Transcription factors (TFs) are often regarded as being composed of a DNA-binding domain (DBD) and a functional domain. The two domains are considered separable and autonomous, with the DBD directing the factor to its target genes and the functional domain imparting transcriptional regulation. We examined an archetypal zinc finger (ZF) TF, Krüppel-like factor 3 with an N-terminal domain that binds the corepressor CtBP and a DBD composed of three ZFs at its C-terminus. We established a system to compare the genomic occupancy profile of wild-type Krüppel-like factor 3 with two mutants affecting the N-terminal functional domain: a mutant unable to contact the cofactor CtBP and a mutant lacking the entire N-terminal domain, but retaining the ZFs intact. Chromatin immunoprecipitation followed by sequencing was used to assess binding across the genome in murine embryonic fibroblasts. Unexpectedly, we observe that mutations in the N-terminal domain generally reduced binding, but there were also instances where binding was retained or even increased. These results provide a clear demonstration that the correct localization of TFs to their target genes is not solely dependent on their DNA-contact domains. This informs our understanding of how TFs operate and is of relevance to the design of artificial ZF proteins. Under this model, the DBD acts to direct the TF to certain regulatory regions in the genome based on its affinity for a particular DNA sequence and the trans-acting domain then imposes regulatory effects on the appropriate gene. Recognizing the capability of the two distinct domains to function autonomously has been helpful in understanding TF function and has led to the development of methodologies such as the yeast two-hybrid system, where two separable domains are reunited to recreate a functional TF. Nevertheless, it is known that the situation is sometimes more complex: DNA-binding domains can also make functional protein–protein interactions with coregulators, and several results imply that non-DNA-binding domains can contribute to the localization of TFs to their target genes (Transcription factors (TFs) are typically regarded as having two distinct components: a sequence-specific DNA-binding domain (DBD) and a et genes .in vivo genomic profiles being observed in chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experiments. In these experiments, the genome-wide occupancy of TFs is determined by immunoprecipitating them together with associated DNA fragments and then identifying those fragments via large-scale sequencing. The TFs are first cross-linked to their target sites in living cells so that in vivo maps of binding sites can be generated. These maps show that in vivo TFs are far more discriminating about where they bind than in vitro. That is, in vitro most TFs bind to all sites that reasonably match their consensus binding sequence but in vivo only a small subset, sometimes <1% of possible sites are bound. For instance, ChIP-seq studies have revealed that GATA-1 binds to <1% of predicted consensus sites in erythroid cells , a motif would need to be >16 bp in length to be unique if a random nucleotide distribution is assumed. Despite this, most eukaryotic TF motifs are rather short and only some positions carry strong sequence preference. The zinc finger (ZF) TFs of the Krüppel-like factor (KLF) family, for instance, recognize a 10-bp sequence with only four of these positions being restricted to a single specific nucleotide . Furthercis-regulatory elements. KLF3 is an archetypal ZF protein belonging to the SP/KLF family and nine SP and 17 KLFs have been described to date. These proteins are characterized by a highly conserved C-terminal DBD composed of three tandem classical ZF motifs and variable N-terminal domains that can recruit coactivators or corepressors  cell lines were generated from Klf3−/− mice as previously described  with either Klf3-V5, ΔDL-V5 or DBD-V5. Stable clones expressing each transgene were then isolated under puromycin selection (2 μg/ml) using the cell dilution method in 24-well plates. Single clones were evaluated for relative protein expression by western blot using anti-V5 antibody  and for relative mRNA expression by real-time reverse transcriptase-polymerase chain reaction (RT-PCR) (Supplementary Table S1. Electrophoretic mobility shift assay (EMSA) was performed as previously described (Supplementary Table S2.escribed . All cel(RT-PCR) . For wesescribed . Probe sKlf3−/− MEFs expressing recombinant Klf3-V5, ΔDL-V5 or DBD-V5. Approximately 5 × 107 cells were used for each experiment and ChIP was conducted as previously described  according to the manufacturer’s instructions with minor modifications. Adapter sequences were diluted 1/40 before use and following adapter ligation, the library size extracted from the gel was 100–280 bp (excluding adapters) in line with the size of sonicated fragments. Library preparation was performed by the Ramaciotti Centre, University of New South Wales, New South Wales, AustraliaChIP was conducted in duplicate on escribed  using anhttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/.Libraries (6 inputs and 6 IP samples) were multiplexed into four lanes using sample-specific adapters such that there were three samples per lane. Samples were sequenced using 50 bp chemistry on the HiSeq 2000 . Library preparation and sequencing were performed by the Ramaciotti Centre, University of New South Wales, New South Wales, Australia. Quality control on the sequence data was performed using FastQC v0.10.1 available from Mus musculus genome using Bowtie2 v2.0.0-beta7   . The scrHOMER was used to quantify ChIP tag density at peak locations across the genome. Unless otherwise noted, tags were counted within 400 bp around the peak center (as peak widths could vary across the three different samples). All tag counts were normalized to 100 M reads, and were thus expressed as reads/100 M reads to allow comparison across samples. Histograms of tag densities around various genomic features were also derived using HOMER. Bin sizes varied depending on the application and are given with each result.http://omics.pnl.gov/software/VennDiagramPlotter.php) and eulerAPE v2.0 (available from http://www.eulerdiagrams.org/eulerAPE/).HOMER was used to create bedgraph files using the makeUCSCfile program. These were viewed using IGV v2.2 . Venn diAn ENCODE DNase-seq data set produced from murine lung fibroblasts by the Stamatoyannopoulos Laboratory at the University of Washington was downloaded from GEO (Accession# GSM1014199) ,26. An EDe novo motif discovery was conducted on these sequence databases using MEME v4.9.0 . RNA was subsequently ethanol precipitated and washed with 75% ethanol in DEPC-treated deionized water for further purification. RNA was then subjected to whole transcript sense labeling and hybridized to Affymetrix GeneChip 1.0 ST mouse gene arrays . Microarray preparation and scanning were performed by the Ramaciotti Centre, University of New South Wales, New South Wales, Australia. Microarray data were analyzed using Partek genomic suite v6.5 .Total RNA was purified from P-values were corrected for multiple testing using a false discovery rate threshold of 0.2.Microarray CEL files were imported into Partek and normalized using the robust multi-array average algorithm. After confirming array quality , differential gene expression was calculated and tested for significance using a one-way analysis of variance. Gene expression We developed a system to compare the occupancy of wild-type KLF3 with two KLF3 mutants A. The fiKlf3−/− mice .To avoid any competition between the mutants and endogenous, wild-type KLF3 we used MEFs generated from −/− mice . These Kanalysis B. In theat lower C. Importat lower D. Immunoin vitro binding of the three constructs to a previously validated CACCC-box probe derived from the Klf8 promoter . ChIP-seq was then performed on MEF cells expressing Klf3, ΔDL or DBD in duplicate. Samples were sequenced on the HiSeq 2000  using 50 bp chemistry. Across the six samples, a total of >700 M reads were mapped to the mouse genome using Bowtie2 (for details see Supplementary Table S4). Peaks for each mutant were called on individual replicates, and the overlap between replicates was established  with overlapping peaks taken forward for further analysis. An annotated table containing ChIP peaks across all three samples and sorted by KLF3 peak height can be found in Supplementary Table S5. Replicates were shown to be consistent based on the correlation between peak heights across replicates at overlapping peak locations .We also investigated promoter . In EMSAKlf8, Lgals3 and Fam132a (Stard4 promoter and two previously established unbound regions in the Klf8 locus (Supplementary Table S3). As shown in Supplementary Figure S5, the ChIP–PCR confirmed the presence of the expected peaks and the absence of peaks in negative control regions. To further validate the biological relevance of the rescued cell lines, we examined endogenous KLF3 occupancy at a number of genomic loci where we observed KLF3-V5 peaks by ChIP-Seq. These ChIP experiments confirmed that the sites identified as targets of KLF3-V5 are also bound by endogenous KLF3 .Encouragingly, the ChIP-seq peak analysis revealed strong peaks at previously identified KLF3 targets including  Fam132a . To furtf8 locus . New indSupplementary Figure S3). The distribution of KLF3 peaks in promoters, exons, introns and other regions across the Mus musculus (mm9/NCBI37) genome was analyzed based on RefSeq annotations. Promoter regions were defined as being −1 to +0.1 kb from the RefSeq transcription start site (TSS); intronic regions were those lying between exons; and intergenic regions made up the rest of the genome. Peaks that fell into coding exons, 5′ and 3′ UTR exons and close to the transcription termination sites (−100 bp to +1 kb) were all labeled as ‘other’.First the binding profile of wild-type full length KLF3 was analyzed as a reference for comparison with the mutants. A total of 14 115 KLF3 peaks were identified as overlapping across the two replicate sets of samples . An enrichment