Here, we review the main mechanisms of telomerase activation and the associated hematologic malignancies.Telomerase expression and telomere maintenance are critical for cell proliferation and survival, and they play important roles in development and cancer, including hematological malignancies. Transcriptional regulation of the rate-limiting subunit of human telomerase reverse transcriptase gen ( The ends of all linear genomes are comprised of a unique and genetically stable structure, termed telomere, which preserves genome integrity ,2. Due tTelomerase consists of two core components: a catalytic subunit, human telomerase reverse transcriptase (hTERT) with reverse transcriptase activity and an RNA component, human telomerase RNA component (hTR), used as a template for the elongation of telomeres. In vivo telomerase activity requires additional components that associate with hTERT and hTR to form the holoenzyme . SomatichTERT expression is transcriptionally shut-off in somatic cells, but the other telomerase associated components are constitutively expressed in most mammalian cell types; expression of hTERT mRNA in somatic cells is sufficient to reconstitute telomerase activity; and the expression levels of hTERT show strong correlation with telomerase activity [It is believed that the limiting factor for telomerase activity is the level of hTERT . Corroboactivity ,15,16. hTERT is primarily determined by the transcriptional activity of the hTERT gene promoter. The hTERT promoter does not have typical transcription regulatory elements like TATA and CAAT boxes, but it contains a number of binding sites for multiple important transcription factors, which integrate hTERT transcriptional responses with many important pathways that are deregulated in various tumor types [hTERT promoter expression. In contrast, Mad, histone deacetylases, E2F1, transforming growth factor-β-activated kinase 1 (TAK1), Wilms' tumor 1 (WT1), p53, mothers against decapentaplegic homolog (Smad3), and Menin signaling negatively regulate hTERT promoter expression. [hTERT expression [hTERT gene has a GC rich promoter and may therefore be under epigenetic regulation [hTERT promoter triggers the recruitment of histone acetyltransferase (HAT) activity, allowing hTERT transcription [hTERT transcription start site, results in telomerase expression [hTERT transactivation: several viruses or virus proteins that interact with telomerase are known to be involved in tumorigenesis of infected tissues [The expression of or types . Transcrression. . Even ifpression . The hTEgulation ,21. DNA cription . It is apression . There a tissues . Since t tissues . This rehTERT expression and telomerase activity are increased in both virus-driven and virus-unrelated lymphoproliferative disorders, telomeres are generally short in virus-unrelated malignancies, and several data suggest that virus-associated tumors and/or pre-neoplastic disorders are characterized by longer telomeres [hTERT that may contribute to a delay in replicative senescence and prolonged time to acquire genetic alterations critical for the induction of a fully transformed phenotype [hTERT may thus occur as a subsequent step, necessary for the immortalization of cells with acquired oncogenic potential. Accordingly, in adult T-cell leukemia/lymphoma (ATLL), telomerase activity appears as a key event in the development and progression of the disease, whereas in acute myeloid leukemia (AML), in chronic myeloid leukemia (CML) and in B-cell diseases, it was demonstrated that telomerase activity is not required for the initiation of disease, but it is required for its maintenance [While elomeres ,26,27. Telomeres . On one henotype . On the ntenance ,30,31,32ntenance . In addintenance ,34,35,36hTERT promoter may regulate hTERT transcription on specific cell type and physiological conditions, none of them are sufficient on their own to promote immortalization of somatic cells [Although the transcription factors known to bind to ic cells .hTERT gene is frequently amplified in human tumors, including hematological malignancies [hTERT promoter, suggesting that chromosomal rearrangements could either relieve the promoter from its stringent repressive epigenetic environment or place it in the proximity of enhancers at different chromosomal sites [hTERT gene is rarely but recurrently targeted by somatic chromosomal translocations to immunoglobulin heavy (IGH) and non-IG loci in B-cell neoplasms, including acute lymphoblastic leukemia, chronic lymphocytic leukemia, mantle cell lymphoma and splenic marginal zone lymphoma. In addition, tumors bearing chromosomal aberrations involving hTERT showed higher TERT transcriptional expression and increased telomerase activity [The gnancies . In mostal sites ,40. The activity ,42.hTERT gene are unlikely to yield a sufficient amount of the hTERT transcript, so the marked activation of hTERT transcription during tumorigenesis may be a combination of gene amplifications with other genetic or epigenetic mechanisms [Multiple copies of the chanisms .Epigenetic modifications imply reversible changes in the genome of cells without any alteration in the DNA sequence. Increasing evidence suggests the epigenetics as an important mechanism involved in cancer initiation, progression, treatment and prognosis. There are three major epigenetic mechanisms that are known to regulate gene transcription in carcinogenesis: modified DNA methylations, histone modifications, and deregulated microRNA (miRNA) expression .hTERT gene promoter is a determinant for the control of telomerase activity, and it has been shown that epigenetic modulation may repress hTERT transcription in hematological malignancies and may provide an additional level of enzyme regulation [The epigenetic plasticity of the gulation .hTERT promoter, hTERT gene expression and telomerase activity [There are conflicting studies regarding the correlation between hypermethylation of the activity ,46. hTERT promoter methylation status defines specific ALL subgroups [hTERT expression goes along with hTERT promoter hypermethylation [hTERT gene to be transcribed [hTERT regulation. Leukemias and lymphomas, including B cell chronic lymphocytic leukemia (CLL), express high levels of telomerase but exhibit low levels of hTERT promoter methylation [hTERT promoters [hTERT is targeted by paired box 5 (PAX5), a B cell-specific factor, which is sufficient to activate TERT expression [Regarding hematological malignancies, in a cohort of childhood acute lymphoblastic leukemia (ALL), it was reported that the tumor samples had a methylated promoter, and that the ubgroups . In addihylation . It is bnscribed . On the hylation . Moreoveromoters ,51. In tpression .hTERT promoter. Indeed, it was observed that a small region around the transcription start site has little or no methylation, while there is a densely methylated region 600 base pairs upstream the transcription start site [hTERT transcription in tumor cells, while the hTERT promoter in many normal cells and tissues is either unmethylated or hypomethylated, indicating that hTERT silencing does not require extensive CpG methylation at its promoter [hTERT gene expression and telomerase activity [It is believed that the unusual correlations between DNA methylation and expression in cancer cells may, in part, result from the varied methods used to study differing regions of the art site . The corpromoter . In addiactivity ,53,54. Tactivity . hTERT transcription is histone modification that includes histone acetylation, methylation, phosphorylation and ubiquitination. Histone deacetylation/methylation, in particular, have been reported to be responsible for the repressive status of the hTERT promoter [Another prevalent epigenetic mechanism that affects promoter . hTERT gene, as the induction of hTERT transcription and telomerase activity in some telomerase-negative cells, was observed upon a treatment with trichostatin A (TSA), a histone deacetylase (HDAC) inhibitor [hTERT transcription impairment was reported. TSA has an antiproliferative and apoptosis inducing effect on the human leukemic cell line U937, associated with the inhibition of hTERT expression and telomerase activity [hTERT promoter DNA methylation and histone deacetylation status may contribute to the transcriptional repression of the hTERT gene and associated cell differentiation induction, observed during all trans retinoic acid (ATRA) treatment [hTERT promoter, determines the retinoid capacity to repress telomerase in maturation resistant acute promyelocytic leukemia cells during cellular differentiation [The native chromatin environment is critical for the tight regulation of the nhibitor ,58. The nhibitor ,60. HDACnhibitor . Modest nhibitor . Regardiactivity . In leukreatment ,64. Furtntiation . BCR-ABL fusion gene, the cytogenetic hallmark of CML [Imatinib (IM) is a tyrosine kinase inhibitor selective for the k of CML . IM admik of CML ,67. IM rk of CML ,69.hTERT regulation. SMYD3, a histone methyltransferase (HMTase), is capable to induce hTERT transcription and telomerase activity in normal human fibroblasts and cancer cell lines through histone H3 K4 trimethylation [hTERT gene is initiated [Histone methylation also plays a role in hylation . H3-K4 mnitiated . MiRNAs are a family of 19–24 nucleotide non-protein-coding RNA molecules that regulate the stability and translation of target mRNAs . VarioushTERT expression through a regulatory network which is interconnected with other pathways also involved in tumor development. The miRNAs that target the hTERT 3′UTR have been identified as tumorigenesis inhibitors, and, consequently, are commonly found downregulated