposition. Further fine-mapping and re-sequencing studies can then uncover additional SNPs, ideally including those that are causal in the disease etiopathogenesis We improved a recently described technology for DNA affinity capture by quantitative mass spectrometry CHRM1). This locus is associated with functional differences in gene expression and differential binding of an unidentified transcription factor We benchmarked our system with a SELEX-derived TFAP2 binding site mutated at a single nucleotide position and a SNP (rs509813 C/G) in the promoter region of the muscarinic acetylcholine receptor M1 .We performed 48 SNP pull-downs with the 12 type 1 diabetes SNPs using extracts from the Jurkat T lymphocyte cell line, selected because type 1 diabetes is a T-cell mediated disease . A very HSP27 and ERαIn the eight SNPs of group 1, we found RUNX1  five-fold enriched at allele rs12722508*A . RUNX1 iCGTCA) when reverse complemented reconstituted the binding motif GTGACATGAC (TGTGGBH) for its murine homologue obtained in a recently published ChIP-seq experiment AACCCAC) when reverse complemented (TGTGGGT).Three of the identified transcription factors have known DNA consensus motifs and we therefore investigated whether these motifs were present in the DNA fragment to which they bound. For CREB1 this was indeed the case: the sequence around rs12722522*C (TGACA . InteresTGACA . HoweverP = 0.016). These results link the allele-specific binding of RUNX1 detected in our mass spectrometry screen to functional differences in transcriptional activity.RUNX1 has previously been implicated in other autoimmune diseases IL2RA type 1 diabetes locus IL2RA transcription. Extrapolating from the SILAC ratios, occupancy of the three SNPs rs12722508*A, rs12722522*C and rs41295061*A was altered between four and eight-fold for these transcription factors. Using reporter assays, we have shown that RUNX1 can mediate allele-specific expression via rs12722508. The relatively small difference measured in our reporter gene assay, and the fact that several SNPs in the haplotype also show differential binding to common TFs, offer a plausible explanation for the observed expression difference of 30% in cell surface CD25 expression Our results indicate that differential transcription factor binding to candidate causal SNPs can indicate which SNPs and which TFs might be involved in the causal mechanism(s) from gene-to-protein expression. In the case of SNP group 1 of the a priori knowledge. In conclusion, PWAS is specific, reproducible and generic and only requires synthesis of 40 mers of DNA and batch labeling of cells without the need to obtain cell lines with matching haplotypes. The throughput is currently up to five SNP pairs per day and per mass spectrometer. PWAS may contribute evidence that a given variant is causal. It can thus help to select a subset of polymorphisms from a much larger candidate set that cannot be distinguished by genetic association mapping. Positive results from PWAS directly suggest further gene-phenotype associations that can be investigated to extend the molecular chain of events at least one step further than the GWAS-mapped SNPs themselves.Large scale differential transcription factor binding at SNPs has previously been reported for NFkB and PolII using allele-specific ChIP 13C615N4 L-arginine and 40 µg/ml 13C615N2 L-lysine (Sigma Isotec or Cambridge Isotope Labs) or the corresponding non-labeled amino acids, respectively. Nuclear extracts were prepared essentially as described Hela S3 and Jurkat cells were SILAC-labeled in RPMI 1640  medium containing 10% dialyzed fetal bovine serum (Gibco) supplemented with 84 µg/ml 25 µg of corresponding pairs of oligonucleotides  were ann2, 0.5 percent NP-40, Complete Protease Inhibitor-EDTA [Roche]) for 2 hours at 4°C in a rotation wheel. After three times washing with PBB, bead fractions were pooled and bound DNA-protein complexes were eluted at RT with 200 µl PBB containing 16 mM biotin. The identical steps were automated on a TECAN EVO workstation equipped with a 4 channel LiHAN, robotic arm, cooled buffer storage reservoirs, a temperature controlled shaker and a magnetic separator. Incubations were performed in a 96 well plate (Nunc). Instead of incubation on a rotation wheel, the automated TECAN shaker was operated at 8°C and 700 rpm. Proteins in the elution fraction were precipitated with ethanol and resolubilized in 20 µl 8 M urea for MS analysis.DNA oligonucleotides were immobilized on 50 µl Dynabeads MyOne Streptavidin C1 (Invitrogen) and subsequently incubated with 200 µg of SILAC-labeled nuclear extract (light and heavy separately) in PBB buffer  for 30 min, alkylated with 3 mM iodoacetamide (Sigma) for another 30 min and subsequently digested with trypsin (Promega) overnight at room temperature. The digested protein mixture was diluted in 50 mM ammonium bicarbonate buffer pH 8/0.5% TFA and loaded onto a self-made stage tip. MS analysis was performed essentially as previously described The raw files were processed with MaxQuant www.jaspar.com).Transcription factors identified for differential SNP binding were checked for deposited recognition sequences in the JASPAR database , boiled for 5 min at 85°C and fractionated on a 4–12 percent NOVEX gradient gel using MOPS buffer (Invitrogen). Proteins were transferred to a Protran 85 membrane (Whatman) in a blotting chamber (Biorad) at 300 mA for 1 h. The membrane was blocked with PBST (0.1%)+4 percent low fat milk (Roth) for 15 min prior to incubation with the primary antibody for 1 h at room temperature. The following antibodies were diluted in PBST (0.1%) with 4 percent low fat milk: SP1 [1∶1000], TFAP2 [1∶2000], RUNX1 [1∶1000] and LEF1 [1∶1000] . Membrane was washed with PBST (0.1%) three times prior to incubation with either HRP-anti-mouse or HRP-anti-rabbit antibody (both Amersham) for 1 h at room temperature. For detection ECL Western blotting detection reagent (Amersham) was used according to manufacturer's instruction. Chemiluminescence screens  were used to visualize the band patterns.GGATAACTGGTCCGCAGTGGT, rev: CCCATTCATCCCATGATTCAA); TFAP4 ; RUNX1 ; CREB1 ; CBFB .Endoribonuclease-prepared short interfering RNAs (esiRNAs) were produced as previously described GAGAAAGCTTCAGGAACATCCAAACTGAGCA, Hsp68_rev: GAGAAAGCTTCGCTTGTCTCTGGATGGAAC) from genomic DNA prepared from C2C12 cells. The promoter was cloned into pGL3-basic (Promega) in front of the firefly luciferase gene at the HindIII site. A gateway cassette was inserted 5′ of the promoter to facilitate insertion of different DNA sequences, generating the pGL3/GW/mHsp68prom vector. A triple repeat of the sequence surrounding rs12722508 (AACCCACCCAC[A/T]GAAACTATCAGAG) was cloned into pCR8 and transferred into