of conserved nucleotides around the center of KLF3 peaks is evident, indicating that these sites are more evolutionarily constrained than the surrounding sequence, and therefore likely to be functional regions. Higher conservation is observed for promoter peaks than intronic and intergenic peaks.The conservation of nucleotides around KLF3 peaks was also analyzed using the 30-way vertebrate PhastCons data from UCSC . KLF3 promoter peaks were found to have almost double the nucleosome depletion compared with peaks in introns or intergenic regions.We sought to supplement our KLF3 data by incorporating two data sets from the ENCODE consortium. An RNA-pol II ChIP-seq data set from MEFs produced by the Ren Laboratory at the Ludwig Institute for Cancer Research was analyzed using our ChIP-seq pipeline to produce bedgraph files for visualization ,27. SimiKlf3−/− MEFs and the same cell line rescued with Klf3-V5. A P-value cutoff of <0.05 was applied using 1-way analysis of variance and transcripts dysregulated more than 2-fold were selected. In total, 196 transcripts were repressed and 201 were upregulated on rescue with KLF3 according to these cutoffs. A volcano plot of these data is found in Supplementary Figure S8, and the microarray data are available in Supplementary Table S6.Given that a large number of KLF3 peaks at proximal promoters had been identified, we wished to better understand how KLF3 occupancy related to changes in gene expression. To accomplish this, we performed Mouse Gene ST 1.0 gene expression microarrays  on Supplementary Table S5). A total of 65 genes showed >2-fold repression in the presence of KLF3 and a KLF3 promoter peak. Only 19 genes showed activation >2.0-fold in the presence of KLF3 and a KLF3 promoter peak consistent with previous results and reinforcing the view that KLF3 is predominantly a repressor of transcription  .k height . The motk height ,7 . Similar motifs were found to be enriched in both intronic and intergenic KLF3 peaks, where we saw an overrepresentation of binding sites for AP-1, and TEF and RUNX family members. However, KLF3 promoter peaks showed enrichment for a different set of motifs, with the presence of consensus sites for ETS and E2F factors, along with CCAAT binding proteins. Across the three regions, the highest enrichment was for the AP-1 motif at intergenic peaks where 33.29% of KLF3 peaks contained this motif, compared with a background expectancy of 6.57%. The diversity of motifs enriched within KLF3 peaks would suggest that KLF3 may target genomic sequences in a variety of cis-regulatory modules to influence gene expression.We also investigated the enrichment of known TF motifs within 200 bp of KLF3 peak centers in promoter, intronic and intergenic regions ; in particular, we were able to confirm the importance of the invariant C residues at positions 5, 7 and 8, where the presence of a G on the coding strand presumably allows hydrogen bonding with contact arginine residues in the DBD of KLF3. There is also a strong preference for a C nucleotide at positions 3 and 9. Interestingly, the C to G mutation at position 7 resulted in novel, high affinity binding by an unidentified protein.The sequence F, using ng motif . The impβ-goblin CACCC probes containing each of the four possible bases at position 1. In agreement with the consensus, we found a strong preference for G or A at this position . Taken together, these results demonstrate that the in vitro binding preference provides support for the ChIP-seq generated consensus and highlights for the first time the importance of having a G or A at position 1.In agreement with the consensus, we found greater tolerance at positions 2 and 10, whereas introduction of a C at position 6 had a significant impact on binding. Position 4 appears able to accept a T residue that is not suggested by the consensus. A preference for a G at position 1 was observed in the KLF3 ChIP-seq results; however, the importance of this nucleotide has not been previously discussed or analyzed to our knowledge. When the G at position 1 was changed to a C, a reduction in binding was observed, indicating that the G at position 1 is important F. To invSupplementary Figure S3). A range of striking differences was observed in the binding profiles of these proteins and a number of illustrative peaks are displayed in  and in the body of the Fez2 gene (panel F), while DBD shows a broad loss of binding across all regions. In summary, our comparative analysis of genome-wide binding by KLF3, ΔDL and DBD revealed that loss of binding by ΔDL at promoters is common and dramatic loss of binding by DBD is almost universal. However, as the examples in Having profiled the occupancy of KLF3, we next sought to compare this binding profile against the two mutants: ΔDL and DBD. In total, 12 248 and 4955 peaks were identified for ΔDL and DBD, respectively, compared with the 14 115 peaks identified for KLF3 . Furthermore, in contrast to its in vivo activity, DBD shows a stronger interaction with DNA than full length KLF3, such that progressive deletion of the