in many types of cancer [hTERT, suggesting a tumor suppressor function role for miR-196b [Besides the effort to identify and catalog aberrantly expressed miRNAs in disease, very little is known about the functional consequences of miRNA dysregulation. It has been demonstrated that miRNAs are implicated in the regulation of f cancer . The funmiR-196b .Among all the factors regulating telomerase expression and activity, a few polymorphisms and mutations were also identified.hTERT locus, including the promoter and downstream introns, may be an alternative or additional mechanism influencing enzyme’s expression and activity. The genetic variability in the hTERT genomic region may affect telomerase function and can modulate telomere length and contribute to the development of cancer as well as the outcome of chemotherapy [TERT promoter polymorphisms associated with increased risk of developing hematological diseases, and even suggested as prognostic markers of survival [The presence of single nucleotide variants (SNVs) in the otherapy ,82. Thersurvival ,84.hTERT transcription activation, the TERT promoter region SNP rs2735940 was associated with risk of childhood ALL. The rs2735940 T allele increased the levels of the TERT mRNA compared with the C allele [hTERT regulation was also demonstrated via MNS16A polymorphism in patients with Non-Hodgkin Lymphoma (NHL) [TERT gene and upstream of the putative promoter region of an antisense TERT transcript, has promoter activity depending on the number of tandem repeats. Carriers of the MNS16A short (S) allele display higher telomerase activity than the long/long (LL) genotype carriers. In fact, longer alleles at MNS16A exhibit stronger promoter activity compared to the shorter alleles, but this leads to increased expression of antisense TERT mRNA with a conceivable, or at least partial, silencing of the sense telomerase transcript [Regarding C allele . The rolma (NHL) . The polanscript .hTERT or hTR might increase the risk of chemotherapy resistance and predisposal to specific human diseases, like bone marrow failure or dyskeratosis congenita and acquired aplastic anemia, diseases that predispose to MDS and AML [Clinically, loss-of-function mutations in  and AML ,88,89. T and AML ,91. hTERT mutations and poor prognosis [hTERT gene implicated as risk factors for AML [Analysis of MDS/AML cases, secondary to bone marrow failure or dyskeratosis congenita allowed the establishment of an association between rognosis ,93. In a for AML ,95.TERT promoter,  were reported in several different solid tumors [TERT gene [Recently, two hot spot mutations in the d tumors ,97. Thesd tumors ,97,98,99ERT gene ,97,100.Viruses involved in lymphomagenesis may directly up-regulate telomerase expression and activity ,101,102.hTERT expression [hTERT promoter in proliferating cells, while it activates it in quiescent cells, allowing the cell cycle progression [hTERT expression and telomerase activity. Additionally, the viral protein HTLV-1 basic leucine zipper (HBZ) expressed in ATLL cells increasese transcriptional activity of JunD, an AP-1 protein, while, HBZ in association with JunD activates the hTERT promoter [hTERT promoter in HTLV-1 transformed cells. Activation of the PI3K pathway mediates cytoplasmic sequester of the WT1 protein, a strong hTERT promoter suppressor [Infection with the human T-lymphotropic virus type I (HTLV-I) is associated with the development of an aggressive form of T-cell leukemia known as adult T-cell leukemia/lymphoma (ATLL) . High tepression . Indeed,gression . Notablypromoter . Furtherppressor . hTERT expression and activity [LMP-1 activates TERT at the transcriptional level via NF-kB and  MAPK/ERK1/2 pathways [Epstein-Barr virus (EBV) is involved in the pathogenesis of several lymphoproliferative disorders, including Burkitt’s and Hodgkin’s lymphomas, post-transplant lymphoproliferations, and a subset of T/natural killer (NK) cell lymphomas . Among Eactivity . LMP-1 apathways .hTERT gene is a very complex process. The repressed hTERT promoter can be activated by multiple mechanisms in different hematological malignancies. In addition to a variety of transcription factors that bind and promote hTERT transcription/inhibition, the chromatin environment and nucleosomal conformation appear to be among the major mechanisms that tightly regulate the hTERT gene in the majority of hematological malignancies. Through epigenetic modulation, the hTERT locus is able to adopt a decondensed state, and then allow the binding of sequence-specific transcription factors that will activate its transcription. Chromosomal translocations of the hTERT locus may, in fact, be an important mechanism of telomerase activation, as it allows the escape of the promoter from its native repressive chromatin environment. Amplification of the hTERT gene was reported in hematological malignancies, and combined with other genetic or epigenetic mechanisms, results in a marked activation of hTERT transcription during tumorigenesis. In virus-driven lymphoid malignancies, the hTERT promoter may also be activated directly by viral proteins.The regulation of the


Metabolism of messenger RNAs (mRNAs) consists of multiple steps, from transcription, through splicing, export to the cytoplasm, localization, translation to proteins and, finally, degradation. These steps, which are crucial to ensure correct genetic expression, have long been considered as separate events occurring at distinct time points and different locales. Recent studies suggest that they are not only interconnected, but might also be coupled to the initial process - transcription.Initial studies in the field showed that the occurrence of exon inclusion and intron retention could be altered in HEK293 cells with “slow” and “fast” RNA Polymerase II (RNAPII) mutants, suggesting that the rate of transcriptional elongation is crucial for the appropriate splice form  Figure . AnotherAs splicing and export could occur co-transcriptionally, they might be directly affected by the dynamics of transcription. However, how post-transcriptional processes - such as degradation and translation - could be coupled to transcription? When a single-molecule mRNA decay study measured stabilities of two mitotic mRNAs, SWI5 and CLB2 in yeast, they found that the precise control of their cytoplasmic decay is largely regulated by their promoters via co-transcriptional binding of a co-factor, Dbf2p . SimilarRecently, we discovered a direct genome-wide link between transcription and translation in mammalian cells . While t6A), in coordinating the two processes [6A-regulatory factors, both “writers” and “readers”, we observed a striking positive effect on the TE of mRNA that was characterized by slow transcription rates. Direct immunoprecipitation of m6A-modified mRNAs demonstrated significant difference between the methylation levels of the repressed and induced transcripts, suggesting that mRNAs that are “repressed” , have higher m6A content. This, in turn, represses TE, therefore linking inefficient transcription to inefficient translation. Finally, by artificial slow-down of RNAPII dynamics, we showed that the process of m6A modification on mRNA is likely to be co-transcriptional.To study how this link is maintained, we examined a possible role of a specific RNA modification, N6-methyladenosine  is expected to become much clearer in the near future. The possible applications of RNA modifications, including drug development targeting m6A machineries and thus altering the epigenetic environment, could open up new avenues to a better and more effective diagnosis and treatment of human diseases stemming from imbalanced gene expression.mRNAs are modified by a myriad of epigenetic modifications of which little functional knowledge is present. The functional investigation of the role of these RNA modifications is just emerging, and is expected to increase in volume in the coming few years. With the increasing knowledge of m


Drosophila neural development. We demonstrate that the majority of genes activated during neuronal differentiation are silent in neural stem cells (NSCs) and occupy black chromatin and a TrxG-repressive state. In neurons, almost all key NSC genes are switched off via HP1-mediated repression. PcG-mediated repression does not play a significant role in regulating these genes, but instead regulates lineage-specific transcription factors that control spatial and temporal patterning in the brain. Combined, our data suggest that forms of chromatin other than canonical PcG/TrxG transitions take over key roles during neural development.A key question in developmental biology is how cellular differentiation is controlled during development. While transitions between trithorax-group (TrxG) and polycomb-group (PcG) chromatin states are vital for the differentiation of ES cells to multipotent stem cells, little is known regarding the role of chromatin states during development of the brain. Here we show that large-scale chromatin remodelling occurs during  Drosophila. Here, the authors investigate the large scale chromatin remodelling taking place during fly neural development.While transitions between active and repressive chromatin states are essential for differentiation, little is known regarding their role during development of the brain in  Drosophila, the majority of neural stem cells (type 1 NSCs) produce ganglion mother cells (or GMCs) that divide once to generate a pair of neurons. Once born, neurons undergo an immature growth phase during which axons are guided to their correct targets; once axon growth is complete and synaptic contacts established, neurons can be considered to be