pGL3/GW/mHsp69prom using LR recombination.The heat shock promoter was amplified  in complete medium in a 24 well plate. After 16 hours, 4 ng Rhenilla luciferase vector phRL-TK (Promega) were co-transfected with 200 ng firefly reporter (pGL3/GW3/mHsp69prom) containing either SNP variant with Optimem medium (Gibco). Medium was exchanged against complete medium 4 hours past transfection. Cells were harvest the next day using passive lysis buffer (Promega). Independent biological triplicates were measured on the GloMax luminometer (Promega) using the Dual Luciferase Assay kit (Promega) according to the manufacturer's protocol. For representation, the mean and the standard deviation were calculated. Transfection efficiency was monitored by parallel transfection of RLuc esiRNA targeting rhenilla luciferase.GCAGACAGCCGAGTACATCTT, rev: CCTATGCCTTCGTCCTTGTCC), RUNX1 , CBFB , CREB , GAPDH . Three independent replicates using the IQ SybrGreen supermix (Biorad) were measured on a CFX96 qRT-PCR machine (Biorad). For assessment of knock-down the tΔΔC method was used.Cells form one well (24 well plate) transfected with esiRNA and reporter assay constructs were trypsinized, washed in PBS and RNA extracted using a spin filter kit (UBS). Around 1 µg of pure RNA were reverse-transcribed with polyT primers using the Fast cDNA kit (Fermentas). The following primers were used for the amplification: TFAP4 , rs41295049  and rs41295065 , rs41295063 and rs7909519; Group 2: rs11597367, rs11594656 and rs35285258 ; Group 3: rs2104286. Two-dimensional interaction plots showing enrichment of transcription factors with one variant of the SNP by sorting them in the lower right or upper left quadrant, having inversed high ratios in both pull-downs. Contaminants can be visualized in the lower left quadrant having a low ratio in both experiments.(PDF)Click here for additional data file.Table S1Primers used in 5′-3′ direction.(PDF)Click here for additional data file.Table S2IL2RA SNPs.Protein identifications from PWAS screen for (XLSX)Click here for additional data file.


The mammalian sirtuin family comprises 7 members (SIRT1-7) that act in different cellular compartments to regulate metabolism and aging. The rice genome contains only two Sir2-related genes: OsSRT1 (or SRT701) and OsSRT2 (orSRT702). OsSRT1 is closely related to the mammalian SIRT6, while OsSRT2 is homologous to SIRT4. Previous work has shown that OsSRT1 is required for the safeguard against genome instability and cell damage in rice plant. In this work we investigated the role of OsSRT1 on genome-wide acetylation of histone H3 lysine 9 (H3K9ac) and studied the genome-wide binding targets of OsSRT1. The study reveals that OsSRT1 binds to loci with relatively low levels of H3K9ac and directly regulates H3K9ac and expression of many genes that are related to stress and metabolism, indicating that OsSRT1 is an important site-specific histone deacetylase for gene regulation in rice. In addition, OsSRT1 is found to also target to several families of transposable elements, suggesting that OsSRT1 is directly involved in transposable element repression.Histone acetylation/deacetylation is an important chromatin modification for epigenetic regulation of gene expression. Silent information regulation2 (Sir2)-related sirtuins are nicotinamide-adenine dinucleotide (NAD Homologs of the SIR2 protein are called sirtuins and have been implicated in a variety of processes including transcriptional repression, metabolism, apoptosis, and aging in animal cells Histone lysine acetylation is an important epigenetic modification for genome function and gene activity. Dynamic modulation of histone acetylation in plants has been shown to be involved in gene expression programs of plant development and responses to environmental conditions OsSRT1 by RNAi produces a lesion-mimic phenotype and induces H3K9 acetylation (H3K9ac) and expression of hypersensitive response-related genes in rice plants Plant genomes contain only two sirtuin-like genes. One is closely related to SIRT6, the other to SIRT4 OsSRT1 down-regulation did not drastically alter the genome-wide H3K9ac landscape, but led to increases of H3K9ac over a subset of genes belonging to specific functional categories and transposable elements. OsSRT1 was found to be associated with 1824 genes that showed relatively low levels of H3K9ac. In addition, OsSRT1 binding was significantly enriched in the gene bodies compared to the upstream and the down regions. Gene ontology analysis revealed that OsSRT1 preferentially targets to genes involved in stress-responses and metabolisms and to several families of transposable elements in the rice genome, indicating that OsSRT1 is a site-specific HDAC involved in specific gene regulation and transposon repression.The homeostasis of histone H3K9 acetylation regulated by OsSRT1 in controlling genome-wide gene expression remained unclear. It was not known whether OsSRT1 directly targeted to specific genes to undergo histone deacetylation. To study the chromatin function and to identify direct binding targets of the OsSRT1, we first compared the genome-wide H3K9 acetylation profiles between wild type and OsSRT1 down-regulation plants, and then investigated the genomic binding sites of OsSRT1 by chromatin immunoprecipitation assays. Our data indicated that H3K9ac was mostly associated with active genes in rice. Oryza sativa) cultivar Minghui 63 (MH63) was used in this study. The OsSRT1 RNAi line was previously reported by Huang et al. (2007) Rice (E. coli-produced OsSRT1 protein. The anti-serum was affinity purified with protein-A agarose beads purchased from Millipore (16–157) and tested by Western blots to detect the OsSRT1 protein in rice tissues (t) of the ChIP sample with that of the input with: 2(Ct of input-Ct of sample ChIP)ChIP experiments were performed as described  tissues . The prePrecipitated DNA from ChIP assays was PCR amplified with Illumina primers and library fragments of 100–300 bp (insert plus adaptor and PCR primer sequences) were isolated from agarose gels. The purified DNA was captured on an Illumina flow cell for cluster generation. Libraries were sequenced with Illumina Genome Analysis.p-value of 1.00e-05) and largellocal = 5000 were set up to call peaks representing enriched H3K9Ac or OsSRT1 binding. Peaks in the gene body and the upstream and downstream 2 Kb regions were identified as histone H3K9ac or OsSRT1 binding. The transcription factors in the genome were classified according to PlantTFDB (http://planttfdb.cbi.edu.cn/index.php?sp=Osj).Sequencing reads from all libraries were mapped to the reference genome (MSU6.0) using MAQ software with default parameters http://rice.plantbiology.msu.edu/) was used to assign genes to a hierarchical biological