Overexpression of the MYC transcription factor causes its widespread interaction with regulatory elements in the genome but leads to the up- and down-regulation of discrete sets of genes. The molecular determinants of these selective transcriptional responses remain elusive. Here, we present an integrated time-course analysis of transcription and mRNA dynamics following MYC activation in proliferating mouse fibroblasts, based on chromatin immunoprecipitation, metabolic labeling of newly synthesized RNA, extensive sequencing, and mathematical modeling. Transcriptional activation correlated with the highest increases in MYC binding at promoters. Repression followed a reciprocal scenario, with the lowest gains in MYC binding. Altogether, the relative abundance  of MYC at promoters was the strongest predictor of transcriptional responses in diverse cell types, predominating over MYC's association with the corepressor ZBTB17 . MYC activation elicited immediate loading of RNA polymerase II (RNAPII) at activated promoters, followed by increases in pause-release, while repressed promoters showed opposite effects. Gains and losses in RNAPII loading were proportional to the changes in the MYC share, suggesting that repression by MYC may be partly indirect, owing to competition for limiting amounts of RNAPII. Secondary to the changes in RNAPII loading, the dynamics of elongation and pre-mRNA processing were also rapidly altered at MYC regulated genes, leading to the transient accumulation of partially or aberrantly processed mRNAs. Altogether, our results shed light on how overexpressed MYC alters the various phases of the RNAPII cycle and the resulting transcriptional response. The MYC transcription factor is overexpressed and acts as an oncogenic driver in numerous tumor types. Shedding light on the transcriptional programs driven by MYC is thus a critical area of investigation, with important translational implications. Indeed, numerous studies focused on the analysis of MYC-induced transcriptional responses, typically measuring its binding through ChIP-seq and profiling transcriptional maps by RNA-seq . A serieAt the mechanistic level, how MYC activates and represses transcription remains to be largely addressed. In particular, a unifying view on the role of MYC in the recruitment and progression of RNA polymerase II (RNAPII) within the transcriptional units of regulated genes and the consequent dynamics of transcriptional regulation is still lacking, owing to a series of reasons. First, the interplay between MYC and RNAPII has been studied based on the simple quantification of the density of RNAPII by ChIP-seq, which is not univocally informative on the various steps of RNAPII loading and progression along the transcriptional units. For example, the change of RNAPII density at promoters is determined by the joint action of recruitment and pause-release dynamics, which cannot be fully resolved based on the ChIP-seq data only . Second,In order to overcome these limitations, we set to comprehensively characterize the dynamics of transcriptional regulation following MYC activation in mouse fibroblasts. To this purpose, we profiled nascent and total RNA, alongside MYC and RNAPII binding, and used mathematical modeling to quantify the kinetic rates governing the synthesis, processing, and degradation of mRNA and regulating RNAPII loading and progression through the transcriptional units.MYC-ER fibroblasts (tet-MYC) .To address how binding of MYC to promoters affects gene regulation, we exploited a series of ChIP- and RNA-seq data sets with activated MYC and control samples. The first three were derived from in vitro models, including the post-translational activation of a Myc-ER chimera in mouse 3T9roblasts , as welltet-MYC)  and B-cetet-MYC) . Two othymphomas  and tet-ymphomas , each cotet-MYC cells indicated that the extent of either activation or repression by overexpressed MYC correlated with the increase in MYC occupancy at promoters  or considering every differentially expressed transcript  but showed the opposite for repressed genes (blue lines): as a consequence, the whole transcriptome showed a more homogeneous trend, repressed and activated genes showing the lowest and highest gains in MYC binding, respectively  (P = 0.81) . The other data sets, instead, all gave robust positive and statistically significant correlations. The reasons for this discrepancy may reside in a number of technical parameters, the resolution of which is beyond the scope of our work.The apparently opposite regulatory behavior of repressed genes in U2OS cells is a paradoxical result, which remains to be explained. We deem it unlikely, however, for this to represent a real distinctive feature of these cells. Indeed, we must note that the negative correlation between the changes in MYC share and transcription of repressed genes in the U2OS data set was remarkably low and not statistically significant, whether analyzing genes individually  A or binntet-MYC cells, the transcriptional response to MYC has also been correlated with the MYC/ZBTB17 ratio at promoters . In 3T9MYC-ER cells and Eµ-myc lymphomas, instead, the MYC share had much stronger predictive values, with minor albeit significant contributions of ZBTB17—whether expressed as a MYC/ZBTB17 ratio or as straight ZBTB17 binding . In particular, the ability of MYC to recruit RNAPII seemed to be fine-tuned by ZBTB17: indeed, in all the systems analyzed, the gain in MYC binding that discriminated between activation and repression slightly increased with the level of ZBTB17 binding . Overall, the above observations show that the variation in MYC share at promoters was the main feature separating induced from repressed genes across cell types: gains in MYC binding were roughly proportional to gene activation, as previously reported . However, very few promoters showed actual saturation by MYC in control cells, including proliferating U2OStet-MYC cells . It is noteworthy here that the gain in MYC binding for the high-affinity promoters resulted in the maintenance of their MYC share, consistent with their weak or absent transcriptional response , accompanied by an immediate increase in the immature forms of known MYC-induced mRNAs, followed by accumulation of the mature forms at later time points . We thus used RNA-seq to profile both total and newly synthesized RNA (the latter isolated after 10 min of metabolic labeling with 4sU)   in a detith 4sU) A. Integrith 4sU)  to deterith 4sU) B. Brieflith 4sU) C,D. Effeith 4sU) C,D. ChIPith 4sU) A revealeith 4sU) C,E, confith 4sU) .Supplemental Fig. S3A). For each cluster, we modeled the different steps involved in RNAPII-mediated transcription, based on four parameters , the rate of RNAPII pause-release from the promoter (p2), the elongation rate  (4). Briefly, the changes in density of RNAPII in each region of the transcriptional unit are considered as the net result of (1) the flux of incoming RNAPII from the upstream region, and (2) the flux of RNAPII exiting to the downstream region, both governed by the corresponding kinetic rate (see Methods for details). Importantly, the four parameters (p1–p4), inferred along the entire time-course for each cluster , accurately recapitulated the experimental data .To further address the mechanisms underlying MYC-regulated transcription, we also mapped RNAPII by ChIP-seq A. We therameters : the flune-body) , and the2), rather than loading (p1) . However, these changes were associated with sudden and more prominent changes in RNAPII loading . We conclude that MYC promotes both RNAPII loading and pause-release, thus regulating two key steps in transcription initiation (Previous studies suggested that MYC activates transcription mainly—if not solely—at the level of RNAPII pause-release (ping (p1) . In appa loading A,C. Follitiation .1) . In four clusters (cl9–12), p1 values transiently became negative, indicating nonproductive detachment of RNAPII from promoters. Importantly, the reduced levels of RNAPII were not due to increased pause release, as p2 values also rapidly went down in response to MYC activation (with the exception of cl7). Thus, MYC-repressed genes underwent a general reduction in RNAPII loading.In parallel with the above, down-regulated clusters  showed marked decreases in the RNAPII signal at promoters A, owing 1, on average 69% of explained variance) . Hence, the first effect of MYC-ER was a rapid modulation of RNAPII flux at promoters, with increases in recruitment at activated genes and, reciprocally, decreases—or even inversion—at repressed loci, which also showed the lowest gains in MYC binding. Altogether, the above observations show that acute activation of MYC causes direct recruitment of RNAPII to activated promoters, accounting for most of the observed changes in RNA synthesis, at either up- or down-regulated loci.We showed above that changes in MYC share at promoters correlated with changes in gene expression  and syntariance) D, while Supplemental Fig. S4A). Notably, at induced loci, the increases in RNAPII density exceeded those in RNA synthesis , suggesting that decreasing rates of polymerase elongation contributed to RNAPII accumulation in induced genes . Moreover, while MYC-induced increases in pause-release also contributed to RNAPII accumulation in induced genes, the changes in elongation were more sustained (2 vs. p3)   D. This s(cl9–12) A,C.Supplemental Fig. S4C). Opposite effects occurred at a subset of repressed genes. In silico modeling confirmed that fixing the processing rates of the induced genes at the levels of the untreated condition prevented the observed accumulation of pre-mRNA . Consistent with previous observations . These alterations peaked at the time of maximum changes in the rates of elongation and processing  and were enriched at the 3′ end of genes . Additional alterations occurred late, possibly due to the