mature. While much is known about neuronal development, an understanding of the key chromatin transitions that drive the process has been lacking. In particular, the genome-wide changes in chromatin state through which large numbers of previously-repressed neuronal genes are activated following differentiation, and through which key NSC genes are repressed, are unknown.Neural development is a complex process that ultimately accounts for all the diverse neuronal subtypes within the adult brain. In 5. Three of these—PcG, TrxG and HP1-asssociated chromatin—have been studied in the context of differentiation of ES cells to neural progenitor cells (NPCs)8 and PcG modifications have been specifically compared between cultured NPCs and neurons10. An overall picture of genes specifying cellular fate being regulated by repressive PcG and active TrxG chromatin has emerged13, with repressive PcG10 and HP1-associated chromatin marks15 subsequently spreading over inactive genes in differentiated cells. However, in addition to these three broad categories, two other forms of chromatin have been recently identified in cultured cells: a permissive chromatin state that was not associated with TrxG proteins and encompassed genes involved in metabolism and housekeeping ('Yellow' chromatin in ref. 4); and a silent 'Black' (or 'Quiescent' or 'Null') chromatin state that lacked either common histone tail modification marks or known histone-code reader or writer proteins4 . The roles of these two new forms of chromatin during development are unknown, and they have not previously been studied in the context of development or differentiation.Chromatin has been modelled to different numbers of forms, or states, which can ultimately be reduced to five broad categoriesDrosophila brain and observe large-scale chromatin remodelling during Drosophila neural development. Strikingly, genes involved in establishing NSC or neuronal fate were not repressed by PcG chromatin. Instead, in NSCs they were silent in either a Black chromatin state or a TrxG-repressive state, while in neurons they were repressed via HP1-associated chromatin. We found PcG chromatin to be associated specifically with lineage-specific transcription factors that control the spatial and temporal patterning of the brain.Here we use Targeted DamID to generate cell type-specific chromatin maps of NSCs, GMCs and immature neurons, and mature neurons within the 16, which enabled us to determine the cell type-specific DNA-binding profiles of a set of representative chromatin factors: Brahma 17, HP1 19, Polycomb 20, histone H1 21 and the core subunit of RNA Pol II 16 , larval GMCs and immature neurons  and neurons in newly eclosed adults  )16 Fig. . The genL4) Fig. . Importadpn)  moved from transcriptionally active chromatin to repressive chromatin, as evidenced by decreased binding of Brahma and Pol II and increased binding of HP1 and histone H1. In contrast, neuronal genes, such as the octopamine receptor gene Octbeta1R moved from silent repressive chromatin to transcriptionally active chromatin  to the DNA-binding profiles, fitting separate HMMs to all three data sets Fig. . Hierarc16, with a clear separation apparent between permissive and repressive states , as well as protein and vesicle transport .In addition to the above, we also observed genes that transitioned from the Black chromatin state to the non-TrxG active state Fig. . Consistdpn and E(spl)-HLHmγ , ase (orthologue of the ASCL genes) and the cell cycle gene CycE, were present in active TrxG-associated chromatin in neural stem cells. Given the importance of TrxG/PcG transitions in other systems, we expected that these genes would also be repressed by PcG-associated chromatin. However, in almost every case neural stem cell fate genes were instead repressed by HP1-associated chromatin . For some genes, the transition from TrxG-associated chromatin to HP1-associated chromatin occurred rapidly, being immediately repressed in immature neurons. Another subset of genes showed a delayed transition, remaining in a permissive TrxG-associated state in immature neurons and only entering a repressive HP1 state in mature neurons. Only the gene encoding tap (the neurogenin family orthologue)22, and an adjacent lncRNA (CR45688) transitioned from TrxG active chromatin to HP1-associated repression through a clear PcG intermediate , and we focused on known transcription factors present within these states for further analysis. Developmentally important transcription factors that are not expressed in NSCs, such as peb, scr, cad, sob, lab, tin and lz, were present in the PcG-repressive state in NSCs. In contrast, in the PcG-mixed state we found genes encoding transcription factors that regulate the temporal transitions of the NSCs in the larval brain optic lobe 24 and pattern the optic lobe .Given the absence of any major transitions involving PcG chromatin during neuronal differentiation, we sought to understand whether PcG-repressive chromatin played a significant role in neuronal development. In contrast to a previous study of mammalian NPCs differentiated to neurons in cultureDrosophila brain at an earlier developmental time point26. We identified 46 differentially expressed transcription factors, and plotted the chromatin state transitions occurring at the genes encoding these factors. Of these, 31 30. These genes were found to be present in a poised state that included the TrxG-associated H3K4me3 mark, a situation very similar to the TrxG-repressive state that we observe.The TrxG-repressive state we describe here is intriguing. This state is enriched for Brm binding in transcriptionally silent chromatin, and covers a large number of neuronal genes in NSCs. PcG-independent repression via the REST complex in ES cells has been reported to be associated with neuronal genes31. A mixed PcG chromatin state has also been previously associated with spatially compartmentalised transcription factors in ChIPseq of whole wing discs32, although that study was not cell type-specific. This last study speculated that such a mixed state might be indicative of bivalent chromatin in Drosophila.32 However, both this study and our own found concomitant occupancy of RNA Pol II on gene bodies in the PcG-mixed state, an observation at odds with silent bivalent chromatin. Combined with a significantly enriched association with lineage-specific transcription factors from existing RNA-seq data and immunofluorescence studies, our data suggest that this chromatin state is a genuine mixture between PcG repression in some lineages and TrxG activation in other lineages. We see no evidence in our data sets of true bivalent chromatin as reported in ES cells (strong binding of both PcG and TrxG components with no transcription).In neural development, we observe little role for PcG repression in controlling broad cell fate, but instead a role in specifying different neuronal lineages. Specific PcG repression/TrxG activation has previously been described for lineage-specific transcription factors within the mushroom body of the brainIn conclusion, our data present a picture of neural development that differs from that observed during the differentiation of ES cells in culture. Although lineage-specific transcription factors that generate neuronal diversity are regulated through PcG repression, the majority of genes activated in neurons follow different chromatin transitions. These genes are present in the silent Black chromatin state and a novel TrxG-repressive chromatin state in NSCs and transition to a TrxG permissive chromatin state in immature neurons. Furthermore, we demonstrate that almost all NSC identity and cell cycle genes are repressed in HP1-associated chromatin in neurons, and that this repression occurs concomitantly with a wide-scale accumulation of HP1-associated binding across the genome. Although canonical PcG/TrxG transitions are vital during early development, our data suggest that other forms of chromatin take over important regulatory roles during neural development.33; see Supplementary Table 16 was cut with BglII (NEB), treated with Antarctic phosphatase (NEB), and inserts and cut vector were assembled using the Gibson assembly method34. All vectors were sequenced before being used in germline transformation.Details and sequences of all primers used for generating constructs are shown in Supplemental Experimental Procedures. pUAST-attB-LT3 constructs for Brm, Pc, HP1a and H1 were generated by PCR amplifying the coding sequence of each chromatin factor from an embryonic cDNA library with Gibson Assembly adaptor sequences. Primers were designed using PerlPrimerwor-GAL435 for neural stem cells, GMR71C09-GAL436 for immature neurons and w;+;elav-GAL437 for mature neurons. All driver lines were crossed with tub-GAL80ts on either chromosome 2 or 3 to generate w;wor-GAL4;tub-GAL80ts, w;tub-GAL80ts;GMR71C09-GAL4, and w;tub-GAL80ts;elav-GAL4 lines, respectively, for use in Targeted DamID crosses. All drivers were tested for correct cell type-specific expression by crossing to w;+;UAS-mCD8::GFP and observing the expression pattern via confocal microscopy under the same conditions as the Targeted DamID sample collections (detailed below).GAL4 driver lines were UAS-LT3-Dam-Pc and UAS-LT3-Dam-HP1a flies were generated via injection of w;+;P{CaryP}attP2 embryos with the respective plasmids together with a phiC31 integrase helper plasmid pBS130 as an integrase source; UAS-LT3-Dam-Brm and UAS-LT3-Dam-H1 were generated via injection of y1sc1v1P{nos-phiC31/int.NLS}X;+;P{CaryP}attP2. UAS-LT3-NDam and UAS-LT3-NDam-RpII215 were used as previously described16.39 with the following modifications. Briefly, for