process following the criteria of the Gene Ontology Consortium databases , then the Web Gene Ontology Annotation Plotting tool WEGO was used to plot GO categories (http://wego.genomics.org.cn) p-value of a particular pathway was calculated with Pearson’s chi-squared test, then corrected by False discovery rate (FDR), with a FDR cutoff of 0.05 as the significance threshold OsSRT1 RNAi microarray is GSE71976.Gene ontology classification provided in TIGR Rice Genome Annotation Project (http://www.girinst.org/repbase/) to analyze the MSU6.0 version of the rice genomic sequence in high sensitivity. A transposon is considered to have H3K9 acetylation if located inside a peak. We used 2-fold cut-off in analyzing H3K9 acetylation. For TEs numbers less than 100, Fisher’s exact tests were used to test the enrichment. Hyper geometric distribution tests were used for TE numbers greater than 100. We set the p-value cut-off as 0.01.To study the distribution of transposons in the genome, we used Repeatmaske  to analyze the binding motif of OsSRT1 ChIP-seq peak sequences. MAST software was used to analyze the distribution of the motifs in the MSU6.0 rice genome. Fisher exact test was used in testing enrichment significance.OsSRT1 down-regulation on histone acetylation in rice, a high-resolution map of the genome-wide distribution of H3K9ac in 11-day old wild type and OsSRT1 RNAi seedlings was determined by chromatin immunoprecipitation (ChIP) assays followed by high-throughput Illumina/Solexa sequencing (Oryza sativa L. ssp. Japonica cv. Nipponbare) using MAQ software OsSRT1 RNAi plants, of which 93% were overlapped with those from the wild type plants  were confirmed by ChIP-PCR  in the gene bodies compared to the upstream or down regions, with a peak toward the 3′ end of the gene bodies  of transcription factor genes were found to show OsSRT1-binding and increased H3K9ac in OsSRT1 RNAi plants , but not found over the other retroelement families   , Table 3GATGGGCCGA) that was found within the LTR of the Gypsy retrotransposons. In the rice genome we found that 1209 genes  contained the inverted repeats. The motif was significantly enriched among OsSRT1-binding genes , suggesting that OsSRT1 may target to this DNA sequence.To find potential DNA motifs associated with OsSRT1, we analyzed OsSRT1-binding peaks by using MEME software, a sequence of 31 bp was found in 28 peaks. This sequence contained an inverted repeat motif with a highly conserved half motif  responses for OsSRT1-binding is consistent with the lesion mimic phenotypes observed in OsSRT1 down-regulation led to increased H3K9ac and expression of many transposable elements (this work and ref 6). Finally, a number of OsSRT1 ChIP-seq peaks overlapped with an inverted repeat DNA sequence motif found in the LTR of the Gypsy subfamily, raising the hypothesis that the motif may represent a DNA target sequence of OsSRT1.Yeast SIR2 and mammalian SIRT6 proteins are shown to be involved in telomere stability or silencing Figure S1E. coli –produced OsSRT1-GST fusion was used as positive controls. Detection of histone H3 by anti H3 was used the loading control.Western blot analysis of SRT1 in wild type (MH63) and OsSRT1 RNAi plants. Affinity purified anti-OsSRT1 was used in Western blots to detect OsSRT1 levels. (PPTX)Click here for additional data file.Figure S2http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431496/.H3K9ac and OsSRT1 ChIP-seq mapped reads in wild type (MH63) and OsSRT1 RNAi plants. A. H3K9ac and OsSRT1 ChIP-seq mapped reads in wild type (MH63) and OsSRT1 RNAi plants. B. Normalized strand correlation (NSC) and relative strand correlation (RSC) values of the ChIP-seq reads, calculated according to (PPTX)Click here for additional data file.Figure S3Gene expression level is positively correlated to H3K9ac. Rice genes were divided into 3 tiers  according to microarray signals and compared to average H3K9ac sequence tag density.(PPTX)Click here for additional data file.Figure S4OsSRT1 RNAi plants and the blue columns represent the total genes.Gene ontology analysis of genes with increased H3K9ac (FDR<0.05). The red columns represent (PPTX)Click here for additional data file.Figure S5Gene ontology analysis of OsSRT1-binding genes (FDR<0.05). A. OsSRT1-binding genes (red) compared to the total genomic genes (blue). B. Genes with both OsSRT1-binding and expression altered in RNAis plants.(PPTX)Click here for additional data file.Figure S6in OsSRT1 RNAi plants and OsSRT1-binding.Two genomic regions that show increased H3K9ac (PPTX)Click here for additional data file.Table S1OsSRT1 RNAi plants. The 37 genes on which OsSRT1-binding peaks overlapped with that of H3K9ac increases are marked in yellow.List of genes that showed OsSRT1 binding and H3K9ac increase in (PDF)Click here for additional data file.


In a directed search we identified a potential polycomb responsive element with 25 repeats of YY1 binding motifthatwe designate PRE-PIK3C2B as it occurs in the first intron of human PIK3C2B gene. It down regulates reporter gene expression in HEK cells and the repression is dependent on polycomb group of proteins (PcG). We demonstrate that PRE-PIK3C2B interacts directly with YY1 in vitro and recruits PRC2 complex in vivo. The localization of PcG proteins including YY1 to PRE-PIK3C2B in HEK cells is decreased on knock-down of either YY1 or SUZ12. Endogenous PRE-PIK3C2B shows bivalent marking having H3K27me3 and H3K4me3 for repressed and active state respectively. In transgenic Drosophila, PRE-PIK3C2B down regulates mini-white expression, exhibits variegation and pairing sensitive silencing (PSS), which has not been previously demonstrated for mammalian PRE. Taken together, our results strongly suggest that PRE-PIK3C2B functions as a site of interaction for polycomb proteins.Epigenetic cellular memory mechanisms that involve polycomb and trithorax group of proteins are well conserved across metazoans. The  Drosophila, function through their interaction with chromatin as multi-protein complexes Drosophila, PcG/TrxG proteins regulate their target genes by binding to specific DNA elements called Polycomb/trithorax response elements (PRE/TREs) which interact with both activating and repressive complexes and PRE/TREs recruit PcG/TrxG complexes at multiple loci as seen on polytene chromosomes During development, the transcription status of the genes is maintained from embryonic to adult stages through mitotic or cellular memory mechanisms, which leads to the establishment of different cell lineages. The polycomb (PcG) and trithorax (TrxG) group of proteins, discovered in the context of regulation of homeotic genes in Drosophila, functions in this recruitment as it is known to bind DNA specifically and is involved in the