downstream action of splicing factors, which were enriched among MYC-regulated gene products.Shortly after the decrease in RNAPII elongation, almost half of the induced genes showed decreasing rates of pre-mRNA processing with concomitant accumulation of pre-mRNA, anticipating the transcriptional response  (tet-MYC and 3T9MYC-ER). The role of the MYC share in directing the induction or repression of MYC target genes emerged as a common denominator among these systems, strengthening the view that transcriptional amplification, when observed, does not occur as a direct effect of MYC but rather as a secondary consequence of cellular activation  could effectively discriminate induced from repressed genes. The role of the MYC share was examined in various systems, including models with global increases in transcriptional activity  , or withtivation .Second, we dissected the effects of MYC on the RNAPII life cycle along transcriptional units, identifying loading as the key regulated step. Previous reports indicated that MYC activates transcription through RNAPII pause-release : while wSupplemental Fig. S3E), loss of RNAPII from repressed promoters may have largely resulted from competition for limiting amounts of polymerase. Thus, besides interfering with the activating function of ZBTB17 or other transcription factors, MYC may repress transcription indirectly, owing to passive loss of RNAPII. MYC may also elicit repression through other indirect mechanisms, such as the induction of PTEN, resulting in augmented activity of the Polycomb Repressive Complex PRC2 . Our results also support the concept that ZBTB17, rather than forming repressive complexes with MYC at repressed promoters, may affect its ability to recruit RNAPII at those loci.Fourth, and consistent with the above, transcriptional repression by MYC is partly independent from its interaction with ZBTB17. Indeed, the strongest predictor of transcriptional outcome was the MYC share at promoters, more significant than either ZBTB17 binding or the MYC/ZBTB17 ratio . MoreoveFifth, the rapid effect of MYC-ER on RNAPII recruitment probably caused an overload of the transcriptional machinery at induced loci, as revealed by reduced rates of RNAPII elongation and accumulation of RNAPII at gene-bodies. This could be due to the combination of several factors, including RNAPII crowding, shortage of nucleotides, or the interplay between RNAPII and the spliceosome. In particular, a role for the latter is supported by our data, since pre-mRNA processing rates decreased in parallel to the increase of RNAPII at gene-bodies, leading to the accumulation of unprocessed mRNAs. This points to a limiting activity of the spliceosomal machinery at MYC-activated loci, consistent with its critical role for cell survival in MYC-driven tumors .MYC-ER fibroblasts were obtained by infecting 3T9 c-Myc flox/flox immortalized fibroblasts  but grown without zeocin for subsequent experiments. MYC-ER activation was achieved by addition of 400 nM of the synthetic 4-hydroxytamoxifen . For RNA degradation validation, cells were treated with 1 µM flavopiridol hydrochloride hydrate (Sigma-Aldrich) for the indicated time points.3T9roblasts  with a problasts  and wereDetection of nascent RNA by metabolic labeling using 4sU (4-methio-uridine) has been performed as described before  by labelhttp://www.ncbi.nlm.nih.gov/geo/) under accession number GSE98420. The complete source code for all analyses, including intermediary results and the raw images, is available in the Supplemental Material.The high-throughput sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO;


Cd4, Cd8, and Gata3 genes in thymocytes. We performed ATAC-seq at four distinct stages of development in mouse thymus, probing the chromatin accessibility landscape in double negative (DN), double positive (DP), CD4 single positive (SP4) and CD8 SP (SP8) thymocytes. Integration of chromatin accessibility with TF motifs genome-wide allowed us to infer stage-specific occupied TF binding sites within known and potentially novel regulatory elements. Our results provide genome-wide stage-specific T cell open chromatin profiles, and allow the identification of candidate TFs that drive thymocyte differentiation at each developmental stage.In vertebrates, multiple transcription factors (TFs) bind to gene regulatory elements  to execute developmental expression changes. ChIP experiments are often used to identify where TFs bind to regulatory elements in the genome, but the requirement of TF-specific antibodies hampers analyses of tens of TFs at multiple loci. Here we tested whether TF binding predictions using ATAC-seq can be used to infer the identity of TFs that bind to functionally validated enhancers of the  While ETP retain multi-lineage differentiation capacity, they gradually lose the potential to become non-T lineage cells and become increasingly restricted to a T lineage fate4. During the DN stages, committed, developing T cells undergo immune system-specific DNA recombination, and must successfully recombine a Trb gene allele  to then pass the β selection checkpoint (when the formation of a pre-TCR complex is assessed)6 in order to survive. At the next DP stage (where both CD4 and CD8 are expressed on the cell surface), the TCRα receptor rearranges, and only cells expressing a functional cell surface TCR complex (TCRα plus TCRβ) that is able to bind with appropriate affinity to the major histocompatibility complex (MHC) survive positive selection7. DP cells recognizing MHC class I can then mature into SP8 T cells, while DP cells recognizing MHC class II mature into SP4 T cells. Finally, negative selection eliminates by apoptosis cells that bind to self-peptides presented by the MHC, and only cells that do not exhibit high affinity to self-peptides survive7.T cells develop in the thymus, where biologically distinct events driven by the interplay of multiple transcription factors (TFs) acting in coordination take place at each thymocyte stage. After migration of thymic seeding progenitors from the bone marrow and their occupation of supportive niches in the thymic medulla, early thymic progenitors (ETP) develop through immature double negative , 107,110 (DP), 115,074 (SP4) and 104,411 (SP8) genomic open chromatin peaks at 5% FDR , one that was ubiquitous, and one that was a combination of DN and ubiquitous  of patterns of chromatin accessibility across the analyzed thymocyte developmental stages in an unbiased manner. We performed ous Fig. . The ubious Fig. , which ip < 10−3 24, pairwise Kolmogorov-Smirnov tests with Bonferroni correction), suggestive of it being more associated with promoters and housekeeping genes than cell-identity features 26 and CTCF ChIP-seq in total thymocytes 22. We used the Genomic Annotation Tester (GAT) tool27 to statistically evaluate the overlap between footprint calls and ChIP-seq bound motifs, while controlling for genome and feature sizes, as well as mapability issues (see Methods for details). Tests on both datasets showed significant overlap between ChIP-seq and footprint data (p < 10−3), indicating that the footprint predictions recapitulate actual protein binding events detected by ChIP-seq for the corresponding TF . RUNX patterns were visible in the common and DN clusters, but not in the more differentiated stages. Although GATA footprints were enriched in all clusters, we could not detect strong binding patterns, which is suggestive that it may have weaker interactions with DNA29. Interestingly, we did not find any SP4- or SP8-specific occupancy patterns, even though some motifs, such as TCF3 and ID4, had higher enrichment values in the SP4- and SP8-specific clusters than in the ubiquitous cluster . ChIP experiments, in contrast, can capture indirect binding by virtue of protein-protein interactions that occur in larger complexes formed with a specific DNA binding protein31, potentially complicating assignment of which factor is genuinely bound to DNA at any given site.We performed ATAC-seq experiments and footprint analyses at four major stages of thymocyte development in order to compile a catalogue of stage-specific accessible chromatin sequences as well as to identify specific sequences bound by TFs. We identified ubiquitous and stage-specific open chromatin regions, recapitulating the identity of functionally validated regulatory elements, as well as revealing novel regulatory loci. The ATAC-seq footprinting data for predicted αβT cell activators and repressors highlighted TF-bound motifs within those regulatory regions, as well as bound motifs that were enriched in each of the thymocyte stage-specific accessible chromatin clusters, providing an in-depth view into the inner regulatory workings of thymocyte development. We identified between 8 and 20 novel sequences that were predicted to be bound by proteins within previously identified regulatory elements for the k-means clustering approach highlighted the positions for thousands of potentially novel developmental stage-specific regulatory elements. The ATAC peaks provided evidence for the previously predicted closed- or open-chromatin status in both the Cd4 and Cd8 loci during thymocyte development32. Furthermore, the identification of two major ATAC peaks within the 7.1 kbp that originally defined the Gata3 enhancer, TCE134, suggests that one or both of these two open chromatin domains (of approximately 600 bp and 500 bp) play a major role in the enhancer activity of TCE1. In agreement with this hypothesis, one of these ATAC-seq peaks aligns perfectly with a 1.2 kbp “core” sequence that exerts similar reporter gene activation in thymocytes of transgenic mice that is roughly equivalent to the whole 7.1 kbp TCE1 sequence34.The thymocyte stage-specific open chromatin regions identified here by ATAC-seq followed by 28 predicted from lineage specific gene expression profiles. The most immediate future