NSC and immature neuronal data sets, flies were allowed to lay on apple juice plates with yeast for 4 h at 25 °C, before transferring plates to 18 °C for 2 days. About 100 larvae from each plate were transferred to food plates and grown at 18 °C for a further 5 days, before shifting to the restrictive temperature of 29 °C. For the NSC data set, expression of the Targeted DamID fusion proteins was induced for 16 h, and 30 brains were dissected per sample per replicate. For the immature data set, expression of the DamID fusion proteins was induced for 24 h and 30 ventral nerve cords were dissected per sample per replicate.Targeted DamID was performed as previously described40 using mesh sizes of 710, 425 and 150 µm.For the mature neuronal data set, flies were allowed to lay at 18 °C for 24 h in food vials. Vials were then kept at 18 °C until eclosion, whereupon the newly eclosed adults were transferred to fresh food vials and grown for a further day at 18 °C. The vials were then shifted to 29 °C for either 24 h (two replicates) or 48 h (two replicates). Following induction, flies were frozen in 14 mL tubes cooled in dry ice. Frozen flies were vortexed and body parts sieved to separate the heads as previously describedDpnI (NEB), before cut DNA was obtained with a PCR purification kit (Qiagen). PCR adaptors were ligated to the cut DNA, before digestion with DpnII (NEB) and PCR amplification (Clontech Advantage cDNA polymerase).Following tissue isolation, genomic DNA was isolated via DNA micro kits (Qiagen) and digested with Sau3AI or AlwI digestion. The resulting DNA was purified via magnetic bead clean up using Seramag beads41 in 20% (w/v) PEG-8000, and 500 ng of DNA was processed for Illumina Sequencing as previously described39. Briefly, DNA fragments were end repaired, A-tailed and ligated with Illumina TruSeq adaptors, cleaned twice with Seramag beads, enriched via six rounds of PCR before a final cleanup with Seramag beads. About 50 bp single-end reads were obtained via either a HiSeq 2500 (Illumina) or HiSeq 1500 (Illumina). Libraries were multiplexed such as to yield at least 20 million mapped reads per sample.Following the DamID procedure, samples were sonicated in a Bioruptor Plus (Diagenode) to reduce the average DNA fragment size to 300 bp, and DamID adaptors were removed via either overnight 39 using default options for all data sets except for histone H1. For histone H1, samples were normalised using reads per million (RPM) values owing to the low correlation between Dam- and H1-Dam-binding profiles. The resulting gatc.bedgraph data set replicates were compared via Pearson’s correlation and replicates averaged. The mean correlation between replicates was 0.90, with the minimum correlation being 0.81. To allow comparisons between different conditions, averaged data sets were scaled by dividing each data set by its standard deviation. Data sets were visualised using IGV42.NGS reads in FASTQ format were aligned using the damidseq_pipeline softwareProcessed data from the damidseq_pipeline software in gatc.gff format for the five chromatin proxy proteins was merged, sorted by chromosome and location, and a Gaussian HMM resolved using the RHmm R package (using 2000 random starts and 5–15 iterations per start). Each HMM was fitted for 20 states in order to detect the presence of mixed states within the data; Bayesian information criterion (BIC) was calculated from models fitted from 5 to 20 states for each data set to ensure that the HMMs were not over-fitted. A Viterbi path was then generated from the best fitting model and the original data using the RHmm R package. Each cell type was modelled separately to allow for the possibility that not all chromatin states would be shared between cell types.Chromatin states were then assigned broad chromatin classes with reference to hclust clustering of state means and HMM state transition probabilities. States with similar mean protein binding and a high shared transition probability were considered to be related and were merged. A simplified Viterbi path was generated from these merged states, and used for subsequent analysis.6 GATC fragments, each with the binding of the five chromatin proteins. PCA was performed using the prcomp function in R, and a plot generated from the first two principle components. Each point was coloured using the assigned chromatin state from the simplified Viterbi paths.To generate the PCA plot in Fig. Drosophila genome and the GATC resolution of the data, the modal state was assigned as the state occupying the plurality of each gene body ±250 bp.Genes were assigned chromatin states based on the modal state. To allow for the large number of short gene bodies in the http://gforge.se/). Genes encoding transcription factors were determined via a previously published list of all predicted and annotated Drosophila transcription factors43. All gene ontogeny analysis was carried out using the InterMine perl API44. Lists of all genes annotated with a GO term and associated child terms were obtained from the EBI QuickGO site (http://www.ebi.ac.uk/QuickGO/).Chromatin state transition graphs were generated in R using the transitionPlot function from the Gmisc R package  were filtered for replicates, where (mean)/(standard deviation) <1 and replicates were averaged. Genes were assigned as differentially transcribed if the TPM was both >10 in one lineage and <5 in one lineage. All transcription factors within this group, which were also expressed with FDR < 0.01 in at least one data set described in this study, were considered for chromatin state analysis.Previously published data for RNA-seq of different larval NSC lineages39 using the polii.gene.call R script with default parameters.Gene calls from RNA Pol II DamID-seq data were performed on averaged data sets as previously describedwww.r-project.org).All other analyses were performed using R  repository with accession number GSE77860. Requests for reagents should be addressed to the corresponding author.Supplementary Information


Numerous studies based on new single-cell and single-gene techniques show that individual genes can be transcribed in short bursts or pulses accompanied by changes in pulsing frequencies. Since so many examples of such discontinuous or fluctuating transcription have been found from prokaryotes to mammals, it now seems to be a common mode of gene expression. In this review we discuss the occurrence of the transcriptional fluctuations, the techniques used for their detection, their putative causes, kinetic characteristics, and probable physiological significance. Kinetics may lie at the heart of the mysterious ability of biological molecules to work in concert to regulate gene expression at the whole genome level . Measuri1.Although the oscillating nature of transcription has drawn quite a bit of attention in the past two decades, the existence of this phenomenon was suggested much earlier. An irregular distribution of the nascent transcripts on the non-ribosomal DNA strands was observed in a study of the chromatin spreads of the Drosophila melanogaster cells . The autTranscriptional fluctuation has been discovered in the cells of diverse species ranging from prokaryotes to mammals; in developing embryos as well as in various cell differentiation systems including embryonic stem cells . Viral gcyclin D1 gene whose transcription was pulse-like when driven by its own promoter, but became continuous under the powerful CMV promoter [Not surprisingly, various genes in the same cell display a wide range of transcriptional kinetic behaviour ,16–19. Ipromoter . Neverthpromoter ,23.Although the discontinuous expression has been studied predominantly in genes transcribed by pol II, the products of RNA polymerase III, which also works under a complex regulation,  are alsopS2 gene promoter with a period of approximately 20 minutes, which periodically prevents association of pol II and initiation of transcription [Transcriptional fluctuation seems to be irregular in most cases , and 1D,cription . Less recription . A more cription ,33.FiguTranscriptional fluctuation should be distinguished from the transcriptional cycle  , which mEven this brief sketch suffices to show that the phenomenon of transcriptional fluctuation, which has become known only recently, is a common feature of gene expression.2.in vivo as well as after fixation/lysation of the cells (Discontinuous transcription can be studied he cells . One impSingle molecule RNA fluorescence in situ hybridization (smFISH) is used for quantitative analyses of gene expression and nascent transcripts in a certain period of time at the single cell level . The numin vivo, cells are transfected with various constructs providing a fluorescent signal that corresponds to the expression of a particular gene. In the method based on a gene trap strategy a luciferase gene is inserted under the control of endogenous regulatory sequences [To observe the transcriptional activity equences . Since bequences ,20.et al. on myxamoeba Dictyostelium [et al. [The MS2 and PP7 based labelling methods, have become widely popular after the work of Chubb ostelium . These mostelium ,42,43. Tostelium . The fluostelium ,19,45–48 [et al. , a genetet al. compared the data on the activity of an HIV viral promoter obtained by the RNA FISH and MS2 based strategy, and found a general concordance of the two methods in terms of the numbers of molecules produced in one transcription burst [Although the described FISH and GFP based methods have provided most of the data about discontinuous transcription, both approaches have their shortcomings. The entire kinetics cannot be deduced from