recruitment of PcG complex Pleiohomeotic (PHO), a PcG protein from cis-regulatory elements MafB gene due to inversion of a large sequence led to the identification of PRE-kr in mice, while the selective enrichment of H3K27me3 and PcG proteins and its correlation with MNAse sensitivity led to the identification of HOXD11-12 PRE in human embryonic cells Drosophila miniwhite reporter as well as in transgenic mice Though mammalian homologues of several PcG and TrxG proteins are known, PRE/TRE-like function is attributed only to a few in silico analysis to retrieve genic regions with high density of YY1 consensus motif in the human genome. We identified a 1 kb sequence with 25 mer repeating unit containing the YY1 binding site repeated 25 times at the firstintron of PIK3C2B gene and studied its regulatory function on reporter gene expression. The repression of the reporter as well as the endogenous PIK3C2B is dependent on PRC proteins. Further we validate this sequence for its ability to function as PRE/TRE in transgenic Drosophila and detect genetic interaction with PcG and TrxG mutants. Based on these results we discuss the implied PRE/TRE like function of PRE-PIK3C2B.Our goal was to search for potential PRE/TRE like sequences in the human genome, therefore we carried out pcDNA3.1 GFP was obtained from Sanjeev Khosla, CDFD, Hyderabad, India. pHIS-YY1 Antibodies against YY1 (ab43058), SUZ12 (ab12073), EED (ab4469), EZH2 (ab3748), H3K4me3(ab8580) and H3K27me3 (ab6002) were purchased from Abcam. Antibody against EZH2 was purchased from Active Motif (Cat. No. 39875). Anti-Brahma antibodies was a kind gift from Madan Mohan Chaturvedi, Delhi University. Antibodies against Polycomb, trithorax and Polyhomeotic P1 (5′TTGACAAATGCAATAACAAGGC-3′), P2 (5-TCCCTTGTGTCCCGTTGTAATC-3′′), P3 (5-GGTATTCTCACATGTCAAAA-3′′) andP4 (5-GGATCCTAGTGCAAGCTG-3′′), were used for PCRs as required. P1-P4 primers were used for amplification of PRE-PIK3C2B from human genomic DNA. Oligo25-F (5-AGTGAAGCCATCAT GTGAGAATACC-3′′) and Oligo25-R (5-GGTATTCTCACATGATGGCTTCACT-3′′); OligoΔYY1-F (5-AGTGAAGTGAGAATACC-3′′) and OligoΔYY1-R (5-GGTATTC TCACTTCACT-3′′) were used in binding studies by EMSA. WNT1-F (5-CCAGCGCCGCAACTATAAGAG-3′′) and WNT1-R (5-CGCAGTCTGGCTTTAA CAACCC-3′′); RNAP-F (5-GGTTTACCCACGACTCTGGCTC-3′′)and RNAP-R (5-GCTTCTGAGCAGCGAACTCG-3′′); GDAP1-F (5-GCTTTCCAGTCGCAGACC-3′′) and GDAP1-R (5-GCCTCTCAGCCATCTTGG-3′′); GAPDH-F (5-TACTAGCGGTTT TACGGGCG-3′′) and GAPDH-R (5-TCGAACAGGAGGAGCAGAGAGCGA-3′′)were used in chromatin-immunoprecipitation(ChIP) assays.Primers Genic sequences along with 15 kb each of 5′and 3′ flanking regions of genes with altered expression in ALL patients UPGFP and pPRE-PIK3C2B/DNGFP respectively. To generate plasmid pc(25mer)11UP/DN, PRE-PIK3C2B was used as the template and the product was amplified using Oligo25-F and Oligo25-R as primers mapping within the repeat region and the pool of amplicons were cloned in pTZR57R/T and sequenced. Insert from the clone with the tandem ligation of the Oligo25 mer (11 times) was cloned in the Nru1 and Sma1 site of pcDNA-GFP vector to generate pc(25 mer)11UP and pc(25 mer)11DN respectively. To generate plasmid pc(ΔYY1)11UP/DN, OligoΔYY1-F and OligoΔYY1-R were annealed by heating at 95°C for 5 minutes and kept at room temperature to cool slowly. Annealed OligoΔYY1 was self-ligated and the pool of self ligated OligoΔYY1 was used as template for PCR using OligoΔYY1-F and OligoΔYY1-R as primers. The amplicons were cloned in pTZR57R/T and sequenced. Insert from the clone with the tandem ligation of the OligoΔYY1 (11 times) was cloned in the Nru1 and Sma1 site of pcDNA-GFP vector to generate pc(ΔYY1)11UP and pc(ΔYY1)11DN respectively. Transfection of HEK293 cells with the vectors generated and also the siRNA constructs were carried out using Transpass D2 (New England Biolabs) as per the manufacturer's protocol. The cells were analysed for GFP reporter expression after 48 hours by using Flow cytometry .1 kb of the PRE-PIK3C2B region was PCR amplified with P1-P4 primers from human genomic DNA and cloned into pcDNA-GFP vector in the Nru1 and Sma1 site to generate pPRE-PIK3C2B/5′-CCCCACTCTTCAACTTCAGG-3′) and PIKb1R (5′TCTGG CTGGTGGAAATTAGG-3′). Transfection of pSUPER-YY1 and pRetroSuper-SUZ12 was carried out using Lipofectamine2000  as per the manufacturer's protocol, cDNA was synthesized from isolated RNA  from cells after 48 hours after transfection, GAPDH was used as internal control.Expression of endogenous PIK3C2B in HEK293 cells was analyzed by qPCR in absence and presence of siRNA YY1 and siRNA SUZ12 using the primers PIKb1F (32PATP-labelled double-stranded Oligo25 mer (2 ng). The γ32PATP end-labeling reaction was performed using Polynucleotide Kinase at 37°C for 60 minutes. After adding the labeled probe, the mixture was incubated at room temperature for 20 minutes. Electrophoresis was carried out in 5% acrylamide-bisacrylamide (40∶1) gel containing 4% glycerol in 0.5× TBE. For competition experiments, the unlabeled DNA probes were added at the same time as the labeled probes. To detect the binding of YY1, labeled double-stranded Oligo25 mer and purified YY1 protein were incubated with anti-YY1 antibody and binding was detected using Phosphor imager .Gel mobility-shift assay and preparation of nuclear extract from HEK293 cells were carried as described by Mishra et al., Drosophila embryos and ChIP was performed as described previously Cross-linked chromatin was prepared from transgenic 1118 Canton-S strain The PRE-PIK3C2B fragment was PCR amplified from human genomic DNA with primers P1 and P4 cloned into pGEM-T Easy Vector System (Promega) and sequenced. The fragment re-cloned in pLML vector at the EcoR1 and HindIII restriction site is flanked by loxP sites. The insert with the loxP sites from pLML vector was cloned at XhoI site upstream of miniwhite promoter in pCasPeR vector with miniwhite reporter gene. The construct was then injected into embryos from w1118; PI-17/+; +/+, (ii) w1118; PI-17/+; Phob/+ (iii) w1118; ΔPI-17/+;+/+(iv) w1118; ΔPI-17/+; Phob/+. Δ indicates the flip out of PRE-PIK3C2B using Cre recombinase. RNA was extracted from the adult flies, cDNA preparation and qPCR protocols were as described for other genes in the earlier section. Exon spanning primers (forward primer 5′- ATGGCGGCAGCTGGTCA-3′ and reverse primer 5′– GCGGCGATCGAAAGGCAA- 3′) were used for qPCR.To analyze the effect of Pleohomeotic on miniwhite expression, quantitative PCR for miniwhite expression was carried out. Age matched adult males of the following genotypes were compared: (i) wDrosophila trithorax gene To detect putative PRE/TRE in the human genome in silico, we selected genes that show altered expression in acute lymphoblastic leukemia (ALL) with