N-terminal domain of KLF3 appears to result in increased DNA-binding in vitro .It was then possible to look more closely at the differences in peak heights between KLF3, ΔDL and DBD. The mean peak height of KLF3 was compared with ΔDL and DBD at various genomic regions D. ΔDL shSupplementary Figure S13). Motifs were similar between KLF3 and ΔDL, although only 142/500 ΔDL peaks showed the presence of the motif compared with 448/500 for KLF3. The DBD motif was slightly different to the KLF3 and ΔDL motifs and a more limited number of peaks (52/500) showed the presence of this motif. The reduction in the number of motifs in the ΔDL and DBD peaks may suggest that the specificity of these proteins has been compromised to some extent by the mutations introduced. In other words, the mutations appear to be reducing the discrimination in binding, but overall we see the retention of a consistent CACCC-like consensus sequence across the three samples , which is presumably dependent on direct contacts between the ZF domain and DNA.We also examined the KLF3, ΔDL and DBD peaks to see whether there were any differences in the KLF3 or KLF3 mutant consensus binding motifs . There is a high degree of similarity between the emerging consensus DNA motifs of KLF1, KLF3 and KLF4 . Our analysis of KLF3 promoter peaks revealed an association with binding sites for ETS family members  and have also found that progressive deletion of the N-terminus of KLF3 increases in vitro DNA-binding affinity . This increased affinity for DNA may lead to increased promiscuity by DBD and less specific binding in vivo . Also of note is that the related protein KLF1 is known to have an autoinhibitory domain immediately N-terminal to the ZF region . A GATA-1 mutant carrying a non-functional binding domain for FOG-1 displayed a different occupancy profile than wild-type protein  under accession numbers GSE44748 and GSE44744.Supplementary Data are available at NAR Online.National Health and Medical Research Council and the Australian Research Council. Australian Postgraduate Award Scholarships . Funding for open access charge: The University of New South Wales.Conflict of interest statement. None declared.


TnIc) was chosen as a model, and G4s found in this region were subjected to biophysical characterisations. The chromosome 19 specific minisatellite G4 sequence (MNSG4) and near transcription start site (TSS) G4 sequence (−80 G4) adopt anti-parallel and parallel structures respectively in 100 mM KCl, with stabilities comparable to those of oncogene G4s. It was also found that TnIc G4s act cooperatively as enhancers in gene expression regulation in HEK293 cells, when stabilised by a synthetic G4-binding ligand. This study provides the first evidence of the biological significance of promoter G4s in cardiac function-related genes. The feasibility of using a single ligand to target multiple G4s in a particular gene has also been discussed.G-quadruplexes (G4s) are four-stranded DNA secondary structures, which are involved in a diverse range of biological processes. Although the anti-cancer potential of G4s in oncogene promoters has been thoroughly investigated, the functions of promoter G4s in non-cancer-related genes are not well understood. We have explored the possible regulatory roles of promoter G4s in cardiac function-related genes using both computational and a wide range of experimental approaches. According to our bioinformatics results, it was found that potential G4-forming sequences are particularly enriched in the transcription regulatory regions (TRRs) of cardiac function-related genes. Subsequently, the promoter of human cardiac troponin I ( These findings indicate that these non-canonical DNA structures are favoured by natural selection in the process of evolution. Secondly, potential G4-forming motifs closely correlate with functional regions in gene promoters in the human genome, such as the gene regulatory elements Due to its diverse biological functions and wide distribution in the human genome, G4 DNA has attracted exceptional attention from nucleic acid chemists to design and synthesise novel G4-binding ligands that can interact efficiently and selectively with this peculiar DNA structure. So far, most G4-binding ligands are researched as potential anti-cancer agents by targeting cancer-related G4s, especially the human telomeric G4 and oncogene promoter G4s. The affinity and selectivity of G4-binding ligands to G4s rather than to other DNA forms are mainly achieved by π–π stacking and electrostatic interaction, which are also the two main criteria in G4-binding ligand design PDGF-A, VEGF-A and HIF-1α, G4 research also has relevance to cardiovascular science.To date, almost all G4 studies have focussed on their involvement in cancer and therefore their potential as targets for anticancer agents. Thus, most studies have centred on telomeric G4 and promoter G4s in proto-oncogenes. Importantly, extensive studies of these cancer-related G4s have contributed greatly to forward our knowledge in this field, which have established the fundamentals