the state of fixed cells and transcription inhibitors may produce uncontrollable side effects. Moreover, transfection of cells with two different complex constructs can also introduce some inaccuracy . Single on burst .3.et al. suggested that periodicity of gene expression may result from periodical association of different chromosomal loci in the transcription factory [Transcription fluctuations can be divided into intrinsic and extrinsic based on their assumed causes . Variati factory .Figure Dynamic characteristics of transcriptional fluctuation can be altered by factors extrinsic in respect to the given gene and its promoter ,53,58–61Transcriptional oscillation can be also caused by intrinsic factors, that is an inherently discontinuous activity of the promoter. Such behaviour is often referred to as “intrinsic noise” ,58,64–66The random telegraph model has been used as a relatively simple way to describe the intrinsic fluctuations ,6,67. AcSince numerous specific interactions precede the initiation of RNA synthesis, it has been suggested that in the silent state that follows each transcription burst at least one additional period (the refractory period) is needed before the gene may be switched on again ,73. In oDictyostelium [An even more complicated model of the bursting gene expression was suggested in the recent study of the actin gene in ostelium . The autostelium ,74,75. Fostelium .Specific DNA features such as different numbers of CCAAT boxes may strongly influence the character of transcriptional kinetics [The discontinuous nature of transcription is apparently related to a repetition in the higher-order levels of chromatin structure involving substantial nucleosome-nucleosome interactions ,60,61,78kinetics ,82. The kinetics .Drosophila and mammalian cells show that pol II accumulates at the 5’ end of 20–30% genes including actively transcribed loci. The pause may serve for coordination of transcription with RNA processing. It is not clear how the RNA synthesis is restarted after the arrest, but it was reported that the proto-oncogene c-Myc plays a direct role in the pause release [Another plausible cause of the transcription discontinuity can be found downstream of the promoter. The so-called promoter proximal posing ,85, whic release .Elongation may be also stalled at the 3’end, close to the termination site, in other parts of the gene, and sometimes in a sequence dependent manner . OccasioThus, discontinuous gene expression may have numerous causes, but it seems probable that the dynamic pattern of transcription depends on a few dominant factors.4.Short periods of intensive transcription frequently alternate with longer silent intervals, which justifies the usage of the term ”bursting” . Howeverin vivo [The following three kinetic parameters seem to be the most important ones: the burst size, the coefficient of variation and the frequency. The burst size, which corresponds to the number of RNA molecules produced in a burst, is limited by the rate of transcription: if one pol II complex occupies about 60 bp of DNA strand, and passes roughly the same distance in a second, it cannot produce more than one transcript in a second , seem toin vivo . The avein vivo .HIV LTR gene increased, but the CV decreased [Another important parameter of transcriptional fluctuations is the coefficient of variation (CV), i.e. the standard deviation of the gene expression level divided by its mean value. In mammalian cells the mean expression is not determined by CV, but by the burst size and the burst frequency ,95. Numeecreased . Such daet al. observed both short (from 2.5 min) and long (up to 27.5 min) pulses in the expression of the act5 gene in Dictyostelium [The frequency is a highly variable parameter of bursting. In different genes the average periods of fluctuation  vary from a few minutes to hours ,17,50,73ostelium . Since tostelium .et al. were able to identify two other parameters: the number and duration of inactive states [Some of the kinetic parameters that are not directly observed may be inferred from other data. The number of nascent mRNA molecules can be used as a proxy for the polymerase occupancy; knowing the length of the gene, the polymerase speed (assumed to be approximately 30 bp/sec), and the polymerase occupancy, one can calculate the transcription rate. All these parameters vary significantly in isogenic cells ,78. UsinThus, the kinetic characteristics and especially the burst frequency are highly variable which should be carefully considered in the studies of transcriptional fluctuations.5.cI gene regulates transition between the lysogenic and lytic phases in the bacteria infected by the lambda phage [In unicellular organisms, especially in bacteria and yeasts, burst-like gene expression causes heterogeneity in populations, since variation in mRNA levels is easily translated into heterogeneity of protein levels and phenotype diversity including adaptation to unfavourable factors ,96–101. da phage . In someda phage , or thatda phage ,105, mayda phage ,106.In multicellular organisms variations of protein levels are relatively low ,107. HowUnder certain conditions fluctuations may be detrimental to the cell homeostasis and they have to be suppressed ,113. TheThe remarkable ubiquity of transcriptional fluctuations suggests that their role in regulatory processes in the cell are likely to be enormous. For one thing, pulsing is likely to cause other pulsing. Thus, RNA processing, which is closely linked to the RNA synthesis, may also occur in pulses ,115. ExtPerhaps the term “burst” was coined with regard to neurobiology, where it is applied to a pattern of action potential in an axon . A tende6.The research on discontinuous transcription has been intensified in the last years and this rising interest in the phenomenon reflects a recognition of its biological relevance. There seem to be two essential problems to be explored: 1) the nature of the local processes leading to pausing and restarting of transcription; 2) the interaction of various transcriptional and non-transcriptional fluctuations in the cell. Alternative approaches and new methods will most likely be needed to resolve these problems. The suggested lists of requirements include improved procedures for arresting transcription; establishing the order of events at the promoter; understanding whether transcriptional fluctuations are stochastic or specifically regulated ; methods


Spatial- and temporal-specific expression patterns are primarily regulated at the transcriptional level by gene promoters. Therefore, it is important to identify the binding motifs of transcription factors to better understand the networks associated with embryogenesis.factor involved in the regulation of rice seed maturation. OsSMF1  is known to interact with GCN4 motifs (TGA(G/C)TCA) to regulate seed storage protein synthesis, and it functions as a key regulator of starch synthesis. Quadruple 9-mer-based PBM analysis and electrophoretic mobility shift assay revealed that OsSMF1 bound to the GCN4 (TGA(G/C)TCA), ACGT (CCACGT(C/G)), and ATGA (GGATGAC) motifs with three different affinities. We predicted 44 putative OsSMF1 target genes using data obtained from both the PBM and RiceArrayNet. Among these putative target genes, 18, 21, and 13 genes contained GCN4, ACGT, and ATGA motifs within their 1-kb promoter regions, respectively. Among them, six genes encoding major grain filling proteins and transcription factors were chosen to confirm the activation of their expression in vivo. OsSMF1 was shown to bind directly to the promoters of Os03g0168500 (GCN4 motif), patatin-like gene (GCN4 motif), α-globulin (ACGT motif), rice prolamin box-binding factor (RPBF) (ATGA motif), and ONAC024 (GCN4 and ACGT motifs) and to regulate their expression.Here, we used a protein-binding microarray (PBM) to identify the binding motifs of OsSMF1, which is a basic leucine zipper transcription OsSMF1 is one of the key transcription factors that functions in a wide range of seed developmental processes with different specific binding affinities for the three DNA-binding motifs.The results of this study suggest that The online version of this article (doi:10.1186/s12284-017-0155-4) contains supplementary material, which is available to authorized users. It belongs to the maize O2-like protein group and is known to interact with the GCN4 motif (TGA(G/C)TCA) to regulate SSPs  is also involved in seed development, including the regulation of starch biosynthesis genes  and starch branching enzyme (SBE1) . To predict the co-expressed genes, we also examined the relationships among genes that are putatively regulated by OsSMF1 by RAN analysis.For the large-scale identification of transcription factor target sites, several laboratory techniques, such as chromatin immunoprecipitation (ChIP) and DNA adenine methyltransferase identification (DamID), have been devised Orian . RecentlOs03g0168500 and patatin-like protein, which contain the GCN4 motif; ONAC024 and ONAC026, which contain either the GCN4 or ACGT motifs; and prolamin box-binding factor (RPBF) and CCCH-type zinc finger protein (OsGZF1), which contain the ATGA motif. The results suggest that OsSMF1 has specific binding affinities for the three motifs and that it functions in a wide variety of seed developmental processes.Q9-PBM analysis revealed that OsSMF1 recognized three binding motifs, namely the GCN4 [TGA(G/C)TCA], ACGT [CCACGT(G/C)], and ATGA (GGATGAC) motifs, with different affinities. We detected 85 genes that were positively regulated by OsSMF1 using the RAN analysis under the tested conditions, with a minimum correlation value of 0.55 and a depth of 1. Among