t(4∶11) translocation, because the translocation partner MLL on chromosome 11 is a homeotic regulator that shares homology with PIK3C2B is an important signaling gene, we selected it for experimental validation. We refer to this sequence as PRE-PIK3C2B, which occurs in the first intron of the gene and is a 1 kb sequence containing 25 repeats of YY1 binding consensus sequence  signal  signal of the reporter; pPRE-PIK3C2B/EK cells . After n) signal .11clones with 11 repeats of 25 mer containing one GCCATCAT motif for YY1 binding in each repeating unit and transfected them into HEK cells. We observed repression of GFP expression by 54% and 56% when cloned upstream and downstream of reporter reporter . Furtherreporter .We detected the direct interaction of purified recombinant YY1 protein with end labeled Oligo25 mer. The specificity of binding is shown by the lack of competition by oligonucleotide with deletion of YY1 binding site (OligoΔYY1), while unlabeled Oligo25 mer could compete out the binding . FurtherThe PRC complexes localize at PRE, and the methyl transferase activity of EZH2 in PRC2 complex brings about H3K27me3 modification. Therefore we analysed the methylation status and also the localization of PRC2 members at PRE-PIK3C2B in HEK293T cells . FollowiOn knock-down of YY1 and SUZ12 using siRNA constructs, H3K27me3 is lost and localization YY1and SUZ12 is significantly reduced at PRE-PIK3C2B . We confWe used GAPDH and GADP1 respectively as negative and positive controls for YY1  [42]. PRPIK3C2B in HEK293T cells and also the reporter gene in separate experiments (UP-GFP and pPRE-PIK3C2B/DN-GFP) were co-transfected with siRNA constructs and a reversal of repression was observed  translocation and detected a high density of YY1 binding motif in the first intron of PIK3C2B. The other recently identified, PRE-kr, that regulates expression of mouse MafB/Kreisler gene, D11.12, the region between HoxD11 and HOXD12 identified in human embryonic cells and PRE in FSHD also contain YY1 binding motif Drosophila intronic PREs are predicted and validated in caudal, aPKC  and EYA DrosophilaDrosophila and position effect of silencers in yeast is known to be orientation independent affecting different promoters We aimed at identifying putative PREs in the human genome based on YY1 or SUZ12. PRE-PIK3C2B is marked by the H3K4me3, an active mark on histones which increases on knock-down of PRC2 members. Therefore PRE-PIK3C2B region carries bivalent marking, having both H3K27me3 and H3K4me3, suggesting that the gene is poised to switch between repressed and activated state Drosophila are known to be the interaction sites for both Polycomb and trithorax complexes and have the potential to switch between repressed and activated state PRE-PIK3C2B is associated with PRC2 complex in HEK293T cells. Following this interaction, EZH2 subunit of PRC2 complex that has intrinsic histone methyltransferase (HMTase) activity confers H3K27me3 mark in vivo interactions of YY1 with other proteins leading to inaccessibility for antibody interaction.The direct interaction of cloned YY1 protein and the proteins in the nuclear extract from HEK cells also shows that the repressive effect on reporter gene is mediated by YY1. However, in the gel retardation assays, the super-shift with anti-YY1 antibody was observed only when we used purified YY1, but not the nuclear extract. It could be because of the PIK3C2B could be the target of repression by PRE-PIK3C2B, however, long range interactions can operate on additional targets, which are being investigated. The reversal of repression is significant when both YY1 and SUZ12 are knocked down, but not when YY1 alone is down regulated. This is similar to the enhancement for example of polycomb phenotype commonly seen in only double heterozygotes of two interacting partners of the PRC complex in DrosophilaPIK3C2B expression and the recruitment of activators is also necessary. PIK3C2B being a signaling protein responds to several signals such as epidermal growth factor, platelet derived growth factors Our results indicate that Drosophila and shows the characteristic pairing dependent silencing/pairing sensitive silencing in flies homozygous for PRE-PIK3C2B in PI-17 line. Even in Drosophila, PSS is not exhibited by all PRE/TREs but only certain PREs are known for PSS We have demonstrated that PRE-PIK3C2B functions as a PRE in Drosophila PREs are typically a few hundred base pairs and deletions reducing their length results in reduction in their repressive function 1Su(var)2-5, 6 Su(var)2-101Su(var)3-9 (data not shown). We rule out the repressive effect due to telomere position effect (TPE) as the transgene is integrated in the 5′UTR of the gene Limpet, about 6.7 Mb from the telomere and not in the telomere associated satellite-like sequences(TAS). DNaseI hypersensitive sites map in this region indicating that it is euchromatic in nature.Though we tested interactions with many genes of the PRC complex, interaction is detected only in certain cases. Similar absence of effect of pho mutations on mini-white repression in iab-7 transgenics was reported earlier DrosophilaPRE-PIK3C2B shows interaction with TrxG genes zeste and brm, identified as transregulators of homeotic genes in In summary, we have identified a polycomb complex interacting site, PRE-PIK3C2B in the human genome through a directed search and demonstrate its function in transcription repression mediated by PRC complex. To the best of our knowledge the pairing sensitive silencing in transgenic flies is unique to PRE-PIK3C2B among the mammalian PREs reported so far. The bivalent marking on PRE-PIK3C2B and the results of the genetic interaction studies in transgenic flies, strongly suggests that PRE-PIK3C2B we describe here could indeed be a potential PRE/TRE in the human genome.Figure S1GCCATCATGTGAGAATACCAGTGAA). Primers location is highlighted in yellow colour. YY1 Binding site is highlighted in red.Complete sequence of PRE-PIK3C2B with 25 repeats of 25 mer including the YY1 binding motif ((EPS)Click here for additional data file.Figure S2Interaction of proteins from HEK nuclear extract: Probe-end labeled (Oligo25 mer), Protein- HEK293 Nuclear extract, Cold (specific)- unlabeled (Oligo25 mer) was used at 100 (a),250(b) and 500 (c) fold excess. Cold (Non- specific)- Random sequence 25 mer Oligo used at 500(d) and 750 (e) fold excess.(TIF)Click here for additional data file.Figure S3QPCR for negative and positive controls used GADP as positive and GAPDH as negative control for ChIP with anti-YY1 and anti-SUZ12. The enrichment of PRE-PIK3C2B was significantly higher compared to the negative control in both the cases (p<0.0001 and 0.0002 for YY1 and SUZ12 respectively).