plans following these identifications are to investigate whether or not each bound sequence is necessary for any specific enhancer/silencer activity, which can be tested by in vivo genomic DNA mutation of the TF motif. In summary, the genome-wide view of open chromatin presented here as well as the identification of the sequence motifs bound by TFs at four different stages of thymocyte development is a useful point from which to begin to assemble precise models for transcriptional regulation of T cell stage-specific gene expression.Enrichment of footprints in the stage-specific open chromatin clusters highlighted TF families binding to the motif as potential stage-specific regulators. These data provide an additional layer of information to the αβ T cell factors17. In brief, 50,000 to 100,000 DN, DP, CD4 SP and CD8 SP thymocytes were isolated by flow cytometry , properly paired alignments and uniquely mapped as described in our previous study12.ATAC libraries were prepared as described previously20 with options –nomodel –shift -50 –extsize 100 -B –keep-dup all. For testing the reproducibility between samples, we generated a set of regions that were called (narrow) peaks in at least one of the merged samples, retrieved the number of fragments mapping to these regions in each replicate and calculated the pairwise Pearson correlations between all replicates of the same stage.In order to account for sequencing depth differences between each library, we down-sampled reads (keeping read pairs intact) to the median depth of all libraries after the pruning steps described above. This ensures that sequencing depth would not confound the analysis. After this step, we combined all replicates from each stage into a single BAM file to increase sequencing depth (ranging from 120 to 134 million reads per stage) and called peaks using MACS2st and 3rd quartiles, to make the values comparable across samples. This signal was then row-wise normalized by the maximum of every sample k = 1, 2, …, 15 k values and determined that k = 6 was suitable for our analyses. Increasing k to higher values only marginally decreased variance and yielded repetitive clusters patterns, with 1,000 random starts for robustness. We analyzed the within cluster variances for all  by using bedtools merge in the combined MACS2 output for all samples. For each sample, we calculated the FPKM in each of the master peaks regions, and normalized the signal by dividing the values by the TSS enrichment of the sample, which accounts for the signal-to-noise ratio, and then applied robust IQR scaling et al.28 from stage-specific gene expression profiling . Position weight matrix (PWMs) for each motif was obtained from ENCODE35, JASPAR36 and TF pairs identified by Jolma et al.37. Total 417 binding motifs for 67 out of 171 Jojic αβ T cell factors were derived from these databases.In the current study we focused on TF binding motifs for T cell activators and repressors that were predicted by Jojic 38 with the G-C content background frequency for mm10 (41.7%), and used the default 10−4 P value threshold, also filtering for motif occurrences intersecting regions with known mapability issues (blacklisted regions). CENTIPEDE25 was used to call footprints from the ATAC-seq data as we have done previously13. Briefly, for each PWM scan result we generated a strand-specific (relative to the motif orientation) single base pair resolution matrix encoding the number of Tn5 transposase integration events in a region ±100 bp from each motif occurrence. A motif occurrence was considered bound if the CENTIPEDE posterior probability was higher than 0.99 and its coordinates were entirely contained by an ATAC-seq peak. To generate the motif occupancy plots for each factor, we aggregated the signal used as input for CENTIPEDE for all the predicted bound motifs, as well as an equal number of motifs with posteriors less than or equal to 0.5 and not intersecting ATAC-seq peaks in that sample. The normalized signal plotted was obtained by dividing the bound signal by the unbound.We scanned the mm10 genome for the PWMs for the 417 motifs using FIMO27 with the workspace set as all the GATA or CTCF motif matches in the mm10 genome, the respective ChIP-seq peaks as the segments, and the respective CENTIPEDE footprint calls as the annotation. By limiting the workspace only to the specific motifs, the data stringently delimit the space for genomic interval overlap testing. The footprint enrichments in the ATAC-seq clusters were performed separately for each sample and for each motif. We used as workspace all the motif occurrences within the master peaks regions (see k-means clustering above) for the individual motif being analyzed. As annotations, we used the cluster designations from the k-means analysis. The segments were all the footprints for that motif in that sample. Additionally, we used the option -n to 1,000 in order to increase statistical robustness. This resulted in a table with the GAT results for every motif in each cluster and in each sample.In order to test the correspondence between footprint calls and ChIP-seq data for GATA and CTCF, we used GAT39 and accessible through accession number GSE107076.ATAC-seq and footprint data have been deposited in GEO databaseSupplementary Information


Polycomb-based repressive chromatin.The first genome-wide examination of the chromatin landscape at the periphery of the plant cell nucleus reveals substantial enrichment of heterochromatin and  Arabidopsis NUCLEOPORIN1 (NUP1) protein, an inner subunit of the nuclear pore complex (NPC) [The cell nucleus is a highly structured subcellular organelle that functionally houses the genome. The double-membrane nuclear envelope provides a physical interface that contributes to the compartmentalization of chromosomal domains that have distinct chromatin states and activities within the nuclear space. Our knowledge of chromatin organization and function in plant systems is rapidly expanding, and the roles of different nuclear peripheral components in structuring chromatin are also beginning to emerge . In metaex (NPC)  responsiArabidopsis cells, most heterochromatin typically aggregates around the centromeric and peri-centromeric regions, forming conspicuous subnuclear foci referred to as chromocenters which are thought to tether transposable elements (TEs) from distant genomic domains [Arabidopsis chromocenters are usually located near the nuclear periphery [Arabidopsis NPCs enhanced its expression [CAB (CHLOROPHYLL A/B-BINDING PROTEINS) genes are repositioned from the interior to the periphery of Arabidopsis cotyledon nuclei when induced by light signaling [In  domains   are frequently involved in long-range interactions between distant loci in plants [Arabidopsis chromosomes also form nucleolus-associated domains (NADs) that are enriched in transcribed ribosomal DNA genes and telomeric regions. Interestingly, NADs also contain heterochromatic TEs and silent protein-coding genes that might be sequestered in the nucleolus away from the RNA Pol II machinery (reviewed in [The integration of genome-wide ChIP-seq and Chromosome Conformation Capture 3C) approaches has recently extended linear epigenomic information on successive chromatin states towards a three-dimensional model of intra-chromosomal associations in n plants  and mammn plants . ArabidoC approacThe study by Bi and colleagues  offers aArabidopsis CAB genes [Polycomb-repressed genes (Fig. Bi and colleagues also report that NUP1 RE-CHIP pulled down chromatin fragments that were enriched in acetylated histone H3 and other chromatin modifications characteristic of transcribed genes. The proximity between transcribed genes and NPCs might facilitate mRNA export via the so-called 'gene-gating process' proposed both for animal cells  and for nes Fig. . DetermiArabidopsis. On the one hand, the association of transcriptionally active chromatin with NPCs can promote efficient mRNA surveillance and export [Polycomb-repressed silent regions at the nuclear periphery may provide an efficient way to organize or stabilize higher-order chromatin architecture. A potential contribution of H3K27me3-marked domains in tethering long-range euchromatin interactions around the nuclear periphery offers a novel and exciting working hypothesis for further investigations.The study by Bi and colleagues  adds to d export  while, oArabidopsis nuclei. PRC2 subnuclear foci are not exclusively enriched at the nuclear periphery, neither is RNA Polymerase II excluded from this area [A further question that is raised is whether there is a gradient of transcriptionally active chromatin domains from the interior to the periphery in his area , possiblhis area . This mohis area . AdditioArabidopsis to be extended, and uncover the molecular drivers of plant nuclear architecture diversity.Cell cycle and cellular responses to endogenous and environmental signals trigger dramatic changes in nuclear architecture whose functional impact on genome expression programs remains poorly understood. Future investigations of peripheral chromatin dynamics during cellular transitions thus offer exciting perspectives that can be used to unravel the functional plasticity of plant cell nuclear organization. Exploration of how plant lamina-like components and chromatin-bound factors mediate the anchoring of distinct chromosomal domains in plant species with diverse genomic and chromosomal arrangements should additionally allow the work of Bi and colleagues in