these putative target genes, 18 (21.2%), 21 (24.7%), and 13 (15.3%) contained GCN4, ACGT, and ATGA motifs within their 1-kb promoter regions, respectively. In addition to confirming the known OsSMF1 target genes, we predicted 35 potential target genes that have not been previously described in immature seeds. Using qRT-PCR and the protoplast transactivation assay, we found that in vivo, OsSMF1 activated OsSMF1 is a transcription factor previously known as RISBZ1 or OsbZIP58. In this study, OsSMF1 was mainly expressed in the endosperm at 11 and 21 DAF during seed maturation  were estimated by gel shift assay using SYBR Gold. DNA-binding band intensity was measured at various DNA substrate concentrations  in the presence of OsSMF1 (0.2 μg/μl). The Kd values for the binding of OsSMF1 to the GCN4, ACGT, and ATGA motifs were 0.6458 μM, 0.3353 μM, and 1.117 μM, respectively  using biotinylated double-stranded oligonucleotide probes corresponding to each motif. The binding of OsSMF1 to the 21-bp fragments of the GCN4, ACGT, and ATGA motifs was detected as lagging bands Fig. . As showely Fig. , d and fOryza sativa) (http://bioinfo.mju.ac.kr/arraynet/rice300k_2011/)   Table . Among t/) Table  have indOsSMF1 was expressed under control of the promoter of Wsi (a member of the group 3 Lea family), which is predominantly active in the whole grain, including the endosperm, embryo, and aleurone layer, during seed development  gene was used as a selectable marker to identify transgenic calli. Four independent transgenic plants were obtained using the Agrobacterium-mediated transformation method  was markedly upregulated in four independent calli derived from OsSMF1-transformed plants compared with that in nullizygous and wild-type calli  expression was also significantly increased in two independent OsSMF1-transformed calli  synergistically activate seed-specific genes during grain filling , PLATZ, RPBF, and OsGZF1. Their promoters were fused to fLUC (promoter:fLUC) as a reporter. Among the 13 putative genes, six genes were upregulated and one gene, OsGZF1, was downregulated by OsSMF1.To investigate whether OsSMF1 activates expression of the putative target genes listed in Table OsEnS44 and OsEnS146, which contain the GCN4 and ACGT motifs in its promoter region, respectively, was dramatically increased in OsSMF1-transformed rice. RPBF and ONAC024 transcription factors, the promoters of which contain the ATGA and GCN4/ACGT motifs, respectively, were highly expressed in OsSMF1-transformed calli compared with wild-type calli. We also selected patatin-like protein, the promoter of which contains the GCN4 motif . The α-Glb promoter was used as a positive control. The Os12g0621600  promoter, which was determined to be correlated with OsSMF1 in RAN analysis  but does not contain any of the three binding motifs in its promoter, was selected as a negative control (HRGP:fLUC). In these assays, the effector gene, OsSMF1, was expressed under control of the P35S promoter and co-transfected together with the reporter construct into the protoplast. Analysis of LUC activity demonstrated that the co-transfection of EnS44:fLUC, α-Glb:fLUC, and ONAC024:fLUC with OsSMF1 resulted in induction of the expression of the luciferase reporter gene by 23.7-, 33-, and 51.3-fold, respectively, compared with co-transfection of HRGP:fLUC , T/G (AACGTG), and G-like (CATGTG) motifs  have been previously identified as OsSMF1 target genes by transient assay using rice callus protoplasts  were characterized as SSPs. A previous study demonstrated that OsSMF1 causes reduced activation of the α-Glb promoter compared with that of the GluA-1 and GluA-3 promoters ”, it contained the GCN4 motif and was determined to be one of the direct target genes of OsSMF1  null mutants displayed abnormal seed morphology with altered starch accumulation and decreased amounts of total starch, particularly amylase, with binding to the promoters of six starch-synthesizing genes . The protoplast in vivo analysis revealed that the binding of OsSMF1 alone to the binding motif was not sufficient to self–activate the OsSMF1 transcription factor (data not shown). This result eliminated the possibility that OsSMF1 autoregulates itself as observed with GUS reporter genes under the control of the OsSMF1 promoter in rice protoplast , including 7.5%, incsay Fig. . Knock-osay Fig. . These rOsSMF1-transformed calli compared with wild-type calli. Among them, OsEnS44 was identified as an OsSMF1 target gene. Interestingly, we determined that OsSMF1 bound to the promoter of OsEnS44 by protoplast transactivation assay , CCACGTC (ACGT motif), and GGATGAC (ATGA motif) with different affinities. First, the transcription factor OsSMF1 regulated the expression of RPBF and OsGZF1, which contained the ATGA motif on their promoters. This result suggested that OsSMF1 regulated SSPs by binding the promoter of these genes. Second, OsSMF1 also regulated starch synthesis by binding to the promoters of OsSMF1 was isolated from panicles of Oryza sativa cv. Ilmi by RT-PCR prior to the heading stage using the primers indicated in Additional file OsSMF1-DsRed fusion gene, thereby producing the plasmid pET-SMFRed. This vector was used for the expression and purification of the OsSMF1 protein in Escherichia coli.GFP sequence of Wsi18:GFP , generating the plasmid Wsi:SMF1Red. Finally, the constructs were introduced into Agrobacterium tumefaciens LBA4404 by triparental mating . Cells were cultured overnight and inoculated into fresh liquid LB medium, grown at 37 °C to an OD260 of 0.6, and induced with 1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) at 25 °C for 5 h. Cell pellets were obtained by centrifugation at 4 °C for 5 min at 5,000 g, followed by washing with cold PBS buffer containing a protease inhibitor (Roche). Then, the cells were resuspended in 5 ml lysis buffer ), sonicated five times with 15 s bursts and 45 s of cooling on ice, and centrifuged at 14,000 g for 30 min at 4 °C. The resulting supernatants were incubated with 2 ml Ni-NTA agarose (Qiagen) for 30 min, loaded into empty columns, and washed twice with 5 ml lysis buffer containing 10 mM imidazole according to the manufacturer’s instructions. Purified proteins were eluted with 0.5 ml lysis buffer containing 240 mM imidazole. Five micrograms of purified proteins, as measured using the Bradford assay, were used in each experiment.The proteins were expressed in the A microarray was designed as described previously and manufactured by Agilent Technology  .Biotin end-labeled and unlabeled oligonucleotides were annealed with each complimentary sequence  and 0.2 μg/μl OsSMF1. Binding was performed in the presence of 10 mM Tris, 50 mM KCl, 1 mM DTT (pH 7.5), 50 ng/μl poly(dI–dC), 2.5% glycerol, 0.05% NP-40, and 5 mM MgClKd is the concentration of ligand required to reach half-maximal binding.where Bmax is the maximal binding, and Agrobacterium strain LBA4404 harboring Wsi:SMF1 was introduced into embryogenic rice calli (Oryza sativa L. Japonica cv. Ilmi) by Agrobacterium-mediated transformation  kept in a greenhouse for subsequent growth. Wsi:SMF1 transgenic rice of the T1 generation were used in further analyses.The www.mrcgene.com) and purified with a Qiagen RNeasy Mini Kit . cDNA templates were synthesized using RevertAid H minus M-MulV reverse transcriptase . Semiquantitative RT-PCR was performed in a 20 μl reaction mixture under the following conditions: one cycle at 95 °C for 2 min and 25 to 35 cycles at 94 °C for 30 s, 60 °C for 30 s, and 72 °C for 30 s. Real-time quantitative RT-PCR analysis was performed using 2X Real-Time PCR Premix with EvaGreen  according to the manufacturer’s protocol. Thermal cycling and fluorescence detection were performed using a Stratagene Mx3000P Real-Time PCR machine and Mx3000P software v2.02 . Melting curve analysis (with an increase from 55 to 65 °C in increments of 0.1 °C s−1) was performed to ensure that only the desired PCR product was measured at a specific melting temperature. Real-time PCR was performed in triplicate for each cDNA sample. Following amplification, the PCR data were assessed using a comparative quantification  analysis with Mx3000P software v2.02. (Stratagene). The rice tubulin gene (Os11g0247300) was used as an endogenous control. All primer pairs used are listed in Table S2.Total RNA was extracted from leaves of transgenic and wild-type rice plants using TRI REAGENT® . To construct reporter plasmids, promoters of putative target genes of OsSMF1 were amplified from 35S:OsSMF1, was co-transformed with the reporter plasmid into isolated rice protoplasts by polyethylene glycol (PEG)-mediated transformation (1 μg per transfection). P35S:rLUC (Renilla luciferase) was also added to each sample as an endogenous control (1 μg per transfection). Protoplast isolation and PEG-mediated transformation were performed as previously described . The transcript levels were measured in different sized panicles before heading , at the indicated days after pollination  and in the leaf, root, germinating seed, callus, and regenerating callus. (PPTX 70 kb)Transcript levels of Additional file 2: Figure S2.Rank analysis of OsSMF1 binding by Q9-PBM analysis. According to the rank-ordered signal distribution, two independent linear models (y = ax + b) were applied in the deep  and heavy right  tail regions of the curve. The extrapolated rank estimation for motif extraction was 1,286. (PPTX 84 kb)Additional file 3: Table S2.Primers used for PCR/real-time PCR. (XLSX 12 kb)Additional file 4: Figure S3.OsSMF1, is marked by an asterisk. Each circle indicates a gene, and the lines represent the correlations between the genes. Eighty-five genes were identified as OsSMF1-related genes, with a minimum correlation value of 0.55 and depth of 1. (PPTX 473 kb)The query gene, Additional file 5: Figure S4.OsSMF1 based on the 300 K Rice Genome Microarray (www.ggbio.com). The expression was measured in different sized panicles before heading , at the indicated days after pollination  and in the leaf, root, germinating seed, callus, and regenerating callus. (PPTX 75 kb)The expression patterns of transcription factors as a putative target of Additional file 6: Table S1.List of putative OsSMF1 target genes, as determined by RAN analysis . (XLSX 19 kb)