(EPS)Click here for additional data file.Figure S4QPCR for WNT as positive and RNAP as negative control for ChIP with anti-EZH2 and anti-EED. The enrichment of PRE-PIK3C2B was significantly higher compared to the negative control in both the cases (p<0.0001 and 0.00001 for EZH2 and EED respectively).(EPS)Click here for additional data file.Figure S5Effect siRNA on YY1 expression in HEK293. A- qPCR for transcript level. Significant knock down (∼90%) is observed. B- Under similar conditions, protein level was observed.(TIF)Click here for additional data file.Figure S6Line diagram showing features of the reporter gene construct pCaSpeR. The construct contains the mini-white reporter gene under its promoter. PRE-PIK3C2B(shown as shaded arrow) was inserted upstream of the reporter gene.5′P and 3′P refer to P element present 5′and 3′to the reporter gene. The small clear arrows denote the loxP sites.(TIF)Click here for additional data file.Figure S7Interaction of PRE-PIK3C2B with PcG/TrxG proteins. ChIP with antibodies indicated. Input is 20% (A), 10% (B) of sonicated chromatin.(TIF)Click here for additional data file.Figure S8A- Image from UCSC browser, showing histone mark in the PRE-PIK3C2B region, in NT2-D1 . H3K27me3 and H3K4me3 are detected in this region, showing bivalent marking (arrows). ** p<0.005. B- The histone modification in the region of PRE-PIK3C2B (202706547-202707642) in K562 cell line. Data taken from MPromDb (TIF)Click here for additional data file.Table S1List of top ten genes having highest density of YY1 binding site. Total refers to the total number of YY1 motifs, in the genic region, along with 15 kb upstream and downstream sequences.(DOC)Click here for additional data file.Table S2Details of PRE-PIK3C2B transgenic lines(DOC)Click here for additional data file.Table S3*Represents mutant backgrounds that showed interaction PRE-PIK3C2B transgenics.List of Polycomb and trithorax group mutations used in the study. (DOC)Click here for additional data file.Table S4*Represents mutant backgrounds that showed interaction CE-PIK2B transgenics.Polycomb and trithorax group of trans–heterozygote mutations used in the study. (DOC)Click here for additional data file.


We found that ICP22 inhibits transcription of the HSV-1 α, β and γ gene promoters. The viral tegument protein VP16, which plays vital roles in initiation of viral gene expression and viral proliferation, can overcome the inhibitory effect of ICP22 on α-gene transcription. Further immunoprecipitation studies indicated that both ICP22 and VP16 bind to positive transcription elongation factor b (P-TEFb) and form a complex with it in vivo. We extended this to show that P-TEFb regulates transcription of the viral α-gene promoters and affects transcriptional regulation of ICP22 and VP16 on the α-genes. Additionally, ChIP assays demonstrated that ICP22 blocks the recruitment of P-TEFb to the viral promoters, while VP16 reverses this blocking effect by recruiting P-TEFb to the viral α-gene promoters through recognition of the TAATGARAT motif. Taken together, our results suggest that ICP22 interacts with and blocks the recruitment of P-TEFb to viral promoter regions, which inhibits transcription of the viral gene promoters. The transactivator VP16 binds to and induces the recruitment of P-TEFb to viral α-gene promoters, which counteracts the transcriptional repression of ICP22 on α-genes by recruiting p-TEFb to the promoter region.ICP22 is a multifunctional herpes simplex virus 1 (HSV-1) immediate early protein that functions as a general repressor of a subset of cellular and viral promoters in transient expression systems. Although the exact mechanism of repression remains unclear, this protein induces a decrease in RNA polymerase II Serine 2 (RNAPII Ser-2) phosphorylation, which is critical for transcription elongation. To characterize the mechanism of transcriptional repression by ICP22, we established an  Herpes simplex virus 1 (HSV-1) is a member of the herpes virus family and has a 152 kb double-stranded DNA genome that encodes for more than 80 proteins and possesses complex transcriptional regulation mechanisms in vivo transient expression system in vivo transient expression system A) is bound to elements within the promoter region. After the phosphorylation of Ser-5, the transcription complex enters into the early extending mode. Soon after, transcription of the mRNA molecule resulting from the early extending mode is terminated by two negative elongation factors, DSIF and NELF, which associate with the transcription complex. The next step is capping of the transcript by the capping enzyme. After the capping process, P-TEFb functions as a key factor to ensure that the transcription complex resumes normal elongation. The phosphorylation of Ser-2 of the CTD converts RNAPII into the elongation active hyperphosphorylated state (RNAPIIo). Simultaneously, P-TEFb also phosphorylates the SPT5 and RD subunits of the two negative elongation factors DSIF and NELF, respectively. The phosphorylation of these two subunits is a key step in the dissociation of these two negative elongation factors from the transcription complex. Thus, RNAPII drives the transcription complex into the normal elongation state, which is a very important event during transcription et al. suggest that during HSV-1 infection ICP22 triggers a decrease in RNAPII Ser-2 phosphorylation and induces an intermediate status (RNAPIII), which causes abnormalities in cellular-related gene transcription and optimal expression of viral genes VP16, in association with the host cellular proteins Oct-1 and HCF-1, recognizes the core motif TAATGARAT in α-gene promoter sequences, thus initiating transcription of the α-genes in vivo transient expression reporter system and HSV1-infected cells to add to our previous studies that indicated a transcriptional co-regulation effect of ICP22 and VP16 on viral α-genes. We observed that ICP22 represses transcription of the viral α-, β- and γ-gene promoters by interacting with and blocking the recruitment of P-TEFb to promoter regions. In contrast, VP16 overcomes the transcriptional inhibition of ICP22 by binding to and recruiting P-TEFb to promoter regions containing the TAATGARAT motif such as α-genes. Thus, based on this model, the current paper suggested a possible manner of recruitment of P-TEFb to the promoter of HSV1 α-gene in viral infection, in which ICP22 and VP16 may regulate P-TEFb through binding the different components of it.We used an et al. have reported that ICP22 can inhibit the transcription of several genes in vivo transient expression system using the dual luciferase reporter in which pRL-CMV, the internal transfection control reporter plasmid, and pcDNA3, the eukaryotic expression vector used to express ICP22 and other proteins, are