to investigate the role of G4s in other genes, such as those involved in regulating cardiac functions. Since possible biological functions of G4s have been identified in some heart-related genes, such as in vivo, and the structural similarity between different G4s, it makes the design of selective G4-binding ligands extremely challenging, and off-target effects are practically inevitable. However off-target effects may lead to multi-targeting effects in some cases, which in turn become advantageous for G4-binding ligands, and may enhance their therapeutic potential, such as the ligand naphthalene diimide derivative 1 Taking into account the instability of G4s and their much lower abundance as compared to adjacent duplex DNA in the human genome In this article, we first evaluated, by bioinformatics approaches, the importance of G4s in TRRs of key cardiac genes as compared to other genes, especially those involved in cancer. We found that potential G4-forming motifs are particularly enriched in TRRs of genes active in the heart, and TRRs of genes involved in cardiac function-related pathways are also highly G4-abundant. Although very basic, these findings clearly supported the hypothesis that G4s are important in regulating cardiac function-related genes. Furthermore, due to the abundance of G4-forming motifs in TRRs of cardiac function-related genes, potentially, multi-targeting strategy may have similar therapeutic potential as those observed in anti-cancer research.TnIc) gene was selected as a model system. Human TnIc is the only sarcomeric protein found to be exclusively expressed in the cardiac myocyte, which makes it an ideal model to investigate cardiac-specific gene expression and in turn to provide new approaches to the construction of cardiac-specific vectors in gene therapy. Although TnIc has been regarded as a preferred biomarker in MI  diagnosis for more than a decade TnIc transcription regulation are still poorly understood, and only a few TFs have been found to be involved in regulating the transcription of TnIcTnIc is highly G4-enriched according to the bioinformatics analysis. Multiple G4-forming sequences have been identified in the proximal promoter of human TnIc, and two types of G4-forming motifs were selected for detailed studies, which are designated as “MNSG4” , and “−80 G4” (centred at −80 bp to the TSS). The MNSG4 motif is composed of 6 repeats of chromosome 19 specific G-rich minisatellite (MNS), which are highly conserved in primates. Although conserved chromosome 19 specific MNS repeats are also found in many other genes, such as the neuronally expressed Shc adaptor homolog SCK1/SLIEMR3TnTTo validate the bioinformatics results (i.e. that G4s are involved in regulating cardiac function-related genes) and to initially test the multi-targeting strategy within a single gene, subsequently, the human cardiac troponin I (TnIc. The methods include CD (circular dichroism) spectroscopy We have used a combination of biophysical and biochemical approaches to characterise the formation, stability and possible regulatory roles of the G4s (MNSG4 and −80 G4) in the promoter of the human ≥3(N1∼7G≥3)≥3. Tissue-specific enrichment of G4-forming motifs was defined as the percentage of genes active in certain tissue (GNF/Atlas organism part) containing at least one G4-forming motif in a certain region of the TRR (Equation 1)Sequences of the human genome (version 37.64) were downloaded from ENSEMBL FTP, and gene/transcripts features were exported from BioMart , proximal promoter region (−500∼−1 bp), and downstream region . The analysis was carried out in 10 iterations to consider transcript redundancy. Hence the tissue-specific enrichment of G4-forming motifs was presented as mean ± standard deviation (SD). In analysing specific tissue, differences among iterations were evaluated by one-way ANOVA test, in which F and Q, were calculated respectively to reflect the abundance and location significance of G4s identified in each transcript. In the TRR of each transcript, the percentage of nucleotides involved in G4 formation is defined as F values according to n is the number of G4s identified in the TRR (F = 0 when n = 0), igs and ige are the start and end positions of ith G4 identified in the TRR relative to the TSS in 5′ to 3′ direction, and T, the length of TRR being searched, is fixed at 3,000 in this study.To evaluate the importance of G4s in individual transcript, two scores, Fcd, and Fncd, . Overall abundance of G4s, the Po , were calculated as the sum of Fcd, and Fncd. To genome-widely compare the abundance of G4s in TRRs of different transcripts, F scores of all transcripts without redundancy were calculated (one transcript was randomly picked when multiple transcripts were reported from the same gene), and the cumulative frequencies of F scores of all transcript were calculated and denoted as CFcd, CFncd, and CFo. To reach a more stringent criterion, transcripts with F scores equal to 0 were excluded when calculating CF. Genes with transcript CF values higher than 50% were regarded as G4-rich in