SPRY2 gene. Here, we demonstrate that in the human hepatoma cell line, Hep3B, the transcription of SPRY2 is inhibited by the transcription regulating hypoxia inducible factors (HIFs). HIFs are composed of an oxygen regulated alpha subunit (HIF1α or HIF2α) and a beta subunit (HIF1β). Intriguingly, silencing of HIF1α and HIF2α elevates SPRY2 mRNA and protein levels suggesting HIFs reduce the transcription of the SPRY2 promoter. In silico analysis identified ten hypoxia response elements (HREs) in the proximal promoter and first intron of SPRY2. Using chromatin immunoprecipitation (ChIP), we show that HIF1α/2α bind near the putative HREs in the proximal promoter and intron of SPRY2. Our studies demonstrated that not only is the SPRY2 promoter methylated, but silencing HIF1α/2α reduced the methylation. ChIP assays also showed DNA methyltransferase1 (DNMT1) binding to the proximal promoter and first intron of SPRY2 and silencing HIF1α/2α decreased this association. Additionally, silencing of DNMT1 mimicked the HIF1α/2α silencing-mediated increase in SPRY2 mRNA and protein. While simultaneous silencing of HIF1α/2α and DNMT1 increased SPRY2 mRNA a little more, the increase was not additive suggesting a common mechanism by which DNMT1 and HIF1α/2α regulate SPRY2 transcription. Together these data suggest that the transcription of SPRY2 is inhibited by HIFs, in part, via DNMT1- mediated methylation.Receptor Tyrosine Kinase (RTK) signaling plays a major role in tumorigenesis and normal development. Sprouty2 (Spry2) attenuates RTK signaling and inhibits processes such as angiogenesis, cell proliferation, migration and survival, which are all upregulated in tumors. Indeed in cancers of the liver, lung, prostate and breast, Spry2 protein levels are markedly decreased correlating with poor patient prognosis and shorter survival. Thus, it is important to understand how expression of Spry2 is regulated. While prior studies have focused on the post-translation regulation of Spry2, very few studies have focused on the transcriptional regulation of  Sprouty (Spry) proteins were first discovered in Drosophila melanogaster as inhibitors of fibroblast growth factor receptor-induced tracheal branching . SubsequSPRY is upregulated by growth factors [SPRY2 promoter, few have actually been shown to bind [SPRY2 promoter and identified that Ap2, Ets-GATA, and SP-1 bind to the SPRY2 promoter enhancing its transcription [SPRY2 promoter remains unknown.We focused on Spry2, which is ubiquitously expressed and most studied among the Spry isoforms. Prior studies have concentrated on the regulation of the Spry2 protein through a variety of posttranslational modifications such as ubiquitylation or phosphorylation . How factors –37 eleva to bind . Ding etcription . HoweverSPRY2 promoter have shown that FOXO and beta-catenin bind to the SPRY2 promoter and induce its transcription [SPRY2 promoter is hypermethylated in hepatocellular carcinomas [Because Spry2 levels are reduced in some forms of cancer –29,31, tcription ,45. In tcription , but notcription . Two reprcinomas ,47, but rcinomas .In both development and tumorigenesis, cells experience a hypoxic environment to which they adapt to by upregulating the transcription factors, hypoxia inducible factors (HIFs). HIFs are composed of an oxygen-regulated alpha subunit (HIF1α/HIF2α) and a beta subunit (HIF1β a.k.a. aryl hydrocarbon receptor nuclear translocator (ARNT)). Opposite to the actions of Spry2, HIFs promote proliferation, migration, and survival of cells by increasing the transcription of a number of genes that regulate these processes (reviewed in –50).in silico analysis of the SPRY2 promoter for hypoxia response elements (HRE) with the consensus sequence 5’-A/GCGTG-3’ and found 10 putative HREs; five in the proximal promoter and five in the first intron. Therefore, the purpose of this study was to determine whether HIF1α/HIF2α regulated the transcription of the SPRY2 promoter. Herein, we demonstrate that, in the hepatoma cell line Hep3B, endogenous HIF1α and HIF2α decreased the mRNA levels of SPRY2 with a concomitant decrease in the protein levels of Spry2. While the stability of the SPRY2 mRNA wasn’t altered by HIF silencing, inhibiting DNA methylation with decitabine (DAC) abolished the increase in SPRY2 mRNA when the expression of HIF1α/2α were silenced. Chromatin Immunoprecipitation (ChIP) assays revealed HIF1α/2α bind to regions in both the proximal promoter and first intron, each of which contains four and five HIF1α/HIF2α binding sites, respectively. Methylation of the proximal promoter of SPRY2 was also observed and HIF1α/2α silencing decreased this methylation. Furthermore, ChIP assays revealed association of DNA methyltransferase 1 (DNMT1) with the proximal promoter and first intron of SPRY2 and silencing of HIF1α/2α diminished this interaction. Finally, silencing of DNMT1 mimicked the actions of HIF1α/2α silencing in elevating SPRY2 mRNA and protein levels. However, simultaneous silencing of DNMT1 and HIF1α/2α did not elevate SPRY2 mRNA or protein levels additively suggesting that DNMT1 and HIF1α/2α work through a common mechanism. These data suggest that HIF1α/2α suppress SPRY2 transcription, in part by increasing SPRY2 promoter methylation by DNMT1.Because Spry2 protein levels are decreased in hepatocellular carcinomas –28 and gSPRY2 mRNA and protein levels, we used siRNAs to silence the expression of endogenous HIF1α and HIF2α proteins in the hepatoma cell line Hep3B. While the silencing of HIF1α or HIF2α separately elevated SPRY2 mRNA levels by about 100% each, silencing of both HIF1α and HIF2α together more profoundly (200%) elevated SPRY2 mRNA levels   [PGK-1 mRNA while expression of HIF1β alone or together with HIF2α had no effect  . As expeSPRY2 mRNA. For this purpose, Hep3B cells transfected with control or HIF1α and HIF2α siRNAs were treated with actinomycin D to inhibit RNA synthesis and the mRNA levels of SPRY2 were then monitored over 2 hours by qRT-PCR. As shown in SPRY2 mRNA levels were reduced by approximately 80%. However, the rate of SPRY2 mRNA degradation was not significantly different whether or not HIF1α and HIF2α were silenced  with the consensus sequence 5’-A/GCGTG-3’ in the promoter of the genes they regulate [in silico analysis to determine if the SPRY2 proximal promoter (-3850 to +1) or first intron (+1 to +3395) contained putative HREs. Indeed, we found 5 putative HREs in the proximal promoter located at positions -3271, -1360, -1319, -570, and -390 and 5 putative HREs in the first intron located at nucleotides 1770, 1811, 1830, 1858, and 1953  [EPO genes, and silencing of HIF1α or HIF2α greatly diminished the DNA enrichment from PFK and EPO promoters, respectively  assay using a HIF1β antibody to immunoprecipitate both HIF1α and HIF2α bound DNA. We then used primers targeted against 4 different HRE containing areas of the proximal promoter and intron of er set 1 . Howeverse sites . As a poes (EPO) ,59. As eectively . These lSPRY2 promoter and first intron to repress the expression of Spry2. While studies have shown that hypoxia represses a set of genes, not many studies have shown that HIF1α or HIF2α specifically repress gene transcription. Furthermore, the precise mechanisms of repression are unknown or vary depending on the gene [SPRY2 promoter: (a) altered SPRY2 mRNA levels, (b) modulated the ability of HIF1α/HIF2α silencing to alter SPRY2 mRNA levels, and (c) was regulated by endogenous HIF1α/HIF2α.The data in Figs the gene –64. Meththe gene  and hypothe gene ,67. TherSPRY2 promoter were methylated. Using bisulphite-treated genomic DNA and primers that specifically detect methylated  and unmethylated  DNA corresponding to the regions 1 and 2 on the SPRY2 promoter shown in SPRY2 promoter after treatment with DAC or its vehicle. As shown in SPRY2 promoter at primer sites 1 and 2 by 80% and 47%, respectively. Concomitantly, as expected, the amount of unmethylated promoter monitored by unmethylated DNA-specific primers for sites 1 and 2 was elevated by 78% and 80%, respectively. These findings demonstrate that the SPRY2 promoter is methylated and DAC treatment effectively reduces its methylation.By treating cells with decitabine (DAC), an inhibitor of DNA methyltransferases ,69, we fSPRY2 mRNA levels and the ability of HIF1α/HIF2α silencing to further modulate the amount of SPRY2 mRNA. As shown in SPRY2 mRNA levels by nearly 2-fold. However, while HIF1α/HIF2α silencing in vehicle treated cells (control) elevated SPRY2 mRNA levels by ~100%, in the presence of DAC, silencing of HIF1α/HIF2α did not significantly increase SPRY2 mRNA levels  vs. unmethylated DNA (U-1 and U-2), we determined the methylations status of the SPRY2 proximal promoter with and without HIF1α/HIF2α silencing. As shown in SPRY2 promoter methylation detected by M-1 and M-2 primers by 52% and 42%, respectively, and increased the amounts of unmethylated SPRY2 promoter monitored by U-1 and U-2 primers by 111% and 82%, respectively. Overall, these data , which are the enzymes that methylate the 5-position of cytosine in DNA primarily within a CpG dinucleotide . There an embryo . DNMT3L n embryo . Intrigun embryo ). One pon embryo –78. In fn embryo ,80. WithSPRY2 promoter   irrespective of which protein we immunoprecipitated. Thus, the precise mechanism by which HIF1α/HIF2α regulates binding of DNMT1 to the SPRY2 promoter and first intron remains to be defined.One mechanism by which DNMT1 could be recruited to the SPRY2 mRNA levels by HIF1α/HIF2α, we monitored the levels of SPRY2 mRNA in cells transfected with either control siRNA or siRNAs targeting HIF1α/HIF2α when DNMT1 expression was either silenced or not. In these studies, we included two hepatocellular carcinoma cell lines, HuH7 and Hep3B, to demonstrate the generality of the mechanisms investigated in this report. As shown in SPRY2 mRNA levels by 130%. The silencing of DNMT1 alone also increased SPRY2 mRNA levels by ~50% . As SPRY2 mRNA and protein as silencing of endogenous HIF1α and HIF2α elevate both SPRY2 transcript and protein levels. Conversely, ectopically expressed HIF1α and HIF2α decrease the amounts of SPRY2 mRNA. The increase in SPRY2 mRNA levels is not the result of changes in stability of the transcript, but for the following reasons, is a function of the change in