both driven by the CMV IE promoter. The activity of this promoter in the presence of ICP22 had been confirmed in our previous study Although the immediate early proteins are involved during the regulation of viral gene transcription in the HSV-1 infection process, the function of ICP22 is not yet clear. Studies have shown that ICP22 is involved in viral gene transcriptional regulation through multiple mechanisms and that this protein can be observed in the transcriptional complex of HSV-1 infected cells in vivo and in vitro binding assays. Despite not being detected by yeast trap experiment and in vitro binding assay .P-TEFb need to be recruited to the promoter region of transcription initiation to enhance transcription elongation through the phosphorylation of RNAPII CTD Ser-2, while ICP22 can induce abnormal RNAPII CTD Ser-2 phosphorylation by interacting with P-TEFb Because VP16 can release the α-gene transcriptional inhibition by ICP22 and interact with P-TEFb, we performed ChIP assays to investigate the role of VP16 together with ICP22 in the recruitment of P-TEFb to the viral α-, β- and γ-gene promoters in the co-transfected transient expression system and in HSV-1 infected cells. The results show both in the transient expression system and in infected cells, that VP16 increases the recruitment of P-TEFb to the viral α-gene promoter but not the β- and γ-gene promoters . This fiThe function of ICP22, an immediate early protein encoded by HSV-1, has been investigated in many studies of viral proliferation, these studies concluded that the protein possesses multiple functions and these functions optimize the expression of HSV-1 late genes, such as γ2 The transcription factor P-TEFb performs key functions in the RNAPII complex, it controls the production of mRNA by regulating RNAPII transcriptional elongation via phosphorylation of Ser-2 of the CTD and of the negative elongation factors DSIF and NELF in vivoin vivo transient expression system and in HSV1-infected cells. Because of the function of P-TEFb in the RNAPII complex, the interactions of P-TEFb with ICP22 and VP16 suggest that transcriptional regulation by ICP22 and VP16 is mediated by P-TEFb. Conversely, the interactions between ICP22 and VP16 with P-TEFb imply that the function of P-TEFb may be interfered with. Based on our luciferase reporter system and ChIP experiments, the observation that ICP22 inhibits transcription of the viral α-, β- and γ-genes is likely due to the interaction between ICP22 and P-TEFb that blocks the recruitment and function of P-TEFb at the viral promoter regions. Similarly, the interaction between VP16 and P-TEFb suggests that the overcoming of ICP22-mediated viral α-gene transcriptional inhibition is likely mediated by the recruitment of P-TEFb to the promoter regions via recognition of the TAATGARAT element of α-genes. In this transcriptional regulation model, the interaction with ICP22 may block the regular cellular recruitment pathways of P-TEFb to viral and cellular gene promoters. In contrast, VP16 interacts with P-TEFb and recruits it to the viral α-gene promoters that contain the TAATGARAT motif and overcomes transcriptional inhibition by ICP22 and promotes transcription of IE genes. Thus, the regulation of P-TEFb recruitment by HSV-1 may inhibit transcription of cellular genes through ICP22 and hijack the host transcription complex for viral gene expression through VP16.Our findings confirm the observed interactions between ICP22 and Cdk9, VP16 and CyclinT1 in vivo transient expression reporter system and then confirmed in virus-infected cells. All results obtained here suggest ICP22 and VP16 in the transcriptional regulation of viral α-gene promoters and reveal the regulation of P-TEFb function by ICP22 and VP16 during viral infection. These data help to create a model that could be used to investigate additional mechanisms of HSV-1 infections.Our experiment was initially performed in an 2Chinese hamster ovary cells (CHO-k1) acquired from Kunming Cell Bank  were grown in complete Ham's F12 medium (GIBCO) containing 10% bovine serum at 37°C in 5% CO2. Hep-2 and Vero cells  were grown in Dulbecco's modified Eagle's medium (GIBCO) supplemented with 10% bovine serum at 37°C in 5% COThe eukaryotic expression plasmids pcDNA-ICP22, pcDNA-VP16, pGAD-ICP22 and pGBK-VP16 that contained the entire viral ICP22 or VP16 gene sequence, were generated by our laboratory as previously described A rabbit anti-cyclinT1 antibody (sc-10750), a rabbit anti-Cdk9 antibody (sc-8338), a mouse anti-Oct-1 antibody (sc-8024), and control pre-immune rabbit or mouse IgGs were purchased from Santa Cruz Biotechnology. The rabbit anti-VP16 polyclonal antibody (V4388) was purchased from Sigma. The mouse anti-GAPDH monoclonal antibody (AG019) was purchased from Beyotime Biotechnology. The mouse ICP22 antiserum was generated in our lab as previously described et al  according to the manufacturer's instructions. 40 h after transfection, the transfected cells were harvested, and total cellular protein extracts were prepared for western blot analysis.Luciferase assays were performed using a Dual-Glo luciferase assay system according to the manufacturer's instructions (Promega). Briefly, CHO-k1 cells were cultured in 6-well plates and co-transfected with expression plasmids  and reporter plasmids  with the pRL-CMV plasmid which expresses renilla luciferase as an internal control to normalize the transfection efficiency. For siRNA, Hep-2 cells were co-transfected with siRNA against Cdk9 and CyclinT1 as well as the expression and reporter plasmids mentioned above. All transfections were balanced for a total equal amount of DNA or siRNA with the empty plasmid pcDNA3 or negative control siRNA. The detection of both firefly and renilla luciferases activity were performed according to the Dual Luciferase Reporter Gene Assay Kit (Beyotime Biotechnology) 36 h post-transfection, relative luciferase activity (RLA) was calculated by normalizing to the renilla luciferase activity. Each experiment was repeated three times and the mean RLA was calculated for a statistical analysis.CHO-K1 or Hep-2 cells were cultured in 10-cm cell culture plates, next day CHO-K1 cells were co-transfected with the indicated plasmids, Hep-2 cells were mock infected or infected with HSV-1 (MOI = 1). 