E6 and E7 viral oncogenes, modulated by the LCR, causes modifications in cellular pathways such as proliferation, leading to malignant transformation. The aim of this study was to identify specific TFs that could contribute to the modulation of high-risk HPV transcriptional activity, related to the cellular histological origin. We identified sex determining region Y (SRY)-box 2 (SOX2) response elements present in HPV16-LCR. SOX2 binding to the LCR was demonstrated by in vivo and in vitro assays. The overexpression of this TF repressed HPV16-LCR transcriptional activity, as shown through reporter plasmid assays and by the down-regulation of endogenous HPV oncogenes. Site-directed mutagenesis revealed that three putative SOX2 binding sites are involved in the repression of the LCR activity. We propose that SOX2 acts as a transcriptional repressor of HPV16-LCR, decreasing the expression of E6 and E7 oncogenes in a SCC context.Persistent infections with high-risk human papillomavirus (HPV) constitute the main risk factor for cervical cancer development. HPV16 is the most frequent type associated to squamous cell carcinomas (SCC), followed by HPV18. The long control region (LCR) in the HPV genome contains the replication origin and sequences recognized by cellular transcription factors (TFs) controlling viral transcription. Altered expression of  Cervical cancer (CC) is the third most common cause of cancer death in women from Latin America . This tyL1 gene and the beginning of E6. This sequence contains response elements that are recognized by regulatory proteins such as transcriptional activators, repressors, terminators and initiators of replication [The HPV double-stranded DNA genome contains a long control region (LCR) or upstream regulatory region (URR) located between the last codon of the lication ,17,18,19lication  which malication ; and E6 lication . Alteredlication .The LCR contains an “epithelial-specific” enhancer, encompassing several regulatory elements that hyper-activate viral transcription . TranscrE6 and E7 oncogene expression in a squamous cell context.The identification of additional TFs regulating the LCR could widen the knowledge of HPV type-specific biological behavior during the development of cervical cancer. The aim of this study was to identify specific TFs that could contribute to the modulation of high-risk HPV transcriptional activities, related to the cellular histological origin. Through in silico analysis of the HPV16- and HPV18-LCRs we identified a variety of response elements exclusive for each LCR. Interestingly, three putative sex determining region Y (SRY)-box 2 (SOX2) response elements were present in HPV16-LCR. SOX2 binding to these sites was demonstrated by in vivo and in vitro assays. The overexpression of this TF repressed HPV16-LCR transcriptional activity, as shown through reporter gene plasmid assays and by the down-regulation of the expression of endogenous HPV oncogenes. Site-directed mutagenesis revealed that the three putative SOX2 binding sites are involved in the repression of the LCR activity. We propose that SOX2 acts as a transcriptional repressor of HPV16-LCR, modulating 2. CaSki, HeLa and HaCaT cell lines were authenticated by short tandem repeat profiling in August 2016, by the Instituto Nacional de Medicina Genómica (INMEGEN), México and exhibited no evidence of cross contamination with known ATCC cell lines.2.2. Plasmid Constructs.CaSki HPV16 positive SCC cell line  was grown in RPMI-1640 medium , with 10% fetal bovine serum (FBS) . HeLa HPV18 positive adenocarcinoma cell line (ATCC # CCL-2) and the non-tumorigenic human keratinocyte HaCaT cell line , were grown in Dulbecco’s Modified Eagle Medium: Nutrient Mixture F-12 (DMEM-F12) medium , with 10% FBS, at 37 °C in a moist atmosphere of 95% air and 5% COCCCGGGCAGACCTAGATCAGTTTCCT-3′, and Reverse (Rev) HindIII 5′-GGG AAGCTTGCAGTTCTCTTTTGGTGCAT-3′, these amplify the region comprising nucleotides 7007–7905 to 1–102 of the HPV16 genome. PCR products were inserted into a SmaI/HindIII-treated pGL2-Basic vector , which harbors luciferase gene as reporter, generating the pGL2-LCR16 vector. The pGL2-LCR18 was previously built from PCR-amplified LCR products obtained from HPV18 positive cervical cancer biopsies [The HPV16-LCR was PCR-amplified from HPV16 positive cervical cancer biopsies. Primers used for HPV16-LCR amplification were as follows: Forward (Fwd) SmaI 5′-GGGbiopsies ; this plThe lentiviral vectors Pax2 and PMD2.G (Addgene) were used to produce recombinant lentiviruses containing SOX2 and/or green fluorescent protein (GFP) genes. The packaging cell line 293T was co-transfected with lentiviral expression plasmids SOX2 and/or GFP, Pax2, and PMD2.G, using lipofectamine plus (Invitrogen). Two days after transfection, cell supernatants containing the recombinant lentiviruses, were collected and stored at −80 °C until use.4 cell/well. After 24 h, based on standard curves, cells were transduced with 50 microliters of lentiviral supernatant added to each well and incubation was continued for 72 h. Lentiviral vector GFP was used as transduction control.CaSki cells were seeded in 24-well plates at a cell density of 3 × 10TM 3010 luminometer . Experiments were performed in triplicate.For transient transfection assays, 30,000 CaSki, HeLa or HaCaT cells were seeded in 24-well plates with complete medium; after 24 h the cells were transfected using lipofectamine 2000 (Invitrogen) with 200 ng of luciferase reporter vector and 1 ng of Renilla plasmid (pRL-CMV) for normalization. As a positive control pGL3-Control, containing simian virus 40 (SV40) promoter was used. Cell extracts were prepared 48 h post-transfection and assayed for luciferase and renilla activities using the Dual Luciferase kit . Relative luciferase units were measured in a MonolightPutative TFs binding sites within the LCR sequences of HPV16 and HPV18 were analyzed using the JASPAR CORE database  and alig32P) end-labelled DNA oligonucleotides. Primers used to identify SOX2 binding sites were: SOX2 consensus binding sequence (CS): 5′ TAGTCATACAATGTTCATTT 3′; putative SOX2 binding site 1 (S1): 5′-AACCATTCCATTGTTTTTTA-3′; putative SOX2 binding site 2 (S2): 5′-TAGTCATACATTGTTCATTT-3′; putative SOX2 binding site 3 (S3): 5′-AACTGCACATGGGTGTGTGCAAACCGT-3′; and non-specific oligonucleotide (NS): 5′ AACTGCACATGGGTGTGTGCAAACCGT 3′. The unlabeled double-stranded competitor was also included prior to the addition of labeled oligonucleotides, when specified. For the super-shift analysis, rabbit anti-SOX2 antibody  and rabbit anti-CCCTC-binding factor (CTCF) (sc-5916X) were used. Binding reactions were incubated for 20 min at room temperature. Protein-DNA complexes were separated from free oligonucleotide on a 6% non-denaturing polyacrylamide/Tris borate–ethylenediaminetetraacetic acid (EDTA) gel, and were resolved at 130 V for 2 h. The gels were visualized in a Typhoon 9400  and analyzed using the Image Quant software .The Electrophoretic Mobility Shift Assay (EMSA) was performed in a final volume of 20 μL containing nuclear protein extract from HeLa cells (15 μg), in the incubation buffer , 1M dithiothreitol (DTT), 10 μg/μL BSA, 1 μg/μL poly (dI-dC)  and 1 μL of double-stranded γ-ATP  and sonicated with Thermo Fisher Scientific sonic disruptor . The fragmented chromatin (mainly 300 to 500 pb) was immunoprecipitated with: rabbit anti-SOX2 ; rabbit anti-p65 , as LCR-binding control [The chromatin immunoprecipitation (ChIP) assay with CaSki cells was carried out using the OneDay ChIP kit , following the manufacturer’s instructions. 1 × 10 control ; and rab control . As a baQuantitative PCR (qPCR) was performed in triplicate in a fast optical 96-well qPCR reaction plate . Reactions were performed with primers amplifying a LCR region using the following primers: Fwd 5′-GTAAAACTACACATGGGTGTGTG-3′ and Rev 5′-GTCTGCTTTTATACTACACCGG-3′; with Thermo Maxima SYBR Green/ROX1 PCR Master Mix , in StepOnePlus Real-Time PCR System . As a positive control of SOX2 interaction, a fragment of the Lefty promoter was PCR amplified with the following oligonucleotides: Fwd 5′-GTCAGGGTAGGGATCACTC-3′; and Rev 5′-TACAATGGTCTGAAGTGTTGC-3′.Plasmid pGL2-LCR16 was mutated in the three putative binding SOX2-sites through site-directed mutagenesis , with primers shown in 2O) and prepared in the presence of complete mini EDTA-free protease inhibitor tablets . Protein concentrations were determined following the instructions of bicinchoninic acid solution and Copper(II) sulfate solution . 