transcription of the SPRY2 gene. First, HIF1α/HIF2α bind to the proximal promoter and first intron of the SPRY2 gene that contains a total of nine putative HRE consensus sequences . Second, HIF1α and HIF2α increase the methylation of the SPRY2 promoter and repress SPRY2 mRNA expression. Third, the inhibitor of DNMT1, LCA, and DNMT1-specific siRNA augment SPRY2 mRNA and protein levels mimicking the effect of HIF1α/HIF2α silencing had to a lesser extent. As discussed later, simultaneous silencing HIF1α/HIF2α with DNMT1 resulted in a significant increase only in SPRY2 transcript and not Spry2 protein levels. However, this increase in SPRY2 mRNA with DNMT1 and HIF1α/HIF2α silenced was not additive suggesting DNMT1 and HIF1α/HIF2α regulate SPRY2 through a similar mechanism.The evidence presented in this report demonstrates that endogenous HIF1α and HIF2α decrease the amounts of SPRY2 promoter and silencing of HIF1α/HIF2α decreases this association of DNMT1 with the SPRY2 promoter. These findings suggest that HIF1α/HIF2α, in some manner, recruit DNMT1 to the SPRY2 promoter to alter the methylation state of the promoter and, therefore, transcription of the SPRY2 gene. One obvious mechanism would be the association between HIF1α/HIF2α and DNMT1 to recruit DNMT1 to the SPRY2 promoter. However, despite several attempts using different immunoprecipitation conditions to elucidate interactions between HIF1α/HIF2α and DNMT1, we have been unable to show that these proteins reside in the same complex. It is possible that HIF1α/HIF2α alter the expression of some other protein that then permits the recruitment of DNMT1 to the SPRY2 promoter.Moreover, our studies also show that DNMT1 binds the SPRY2 promoter and first intron, it would be expected that silencing of DNMT1 would increase SPRY2 mRNA to the same extent as silencing of HIF1α/HIF2α alone or together with DNMT1. However, in both Hep3B and HuH7 cells, the silencing of DNMT1 alone elevated SPRY2 mRNA levels to a significantly lesser extent than when HIF1α/HIF2α and DNMT1 were silenced simultaneously  that may contribute toward HIF1α/HIF2α- mediated regulation of SPRY2 promoter methylation should be the subject of future studies. Notably, the extent to which DNMT1 silencing alone and in combination with HIF1α/HIF2α elevated Spry2 protein is not significantly different  also contain putative HREs  was from Cayman Chemical. Laccaic acid A (LCA) was obtained from TCI America.All siRNAs and PCR primers, including general PCR primers, real time PCR primers and primers for methylation specific and non-methylation specific PCR, were synthesized by Integrated DNA Technologies Inc. The sequences of the primers are listed in Antibodies used for Western blotting and chromatin immunoprecipitation were from the following companies: Sprouty2 , HIF1α (BD Transduction Laboratories), HIF2α (R&D Systems), HIF1β (Santa Cruz Biotechnology), and DNMT1 (AbCam).Human full-length HIF1α is PCR amplified with primers carrying HindIII and NotI sites from HIF1α cDNA clone  and inserted in pcDNA3 at HindIII and NotI sites. HIF2α is PCR amplified with primers harboring BamHI and NotI sites from pOTB7-HIF2α (Thermo Scientific.) and inserted in pcDNA3 at the corresponding sites. Plasmid pcDNA3-HIF1β was kindly provided by Dr. Guo-Qiang Chen . Plasmid pGL2-Pfkfb3/-3566 was kindly provided by Dr. Ramon Bartrons, University of Barcelona.2 levels (21% O2) and 5% CO2 at 37°C. For hypoxic conditions, cells were maintained at 3% O2 and 5% CO2 in a Coy Hypoxic Chamber  at 37°C. All media used for hypoxia experiments were pre-equilibrated under hypoxic conditions overnight before use.Hep3B and HuH7 cells were obtained from Dr. Basabi Rana, University of Illinois, Chicago. HEK293T were incubated in DMEM supplemented with 10% FBS, penicillin (100 units/mL), and streptomycin (100μg/mL). Hep3B cells were incubated in MEM supplemented with non-essential amino acids, sodium pyruvate and HEPES in addition to 10% FBS, penicillin (100 units/mL), and streptomycin (100μg/mL). HuH7 cells were incubated in DMEM F12 1:1 supplemented with HEPES, 10% FBS, penicillin (100 units/mL), and streptomycin (100 μg/mL). For normoxic conditions, cells were maintained at ambient OSPRY2 mRNA stability, Hep3B cells treated with 3μg/mL actinomycin D after siRNA transfection and 24 h hypoxic exposure were lysed at the indicated times with Trizol for RNA extraction. To investigate the involvement of DNA methylation in the regulation of SPRY2 mRNA expression by HIFs, Hep3B cells were incubated with DNA methylation inhibitors, decitabine (DAC) at 5μM or laccaic acid A (LCA) at 50 μg/mL, for 24 h the day after cells were plated. Subsequently, cells were transfected with siRNAs in fresh medium containing DAC or LCA and then maintained under hypoxia for another 24 h before use.To examine whether HIFs alter 5 /dish and transfected next day with 250 ng each of pcDNA3-HIF1β, pcDNA3-HIF1α and/or pcDNA3-HIF2α as indicated using Transit2020 transfection reagent (Mirus) following the manufacturer’s instructions. The total amount of plasmids transfected into each dish was kept the same by adding empty vector pcDNA3. Cells were incubated under normoxic condition for 40 h after transfection before RNA extraction.HEK293T cells were seeded in 3.5-cm dishes at 2 x 105 /dish or HuH7 cells were plated in 3.5-cm dishes at 2 x 105/dish. Next day, cells were transfected with mutant siRNA or siRNAs against HIF1α, HIF2α or both at 20 nM each or for the experiments in 5'-GUC AGC AGA ACA AAA GUA GTT-3' and antisense 5'-CUA CUU UUG GUU CUG CUG ACT T-3'; HIF1α, sense 5’-GAA GGA ACC UGA UGC UUU AAC UUT G-3’ and antisense 5’-CAA AGU UAA AGC AUC AGG UUC CUU CUU-3’; HIF2α, sense 5'-GCU GGA GUA UGA AGA GCA AGC CUT C-3' and antisense 5'-GAA GGC UUG CUC UUC AUA CUC CAG CUG-3'.Hep3B cells were plated in 3.5-cm dishes at 3 x 10HIF1α, HIF2α, SPRY2 and PGK1, real time PCR was performed with specific primers and probes . The extracted total RNA (500 ng) was then converted to cDNA with SuperScript VILO cDNA synthesis kit (Invitrogen) according to manufacturer’s instructions. To detect mRNA amounts for d probes  and Fast5 /dish in 6-cm dishes. Next day, cells were transfected with siRNAs as stated above. An extra dish of cells were transfected in parallel with siRNA and trypsinized for cell counting before use. After a 32 h hypoxic incubation (3% O2), cells were crosslinked with 1% formaldehyde for 10 min at room temperature. The crosslinking reactions were terminated by incubating in 0.125 M glycine for 5 min at room temp. The cells were washed twice with cold PBS, scraped into cold PBS containing protease inhibitors  and pelleted by centrifugation at 2000 rpm for 5 min. The cell pellet was resuspended in SDS lysis buffer  containing the above protease inhibitors (200 ml/1 x 106) and incubated for 10 min on ice. The cell lysate was sonicated to shear DNA followed by centrifugation to remove pellet. The supernatant was diluted 10 times with dilution buffer  and pre-cleared with salmon sperm DNA/protein G beads. The cleared supernatant (from 1 x 106 cells) was incubated with 2.5μg anti-HIF1β antibody or rabbit IgG overnight at 4°C and immunoprecipitated with 25 μL protein G agarose beads the next day. For ChIP with anti-DNMT1 antibody, 1.5 x 106 cells were used per ChIP and mouse IgG was used as control antibody. The immunoprecipitates were washed sequentially with the following buffers: low salt buffer , high salt buffer , LiCl wash buffer , and TE . DNA was then eluted with elution buffer  and the crosslinking was reversed by adding 20 μl 5 M NaCl and incubated at 65°C overnight. After purification with PCR purification kit (Qiagen), the amount of DNA that was immunoprecipitated with a specific protein was quantified by real time PCR using the indicated primers  and SYBR master mix (Roche Life Sciences). The results are presented as % enrichment (% of the input DNA was immunoprecipitated with the indicated antibody).Hep3B cells were plated at 5 x 10SPRY2 gene was examined by PCR employing two sets of primers that match the same sites with one specific for methylated (M) and the other for unmethylated (U) sequences. The sequences of primers are listed in Genomic DNA was extracted from Hep3B cells using the DNeasy tissue extraction kit (Qiagen) following the manufacturer’s instructions. Subsequently, 0.5–1.0 μg of DNA from each sample was used for bisulphite conversion using the EpiTect fast bisulfite conversion kit (Qiagen). The converted DNA was then purified with the same kit from Qiagen. DNA methylation status of the One-way ANOVA was employed for multiple-group comparisons using GraphPad 6 software. For two-group comparison, Student’s t test was performed.S1 FigSPRY1, SPRY3, and SPRY4 from -4000 to the end of the coding sequence encompassing the promoter, transcription start site (+1), exon 1 (Ex1), intron, and exon 2 (Ex2) as well as intron 2 and exon 3 (Ex3) for SPRY1. Each colored rectangle labeled with a letter represents a putative HRE and the location of each HRE is labeled underneath.Schematic of (TIFF)Click here for additional data file.S1 TableSPRY2 promoter aligns with an HRE sequence in chimps, mice, rats, dogs, or dolphins.The table above indicates with an “X” if the putative HRE from the human (DOCX)Click here for additional data file.S2 TableSPRY2 promoter and “U’ designates a primer set that amplifies SPRY2 promoter that is not methylated. “F-n” indicates the nested forward primer that was used in the subsequent PCR following the first PCR with the forward and reserve primers listed as described under “Methylation-specific PCR” in the Experimental Procedures.The sequences for the primers and probes used in real time PCR are listed. The primers for chIP and methylation specific PCR’s are listed. For methylation-specific primers, “M” designates a primer set that amplifies methylated (DOCX)Click here for additional data file.