40 h post-transfection or post-infection, cells were washed with PBS and lysed for 30 min on ice in cold RIPA lysis buffer . The cell lysate was centrifuged at 14,000 g for 10 min, and the supernatant was precleared by incubation with protein A+G agarose beads (Beyotime Biotechnology) for 1 h at 4°C. An equal aliquot of the cell lysates was reserved as an input sample, whereas the remaining lysates were incubated with anti-Cdk9, anti-CyclinT1, anti-ICP22 or anti-VP16 antibodies under standard immunoprecipitation conditions and incubated at 4°C for 3 h with gentle agitation. Normal rabbit or mouse IgGs were used as controls. Protein A-agarose beads were added to the protein-antibody mixture and incubated overnight at 4°C with rotation. The beads were collected by centrifugation and washed three times with RIPA buffer and then subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE).CHO-K1 cell lysates were prepared as previously described. The cell lysates in RIPA buffer were incubated with 8 µg of Cdk9 and CyclinT1 antibodies or rabbit IgG (control) for 4 h at 4°C and then incubated with 100 µl of protein A+G sepharose beads overnight at 4°C. After centrifugation, the supernatants were collected and quantitated, and the protein supernatants of immunodepletion were subsequently subjected to immunoprecipitation or western blot analysis with the indicated antibodies.The precipitated proteins were quantitated, and equal amounts of the protein supernatants were subjected to 10% SDS-PAGE electrophoresis and transferred to a PVDF membrane, followed by a 5% BSA-TTBS  block. The transferred membranes were subsequently treated with a specific primary antibody and a goat anti-mouse or anti-rabbit IgG-HRP secondary antibody. Chemiluminescene (ECL) detection of antigen-antibody complexes using Immobilon Western HRP Substrates (Millipore) was performed according to the standard protocol.2 incubator for 5–7 d to observe the virus's cytopathicity. The 50% cell culture infective dose (CCID50) was determined by Reed-Muench assay.Hep-2 cells were co-transfected with the indicated plasmids (pcDNA3 as control) for 30 h, then infected with HSV-1 at MOI of 1.5. 20 h post-infection, the medium from Hep-2 cells were collected to measure the virus titer by microtitration assay. Briefly, viral stocks were serially diluted 10 times, and 100 µL of the diluted stocks were added to Vero cells with 80%-confluent in each of the 96-well plates. Overall, 8 parallel wells for each dilution stock were used. The 96-well plates were incubated at 37°C in a 5% CO−ΔΔCt. All experiments were repeated three times and the mean value was calculated for the statistical analysis.Total RNA was extracted from the infected Hep-2 cells using TRIzol reagent (Invitrogen) and reverse-transcribed to cDNA using the supermoIII RT kit . Real-time PCR of ICP4, ICP0 and control β-actin mRNA was performed using the SYBR Premix Ex Tag GC (Takara) . Relativ8 confluent CHO-k1 cells were co-transfected with different promoter reporter plasmids  in combination with the expression plasmids of ICP22 and/or VP16. For HSV-1 infected Hep-2 cells, 5×107 Hep-2 cells were transfected with ICP22, VP16 or control pcDNA3 expression plasmids for 36 h, and then infected with HSV-1 at an MOI of 10 or 2 as indicated. 40 h post-transfection or 3–13 h post-infection, cells were treated with 2 mM EGS [Ethylene glycol-bis(succinic acid N-hydroxysuccinimide ester)] (Sigma-Aldrich) for 40 min to crosslink the proteins and then washed three times with PBS, followed by treatment with formaldehyde (FA)  for 10 min at room temperature to crosslink proteins to DNA. Cells were then washed with cold PBS and lysed in SDS lysis buffer . The lysate was sonicated to shear DNA to between 200 and 1000 bp. The sonicated supernatant was diluted 10-fold with the ChIP dilution buffer , precleared with salmon sperm DNA/protein A-agarose (Upstate) for 1 h, and then incubated with a rabbit polyclonal antibody against CyclinT1 (Santa Cruz) or the negative control IgG overnight at 4°C with rotation. Immune complexes were collected using salmon sperm DNA/protein A-agarose and washed sequentially for 5 min with low-salt buffer, high-salt buffer, LiCl buffer and TE buffer. The pellet was dissolved in elution buffer (1% SDS and 0.1 M NaHCO3) and centrifuged to remove the agarose. The supernatant was treated with 5 M NaCl and heated to 65°C for 8 h to reverse crosslinking. The immunoprecipitated DNA was purified by proteinase K treatment, phenol–chloroform extraction, and ethanol precipitation. Immunoprecipitated promoter DNA and input (non-immunoprecipitated) DNA were analyzed quantitatively by real-time PCR using the MightyAmp SYBR Plus reagent  −ΔCt (pcDNA3), ΔCt (ICP22 and/or VP16) = Ct (IP)−Ct (input), and ΔCt (pcDNA3) = Ct (IP)−Ct (input). Each experiment was repeated three times and the mean value was calculated for the statistical analysis.The chromatin immunoprecipitation procedure and quantification were performed as previously described with minor modifications , China) . RelativData obtained from all experiments were described as the mean ± standard deviation (SD), and P<0.05 was considered to be statistically significant using a student's t-test.Figure S1Yeast trap and in vitro binding assay analysis of interaction between ICP22 and VP16. Yeast trap (upper panel): yeast strain AH109 was transformed with the indicated plasmids: pGAD-ICP22 and pGBK-VP16, negative control (pGADT7-T and pGBKT7-Lam), and positive control (pGADT7-T and pGBKT7-p53). Activity of β-galactosidase was measured respectively. The data represent relative β-galactosidase activity values were relative to the negative control from three independent experiments. In vitro binding assay (lower panel): 600 ng GST-VP16 fusion protein was incubated with 400 ng purified ICP22 protein at 4°C for 4 h (GST as control). 100 µl Glutathione-Sepharose precoated with BSA was then added and incubated overnight at 4°C. The protein-sepharose complexes were then boiled and subjected to 10% SDS-PAGE and analyzed by Western blotting using anti-ICP22 antibody.(TIF)Click here for additional data file.Figure S2The enhancement of P-TEFb binding to the transcription complex of viral α4 gene promoter in the presence of crosslinking agents in ChIP assays. CHO-K1 cells were transfected with pGL-α4 plasmid and subjected to ChIP assays. FA or FA plus EGS were used as the crosslinking agents. Antibodies specific for CyclinT1 or control rabbit IgG were used for immunoprecipitation. Real-time PCRs were performed to analyze the precipitated α4 promoter DNA. Values are expressed as percentages of input DNA immunoprecipitated. Error bars represented the standard deviation from triplicate samples.(TIF)Click here for additional data file.Table S1Primers for gene amplification. Oigonucleotide sequences for amplification of Cdk9 and CyclinT1 genes.(DOC)Click here for additional data file.Table S2Oigonucleotide sequences for RNA interference (RNAi). siRNA duplexes against Cdk9 and CyclinT1 genes.(DOC)Click here for additional data file.Table S3Primers for RT-PCR. Oligonucleotide sequences for quantitative real time PCR analysis.(DOC)Click here for additional data file.