30 μg of protein loaded for each lane were resolved in 12% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to an Immobilon-P polyvinylidene difluoride (PVDF) membrane  for western blot. The membranes were blocked with 10% skim milk in TBS-T  and incubated with primary antibodies (in 5% skim milk) overnight at 4 °C. Protein levels of SOX2 and Lefty were analyzed with rabbit anti-SOX2  (1:2000 dilution) and rabbit anti-Lefty antibodies  (1:1000 dilution). Mouse anti-α-actinin, anti-β-actin and anti-GAPDH (1:1000 dilution) , were used as convenient for protein load control. Secondary antibodies anti-rabbit or anti-mouse  , conjugated to HRP (horseradish peroxidase-conjugated), were used. Proteins were detected using Immobilon Western chemiluminescent HRP Substrate kit .Whole cell lysates were collected using RIPA buffer . cDNA was synthesized using the SuperScript II RNAseH-Reverse Transcriptase .Cells were resuspended in 800 μL of Trizol Reagent . RNA was isolated according to the manufacturer’s protocol. RNA pellets were dissolved in 20 μL DNAse-free HcDNA generated from transfected cells was submitted to qPCR using SYBR green PCR master mix , according to the manufacturer’s protocol. The oligonucleotides used were for HPV16 E6, Fwd 5′-GGGGGATCCATGTTTCAGGACCCACAGGAGCGA-3′, and Rev 5′-GGGGAATTCTTACAGCTGGGTTTCTCTACGTGT-3′; for HPV16 E7, Fwd 5′-GGGGGATCCATGCATGGAGATACACCTACATTGC-3′, and Rev 5′-GGGAAGCTTTTATGGTTTCTGAGAACAGATGGGGCA-3′; and for 18S, Fwd 5′-AACCCTTGAACCCATT-3′, and Rev 5′-CCATCCAATCGGTAGTAGCG-3′.P was calculated by Student’s t-test from data presented as mean ± standard deviation (SD). Significant differences were accepted at P ≤ 0.05, as indicated.In order to identify transcription factor binding sites (TFBS) specific for HPV16- or HPV18-LCRs, we performed an in silico prediction analysis of probable TFBS using the JASPAR CORE database and alignment with consensus sequences. The results showed that although HPV16- and HPV18-LCRs shared TF binding elements, a group of sites that were restricted to each LCR, was identified. From this group, we found binding elements related to TFs involved in cellular processes such as proliferation and differentiation: FOX family (forkhead box); xenobiotic metabolism: Arnt (aryl hydrocarbon receptor nuclear translocator), FOXA2 (forkhead box); apoptosis: Ddit3 (DNA damage-inducible transcript 3); embryogenesis and tissue specificity: FOXD1, FOXF2, SOX2, MAFb (musculoaponeurotic fibrosarcoma homolog B) .The presence of SOX2 TFBS, found exclusively in the enhancer region of HPV16-LCR, was particularly interesting since SOX2 participates in stem cell pluripotency , squamouThe regulation of HPV transcriptional activity during the viral life cycle may be influenced by variations in the amounts of TFs or cofactors along the stratified epithelium, as well as under different cellular contexts. In order to determine the effect of the cellular context (squamous or glandular) on the transcriptional activity of HPV16- and HPV18-LCRs, promoter-reporter assays were performed in CaSki, HaCaT and HeLa cell lines with reporter vectors containing the luciferase gene under the control of LCR16 or LCR18. A significant activity of pGL2-LCR16 compared to the control pGL2-B vector was observed in the three cell lines A–C. NeveIn contrast, LCR18 activity was significantly lower than that of LCR16 in CaSki cells A. In HaCWe analyzed endogenous SOX2 protein levels in the different cell lines by western blot. As shown in 32P)  was observed when nuclear extracts were incubated with the SOX2 binding consensus probe (CS), labelled with γ-ATP (32P) A. In ord32P) A. For S132P) B–D. A si32P) B–D. ThesIn order to demonstrate that SOX2 protein is present in the DNA-protein complex, a supershift assay was performed. The presence of SOX2 in the DNA-protein complexes was confirmed after the addition of 50 ng (c) or 2500 ng (d) of anti-SOX2 antibody, resulting in a supershift band (SS) in the CS complex when using 2500 ng of antibody (d) E. A signIn order to confirm that SOX2 binds to the HPV16-LCR in vivo, ChIP assays were performed with chromatin extracts obtained from CaSki cells. ChIP results demonstrate that SOX2 binds in vivo to the HPV16-LCR. As a positive control we employed anti-p65 antibody, since it is known that p65 binds to HPV16-LCR . PreviouChIP results show that the DNA fragment containing the HPV16-LCR SOX2 binding sites was qPCR-amplified from the anti-SOX2 immunoprecipitated sample, with near 40% above IgG background . Such enIn order to elucidate the effect of SOX2 on the transcriptional regulation of HPV16-LCR, CaSki cells were transduced with lentiviral vectors carrying SOX2, and/or GFP as control. After 24 h, cells were transfected with reporter plasmids pGL2-LCR16 or pGL2-LCR18. Cells were processed 48 h later. To assess the presence of a functional overexpressed SOX2, protein levels of Lefty, a known SOX2 gene target, were also measured at different days post transduction. As expected, Lefty protein levels decreased as SOX2 increased A. At 48 To test whether SOX2 binding to S1, S2 and S3 sites is involved in the observed LCR16 transcriptional repression, mutations were generated in the pGL2-LCR16 vector : 2-base pairs (bp) mutated in S1 site (M1), 3-bp mutated in each of the S2 and S3 sites , and 8-bp mutations are introduced in the triple mutant  . As showE6 and E7 viral oncogenes are directly regulated by the LCR, we next analyzed whether SOX2 was acting as a transcriptional repressor of such oncogenes in vivo. Two amounts of SOX2 transcription factor expressing plasmid (150 and 300 ng) were transfected into CaSki cells to analyze its effect on the endogenous levels of E6 and E7 transcripts  may repress it. A differential activity between LCR16 and LCR18 in the three cell lines was evident, which could be due in part to differences in number, position or affinity of shared TFBS, or to the presence of different TFBS for each LCR.To identify novel TFs that could modulate the transcriptional activity of LCR16 and LCR18, we searched for putative binding sites for specific TFs. As expected, we found some TFBS shared between both viral types; however, there were others specific for each of the LCRs. We became interested in SOX2 transcriptional factor; due to the fact that consensus-binding sites for this factor were exclusively identified in the HPV16-LCR sequence and that it is involved in normal development as well as in malignant processes . This TFSOX2 has been linked to cancer hallmarks, promoting cell proliferation in breast, pancreatic, prostate and cervical cancers ,44,45,46In this study, we demonstrated that SOX2 binds to three putative binding sites identified in the enhancer sequence of LCR16 through direct interactions, as shown in EMSA and ChIP assays. We also confirmed that SOX2 is a transcriptional repressor of LCR16, since its activity decreased 3.5 times when SOX2 was over-expressed in CaSki cells . As has The direct interaction of SOX2 on the LCR16 putative binding sites was demonstrated through the analysis transcriptional activities of the mutated binding sites. A significant recovery of luciferase activity was observed with M1, M2 and M1,2,3 mutants in the basal state, which suggested that LCR16 mutants escaped from endogenous SOX2 repression. Moreover, when SOX2 was ectopically overexpressed, no repression of LCR16 M1 and M3 was observed and M2 mutant showed a mild repression (27.5%), in contrast to the observed for LCR16wt (66.2%). These data demonstrate that the three SOX2 putative binding sites contribute to the repressor activity of SOX2 in the HPV16-LCR.SOX2 repressor activity on LCR16 was confirmed in vivo in CaSki cells which contain HPV16 endogenous sequences, where E6 and E7 oncogenes are naturally expressed. Quantitative PCR analysis showed that E6 and E7 transcript levels significantly decreased in cells overexpressing SOX2, although no dose dependent effect of SOX2 was observed, probably due to a saturation of the putative sites at the tested SOX2 doses. With these data, we demonstrate a direct effect of SOX2 on HPV16-LCR, although we cannot discard the contribution of indirect factors. Bass et al. (2009), showed that an increase in the expression of various stem cell TFs was correlated with high levels of SOX2 expression in SCC lung tumors ; therefoIt is interesting that the analysis of SOX2 protein levels in the different cell lines showed that HeLa cells had the higher SOX2 protein levels, compared to the SCC lines (CaSki and HaCaT). These data match the higher transcriptional activities observed for LCR16 in the SQ context, in which HPV16 transcription could be favored due to a less repressive context. Therefore, under this background, it is possible that SOX2 is not acting as an activator of the LCR16 in SCC cells, but instead, as a repressor in adeno cells. Hence, high levels of SOX2 in HeLa cells could have a participation in the low activity observed for LCR16 in this cell type. However, it is important to consider that TFs that we did not analyze in this work surely influence the activity of the HPV LCRs.It is important to note that even though in our study we did not delve further into the distinct transcriptional activities of HPV18-LCR observed in the analyzed cell contexts, it is a subject that deserves additional studies. The assays with reporter vectors showed a clear down-regulation of the LCR18 under a SQ cell context. Furthermore, the in silico analysis also showed putative TFs binding sites that were specific for HPV18-LCR. Thus, it would be relevant to study which novel transcriptional factors could be modulating LCR18 activity.SOX2 regulation of HPV16-LCR could be biologically relevant in early HPV infections. HPV may infect basal as well as stem cells ,51, wherIt is worth mentioning that in cervical SCCs a high expression of SOX2 has been reported; however, the loss of SOX2 in a subgroup of cervical cancer cases, has been associated with poor prognosis . FurtherIn this study, we identified SOX2 as a new player in the transcriptional control of HPV16. A greater comprehension of the differential regulation of HPV types according to the cellular context will help to explain differences in their biological behavior.