Dinoflagellates are of great importance to the marine ecosystem, yet scant details of how gene expression is regulated at the transcriptional level are available. Transcription is of interest in the context of the chromatin structure in the dinoflagellates as it shows many differences from more typical eukaryotic cells. Here we canvas recent transcriptome profiles to identify the molecular building blocks available for the construction of the transcriptional machinery and contrast these with those used by other systems. Dinoflagellates display a clear paucity of specific transcription factors, although surprisingly, the rest of the basic transcriptional machinery is not markedly different from what is found in the close relatives to the dinoflagellates. Lingulodinium polyedrum this nightly bioluminescence [L. polyedrum has been studied for over 60 years as a model system for addressing the biochemical links between the internal clock and the observed rhythms [Dinoflagellates are an important group of unicellular eukaryotes found in both marine and fresh water environments. These marine species are of particular importance on a global scale, as along with the diatoms, they contribute roughly half of the carbon fixed in the oceans, and thus roughly a quarter of the global totals . They alnescence , as wellnescence , cell dinescence , and diunescence , are all rhythms .Phylogenetically, dinoflagellates are grouped in the superphylum Alveolata, which contains apicomplexans as their closest relatives as well as ciliates . MembersThe mechanisms used to control the expression of different genes have been extensively researched in both prokaryotes and eukaryotes. Critical events in eukaryotes include changes in chromatin organization, transcription of DNA into pre-mRNA, splicing of pre-RNA into mature mRNA, mRNA transport, mRNA degradation, mRNA editing and covalent modifications of the mRNA, translation of mRNA into protein, and, lastly, post-translational modification of the protein. All these, either individually or collectively, are responsible for regulating gene expression within a cell. In this review, we will focus primarily on transcription and its regulation as they relate to the control of gene expression in the dinoflagellates, as more comprehensive studies on dinoflagellates have been published elsewhere ,13,14.Prorocentrum micans was inspected using high resolution electron microscope autoradiography for 3H-adenine incorporation, and this revealed that RNA transcription was prevalent only on extrachromosomal DNA filaments and not on DNA within the main body of the chromosome [Dinoflagellate chromosomes are permanently condensed at all stages of the cell cycle  and assuromosome . It was romosome .trans-acting factors and a series of conserved cis-acting sequences, as is the case in other eukaryotes. The complex of trans-acting factors binding the regulatory sequences in the DNA includes, in addition to the RNA polymerases, both general and gene-specific transcription factors, activators and mediators [cis-acting sequences in eukaryotes can include regulatory elements far from the transcription start site, termed enhancers, although the region just upstream of the start site, termed a promoter, consisting of a core region and other regulatory domains [Pyrocystis lunula luciferase (lcf) genes, a GC box consensus sequence <GGGCGG> is present, but its location is further upstream than the usual position of −110  found in many eukaryotes [P. lunula lcf A and L. polyedrum lcf and lbp genes, but its position was not fixed. This GC-rich motif was first reported in the upstream region of the Peridinium bipes ferredoxin gene [Acanthamoeba), slime molds (Dictyostelium), ciliates (Histriculus cavicola), and apicomplexans (Plasmodium) [Given access to the genetic material, transcription initiation in dinoflagellates is likely to require an elaborate set of ediators . The cis domains ,21 is co domains  as theirkaryotes . Furtherxin gene . Howeversmodium) ,28,29,30smodium) ,32,33.L. polyedrum has multiple copies of peridinin-chlorophyll a-binding protein (pcp), luciferin binding protein (lbp) and luciferase (lcf) genes arranged in long tandem repeats [Pyrocystis lunula genomic DNA revealed that, among lcfA, lcfB and lcfC isoforms, two (lcfA and B) are in tandem repeat. However, the sequence of the intergenic region between lcf and pcp coding sequences of the L. polyedrum lacks any known promoter elements. The only common feature between the two was a conserved 13 nucleotide sequence, CGTGAACGCAGTG, proposed as a dinoflagellate specific promoter sequence [P. lunula lcfA and lcfB genes [Amphidinium carterae [Proper understanding of gene organization and structure is required to describe transcription in dinoflagellates. For example,  repeats ,35,36,37B genes . To testcarterae . PCR usiTrypanosoma gene structure [trans splicing of the SL leader at the 5′ end and by polyadenylation at the 3′ end. If true for dinoflagellates, one possibility would place a promoter upstream of each tandem array, thus explaining the lack of recognizable promoter sequences in the intergenic regions. However, the consequences of this hypothesis include the predictions that the intergenic spacer region should be abundant in the transcribed RNAs, and that sequence differences between copies in low copy number arrays should be detected in the mature transcripts at a frequency inversely proportional to the copy number. In a recent transcriptomic study that addressed this issue, none of these predictions were validated experimentally [The lack of identifiable sequence elements in the intergenic spacers has lead to the suggestion that tandem gene repeats may form a polycistronic transcript, in a manner similar to the tructure . The trymentally .Crypthecodinium cohnii, carried out with radiolabeled UTP, revealed that considerable amounts of RNA polymerase activity remained even after inhibition by α-amanitin, a potent inhibitor of RNAP II. This thus confirmed the presence of multiple forms of DNA dependent RNA polymerase as in other eukaryotes [+2, instead of the activation of these enzymes seen in other eukaryotes. It was suggested that dinoflagellate RNAP II activity might differ slightly from the other eukaryotic RNAP II enzymes [L. polyedrum contains a complete set of core and common elements for all the three eukaryotic RNAPs. Furthermore, the specific elements absent from the transcriptome were also missing in other members of the Alveolata  are used for the former while only one is used for the latter. The three eukaryotic enzymes have specialized functions, with RNAP I transcribing most ribosomal RNA (rRNA), RNAP II transcribing protein-coding messengers (mRNA), small nuclear RNAs (snRNA) and micro RNA (miRNA), and RNAP III synthesizing transfer RNAs (tRNA) and the 5S rRNA. An assessment of the activity of RNA polymerase in the dinoflagellate karyotes . Curious enzymes , perhaps enzymes . Howeverlveolata . It seemin vitro reconstitution of a functional eukaryotic transcriptional apparatus requires a suite of other basal/general transcriptional factors (TF) [C. cohnii has been shown to contain a TBP-like factor (TLF), clearly homologous to TBP yet lacking the four phenylalanine residues known to interact with the TATA box. This TLF is unique to dinoflagellates  . Six mulors (TF) ,47,48,49ors (TF) ,51. TBP ors (TF) , althougors (TF) ,54. Thesors (TF) . Interesgellates  and has L. polyedrum transcriptome contains two TLF isoforms similar to the TLF found in C. cohnii and, somewhat surprisingly, no TBP at all [L. polyedrum also lacks most other TAFs, although the closely related Alexandrium expresses two proteins with DNA helicase activity, RuvB-like1 and RuvB-like2 [L. polyedrum lacks any TFIIA, TFIIB, TFIIE or TFIIF components, and only 3 out of the ten expected TFIIH components are found . It must be noted, however, that ciliate, apicomplexan and diatom genomes contain a single TBP and also lack the TAFs and TFs missing in L. polyedrum [L. polyedrum is commensurate with the other related eukaryotes. These properties thus seem more likely to be due to a reduced dependence on these TFs throughout the Alveolata than to the unusual nature of the dinoflagellate chromatin.The P at all . The phyvB-like2 . RuvB-livB-like2 , suggestolyedrum . A figurL. polyedrum transcriptome.Histones are the most abundant and conserved class of basic proteins in the DNA-binding protein class of eukaryotes, and can profoundly affect transcription rates by their ability to alter the degree of chromatin condensation. The classic nucleosome structure, observed microscopically as “beads on a string”, forms when 146 bp of DNA wraps 1.65 times around the histone octamer  ,61. A fiL. polyedrum [. However, the presence of all the core histone sequences in the transcriptome of two dinoflagellate species, the high sequence conservation of these sequences compared to other eukaryotic histones, and the presence of a wide range of histone modifying enzymes in the L. polyedrum transcriptome all suggest that histone proteins are indeed expressed [Although metatranscriptomic analysis with the DinoSL found core histone sequences that were scattered in different dinoflagellate species , the preolyedrum . Howeverxpressed ,71, albeC. cohnii and later renamed HCc 1–4 [C. cohnii HLP revealed that L. polyedrum also has an HLP, which was named HLp [in vivo [Hematodinium, can bind DNA as efficiently as histones and can also be post-translationally modified [Hematodinium, as well as in a family of large algal virus, the Phycodnaviridae. However, DVNP is not found in Perkinsus, the common ancestor of dinoflagellates and apicomplexans, which has instead the typical eukaryotic chromatin with all core histone proteins and DNA arranged into nucleosomes [Hematodinium and the main dinoflagellate lineages from Perkinsus, and thus appears to coincide with the appearance of the unusual core dinoflagellate nuclear morphology. In addition, a substantial proportion of the DNA appears to consist of repeated sequences, and it is possible that this may contribute to genome organization [The total amount of basic proteins in dinoflagellate nuclei (basic protein to DNA ratio of 1:10 ) is much HCc 1–4 ,76. Blasamed HLp , and thi[in vivo . The pre[in vivo . A seconmodified . DVNP isleosomes . The acqnization .Amphidinium carterae, produced in situ by microencapsulation in agarose and sequential extraction coupled with immunoblotting, revealed the presence of two matrix proteins (lamins and topoisomerase II) similar to what is found in higher eukaryotes [The nuclear matrix is a network of fibers in the nucleus that also plays a key role in the functional and structural organization of the chromatin. Electron microscopy studies of nuclear matrices in the dinoflagellate karyotes . The lamkaryotes . They hakaryotes ,84. ThusC. cohnii. Dinap1 does not have any known homologues but does contain two zinc finger domains  and two WW domains (known to interact with proline-rich domains) [C. cohnii cDNA library with a tagged Dip1 retrieved not only the expected Dinap1 but also other interactants, named DAP (Dip1-associated proteins) [Alexandrium, although this protein has not been fully characterized.In pursuit of sequence-specific DNA binding proteins , a dinoflagellate nuclear associated protein (Dinap1) was found in domains) . An intedomains) , and scrroteins) . Dinap1,roteins) , althougroteins) , a grouproteins)  has beenLingulodinium and Symbiodinium [bone fide DNA-binding proteins, and the reason for the preferential expansion of this domain in dinoflagellates, remains to be discovered. However, there is a caveat to assuming that dinoflagellates are bereft of most DNA binding domains based on gene sequence data. Apicomplexans were initially also thought to have a low number of DNA binding proteins, yet further research revealed the expansion of a unique family of transcription factors, ApiAP2, in these organisms [Gene specific transcription factors (TFs) are one of the largest family of proteins in most cells, accounting for ~4% of the genome in yeast or ~8% of the genome in plants and mammals . In contiodinium ,56. Furtiodinium . Whetherrganisms . An as yMethylation of cytosine in the DNA is a well-studied epigenetic modification that plays an important role in several cellular processes such as retrotransposon silencing, genomic imprinting, X-chromosome inactivation, regulation of gene expression, and maintenance of epigenetic memory . CytosinPyrocystis lunula where HLP transcripts peaked during the S-phase [Alexandrium fundyense where HLP transcripts were up-regulated during G1 phase [L. polyedrum [The posttranslational modification of histones plays an important role in regulating gene expression in other eukaryotes, and deserves re-examination in dinoflagellates because of the recent discovery that conserved sequences for core histones and their regulatory enzymes appear in the transcriptomes ,71. It i S-phase , and AleG1 phase . Howeverolyedrum  to see iAmphidinium carterae, Northern blot hybridization revealed that transcript levels of two light harvesting proteins, peridinin chlorophyll a protein (PCP) and a major a/c-containing intrinsic light-harvesting proteins (LHC), were, respectively, 86- and 6-fold more abundant under low light conditions than under normal light conditions [in vitro experiments to link DNA demethylation with transcriptional activation were unsuccessful [Karenia brevis may also have a transcriptional response to low light, as the abundance of 9.8% of the 4269 unique genes in the microarray differed between day and night [Symbiodinium bermudense that result in increased levels of superoxide radicals and hydrogen peroxide [hsp) genes in Symbiodinium residing inside its coral host Acropora millepora, qPCR was used with samples that were subjected to elevated temperatures rapidly or gradually [hsp70 transcript levels increased from 39% to 57% when temperature increased to 26 °C (moderate) or 29 °C (severe), although when cells were exposed to extreme heat stress hsp70 transcript levels decreased by up to 70%. Curiously, hsp90 transcript levels always decreased under heat stress and were independent of the speed of the temperature increase [Most organisms have evolved an ability to respond to environmental changes, including biotic and abiotic stresses such as changes in light or temperature. The signaling pathways involve receptors that sense and transmit the information to regulatory molecules, and changes in gene expression are a frequently observed cellular response . For exanditions . Interesccessful . Kareniand night . In addiperoxide , and thiperoxide . To checradually . Dinoflaincrease . L. polyedrum, metal-induced oxidative stress resulted in sharp increases in the activity of the defense enzyme superoxide dismutase [P. lunula revealed that 204 and 37 genes increased in abundance by 2- to 4-fold after treatment with 1 mM sodium nitrite or 0.5 mM paraquat, respectively [hsp70 and hsp90, to elevated temperature, metal and endocrine disrupting chemicals, were tested in the dinoflagellate Prorocentrum minimum. RT-PCR results revealed that Hsp70 transcripts increased in response to each of these stresses, while Hsp90 transcript level increased only in response to temperature and metals [Oxyrrhis marina, revealed 9 and 21 transcripts to be up- and down-regulated by saline stress, respectively [Oxidative stress is often able to induce a transcriptional response in organisms. In ismutase , with thismutase ,107. Thiismutase . Similarectively . The trad metals ,111. Lasectively . HoweverNeurospora, 10% in Arabidopsis, 5%–10% in mice and 30%–65% in the cyanobacteria Synechococcus elongates [P. lunula, 3% of the genes on a microarray were found to exhibit changes in transcript abundance (between 2- and 2.5-fold) [K. brevis 0.7% of the genes varied in both light/dark and constant light (between 2- and 7-fold) [32P incorporation of ribosomal RNAs in the stationary phase cells of L. polyedrum under constant light, followed by subsequent gel electrophoresis of the labeled RNAs, showed circadian rhythmicity with maximum RNA abundance at CT18 [L. polyedrum cells were treated with Actinomycin D (ActD), a drug that inhibits DNA-dependent RNA synthesis, the bioluminescence and photosynthesis rhythms were unaffected for 30 h or more depending on the dose of the treatment [d-ribofuranosylbenzimidazole) and α-amanitin confirmed no significant effect on growth, luminescence or rhythmicity in L. polyedrum cultures [L. polyedrum have so far proven to be regulated post-transcriptionally [The circadian (daily) clock is an endogenous timer that regulates daily rhythms in organisms from all walks of life ,115,116,longates ,122. In .5-fold)  while in 7-fold) . The flu at CT18 , the tim at CT18 ,126. Howreatment . In contreatment . As ActDcultures . Indeed,tionally .Karenia grown in N-deplete and -replete conditions were compared, 1102 genes on a microarray chip of 11,000 genes were found to be differentially expressed [K. brevis and A. carterae [Alexandrium tamarense, suggesting that expression of genes involved in these pathways may be responsive to nutrients [Alexandrium minutum identified 87 genes that specifically responded to N or P limitation [A. tamarense cultures showed only 2 and 12 out of a total of 40,029 signatures were uniquely expressed under N and P starvation, respectively [Nutrient availability is also an important environmental cue, and can result in the formation of algal blooms for some dinoflagellates. The nutrients most important for the blooms are nitrogen (N) and phosphorus (P), and thus the transcriptomic response of dinoflagellates to N- and P-deplete and -replete conditions has been of great interest. When xpressed . Among tcarterae ,131. Intutrients . Microarmitation , while mectively .A. tamarense discussed above, 489 of the 4298 sequences examined were found to be differentially expressed when exponentially growing and stationary phase cultures were compared, a number even higher than the response induced by nutrient deprivation [A. catenella revealed proliferating cells show over-expression of transcripts from several categories, including transcription and RNA processing, protein synthesis and translational regulation, cell division, transport related, photosynthesis and cellular metabolism [Karenia brevis, five time points representing different growth phases were selected for microarray analysis, and taken together, 21% of the 11,000 features examined had accumulated to different levels in logarithmic compared to stationary phase cells [A. minutum has indicated a strain specific regulation of gene expression [Alexandrium, it is unclear how much reliance can be placed on this line of experiments as many toxin related genes could also have unknown and important metabolic functions in the dinoflagellates and thus be similarly regulate in both strains. This view is supported by the observation that a non-toxic strain of Heterocapsa circularisquama transcribes a substantial number of genes thought to be involved in toxin biosynthesis [L. polyedrum [Prorocentrum donghaiense [The strain and growth stage of dinoflagellate cultures can also affect gene expression. In the microarray study of rivation . Here, privation . Similartabolism . In Karese cells . Interespression . Using mynthesis . Lastly,olyedrum  while a ghaiense .A. tamarense grown axenically and in normal cultures [Scrippsiella nutricula with and without its radiolarian host Thalassicola nucleata. It was found that several genes in the dinoflagellate were differentially transcribed depending on symbiotic or free living growth [+-ATPase gene in Symbiodinium was shown to be expressed exclusively during the coral symbiosis [Calanushel golandicus, Acartia clausii, and Oithona similis) were found to induce a species-specific response of toxin production by the dinoflagellate Alexandrium, and this was associated with the significant and specific regulation of particular sets of genes, especially those involved in signal transduction, translational and post translational mechanisms [Gene expression in the dinoflagellates can also be influenced by biotic factors, as shown by a massively parallel signature sequencing MPSS comparison of cultures . From a g growth . The dinymbiosis . Thermalymbiosis . Lastly,chanisms .L. polyedrum have been measured [It must be kept in mind that most of the gene regulation studies performed in dinoflagellates are expression-profiling experiments, which indicate mRNA levels and are thus determined by the balance between mRNA synthesis and degradation rates. Indeed, mRNA degradation may play a major role in determining the transcript abundance . So far,measured . Thus, dL. polyedrum, such as pcp, lbp and lcf, lack introns [P. lunula, a comparison of genomic and cDNA PCR products of the lcf C gene identified a 403 bp intron [Prorocentrum minimum [Symbiodinium [sxtG in Alexandrium was found to have one intron whose length varied from species to species, ranging from 260 to 750 bp. Sequencing of different sxtG introns showed >90% intraspecies identity and <80% interspecies identity, with no variation observed within a strain [Peridinium willei, Polarella glacialis and Thecadiniium yashimaense, respectively) [. A more detailed test, carried out with 31 genes in A. carterae, showed that four genes  had 6 or more introns, similar to other eukaryotes, another 11 genes had less than 5 introns, and the rest no introns at all [Several posttranscriptional modifications in the primary transcripts of eukaryotic cells are necessary to create a mature mRNA that can be efficiently translated, and of these, arguably the most important is the removal of the intervening sequences, or “introns”, that interrupt the coding sequence, or “exons” ,146,147. introns ,35,37. Hp intron . The for minimum , yet coniodinium . The saxa strain . Analysectively) . A more s at all . This sts at all .lcf C of P. lunula [Symbiodinium rubisco [Alexandrium sxtG [The cellular mechanism that joins exons together by excising the introns is called splicing ,147. As . lunula , the G in conjunction with cytochemical staining for RNA, phosphorylated proteins and DNA [The splice sites in pre-mRNA introns are recognized by base pairing to short RNA molecules  termed small nuclear RNAs (snRNA), each of which is bound to a complex of proteins to form small nuclear ribonucleoproteins (snRNPs). These five snRNPs, together with numerous non-snRNP proteins, constitute the spliceosome, a dynamic complex that forms and reforms repeatedly to process pre-mRNAs to mature transcripts . Many ofi snRNPs . In addiectively ,56. A hiectively . Furtherectively . Intrigu and DNA . These s and DNA  raising cis-splicing events in dinoflagellates, trans-splicing is now known to be pervasive [Trypanosoma brucei, where mRNAs were found to contain a consensus sequence of 39 nucleotides (nt) at their 5′ ends. This sequence, termed a spliced leader (SL) sequence [trans splicing to all trypanosome mRNAs [trans-splicing [Ciona intestinalis [Stylochus zebra [trans-splicing is absent in organelle-encoded transcripts, although a unique type of trans-splicing was recently found in the mitochondria of diverse dinoflagellates. The mitochondrial cox3 gene is encoded in two pieces that are transcribed separately then trans-spliced to form a complete coding cox3 mRNA [trans-splicing is evolutionarily ancient for the dinoflagellates, also being found in the perkinsozoa, Perkinsus marinus is basal to the dinoflagellate and apicomplexans lineages, and has nuclear-encoded transcripts with 5 different SL sequences. Three of the SL are 22 nt long and similar to the core dinoflagellates (SL1) while the other two are truncated 21 nt SL with either A or G as the starting nucleotide (SL2) [trans-splicing is not clear. It is unlikely to be involved in mRNA stability or translation, as there was no difference in translation efficiency or stability between trans-spliced and non-trans-spliced nematodes mRNAs [Despite the paucity of ervasive . In thissequence , is addeme mRNAs . Since tsplicing ,159,160.stinalis  to 51 ntus zebra , and in us zebra . The disus zebra . The dinus zebra . SL tranox3 mRNA . SL trande (SL2) . The funes mRNAs .Perkinsus marinus [The paucity of introns, as well as the presence of multiple relict sequences related to the SL in the 5′ ends of dinoflagellate genes isolated from genomic DNA, has led to the proposal of a mRNA recycling mechanism whereby mature mRNAs are inserted back into the genome through a recombination process . This hy marinus . AlternaL. polyedrum transcriptome to try and retrieve the components expected for RNA transport. There are three general classes of proteins required, those forming the nuclear pore itself and those soluble in either the nucleus or the cytoplasm. Compared to the components found in other eukaryotes, the most marked difference between the alveolates and other organisms appears to lie in those components used for construction of the pore  are enormous protein complexes, ranging from 50 MDa in yeast to 125 MDa in mammals, which are present within the nuclear envelope and mediate nucleo-cytoplasmic transport ,168. Thothe pore . Apart fransport , and theveolates .Eukaryotes also employ a multistep “quality control” or surveillance pathway to selectively degrade the damaged or mutated mRNAs as a protective mechanism against aberrant protein synthesis. This concerted procedure starts with mRNA capping during transcription within the nucleus, and ends in the cytoplasm with the degradation of abnormal mRNAs. There are three main pathways, the first being nonsense-mediated mRNA decay. In mammals, this pathway interprets stop codons found 50 or more nucleotides upstream form the last exon boundary to be premature stop codons, principally because normal stop codon are typically located in the last exon ,173 and Considerable progress has been made in the study of dinoflagellate transcription, fuelled in large part by the recent availability of low cost sequencing. We show here that most of the expected players in the transcriptional machinery are found in dinoflagellates, at least with respect to their counterparts among the Alveolata. The exception to this general rule is that the specific transcription factors seem in large part to be reduced in quantity and type in the dinoflagellates. Thus, while general transcription carries on much as expected for the eukaryotes, the specific targeting of genes for transcriptional control may differ as a result of the unusual chromatin organization in this class. Further studies will now be necessary to confirm the biochemical activities of some of the more interesting components identified from the massive influx of sequence information.