their TRR, while those with transcript CF values lower than 50% were regarded as G4-scarce.Abundance of G4s on the coding strand, and template strand were separately calculated and labelled as KIT and MYC promoter G4s. Thus, another indicator, the Q score, is introduced to evaluate the potential location significance of G4s in particular TRR.Except for the G4 abundance, the location of individual G4 in a particular TRR may also correlate with its biological significance. As reported in previous genome-wide analyses, G4 was found to be enriched in the promoter region between −200 bp and TSS, and peaked at around −50 bp to TSS in the human genome kW is the normalized probability of nucleotide in position k of all TRRs involved in G4 formation, m is the total number of transcripts analyzed. j,kα is the logical value of nucleotide in position k of jth TRR; j,ka = 1 when the nucleotide is involved in G4 formation, otherwise j,ka = 0. G4 location significance score Q  for the TRR of a particular transcript was calculated according to Following on the previously reported method Q scores, CQ, were also calculated. Similarly, transcripts with the zero Q scores were excluded. Genes with both CF and CQ values higher than 50% were regarded as G4-important genes, while those with both values lower than 50% were regarded as G4-less-important.CF and CQ scores on the coding, template strand and both strands were also investigated. The correlation coefficient was calculated according to xi and yi are the CF and CQ scores of the coding, template strand or both strands at genome level, CF and CQ scores at genome level.Correlation between the CF and CQ were calculated for all transcripts without redundancy. To evaluate bias introduced in random-picking when multiple transcripts exist in one gene, calculation was carried out for 10 iterations. Gene list for all pathways was downloaded from KEGG database. All pathways including more than 50 genes were subject to pathway analysis. When more than 50% component genes in a pathway were calculated as G4-important , the pathway was regarded as G4-important. To evaluate the G4-importance of individual pathway, distribution of CF and CQ values of pathways were compared to the distribution of all transcripts in humane genome by Wilcoxon rank sum test. Differences between iterations of individual pathway were evaluated by one-way ANOVA test.The source code of bioinformatics studies is available upon request.MNS-ITr is the consensus sequence of G4-forming minisatellites between −528 and −319 bp to the TSS of human TnIc gene. Oligo MNS-IITr is the C-rich complimentary strand of oligo MNS-ITr. Oligo MNS-IIITr is the Cy3-labeled MNS-ITr attached with a 34-mer artificial linker on its 3′-end. -80-ITr is a G4-forming sequence from the noncoding strand fragment of human TnIc promoter localized between −97 and −73 bp to the TSS, while oligo -80-IITr is its C-rich complimentary strand. Oligo -80-IIITr is the Cy3-labeled -80-ITr attached with a 34-mer artificial linker on its 3′-end. Oligo Comp-Cy5 is a Cy5-labeled oligo complimentary to the 34-mer artificial linker in oligos MNS-IIITr and -80-IIITr. Oligos and primers used in plasmid construction were purchased from Eurofins MWG Operon  and were subjected to HPLC purification. The sequences and labeling sites of these oligos are listed in All labelled and unlabelled DNA oligos used in biophysical studies were purchased from IBA Biotechnology  and HPLC purified (double HPLC purification for labelled oligos). Fluorophores (Cy3 or Cy5) were coupled to nucleotides via NHS (N-hydroxysuccinimide) esters. Oligo concentration was determined by absorption at 260 nm. Oligo Formation of G4s was determined by EMSA, CD spectroscopy, and DMS footprinting in solution. Detailed protocols are described in Unfolding thermodynamics of G4s and the stabilising ability of G4-binding compounds to these G4s were investigated by CD melting experiments. Unfolding kinetics of these G4s were investigated via a pseudo-first order approach as described previously +) buffer to the appropriate concentrations. Prior to use in the FID assay, the DNA strands were incubated to allow the formation of G4s as stated above. The compounds to be analysed and thiazole orange (TO) were dissolved in DMSO to give 1 mM stock solutions. The corresponding solution was then diluted using 10 mM potassium cacodylate (pH 7.4)/50 mM potassium chloride (60 mM K+) buffer to the appropriate concentrations. The FID assay was carried out according to the protocol as previously reported +) buffer an increasing amount of the molecule under study was added . After an equilibration time of 3 min the emission spectrum was recorded between 510 and 750 nm with an excitation wavelength of 501 nm. This was recorded using a Varian Cary Eclipse Spectrometer . The fluorescence area was calculated using the “trapezium rule” method. The area was converted into percentage TO displacement by the following formula: % TO displacement = 100 − [(fluorescence area of sample/fluorescence area of standard) × 100]. The standard fluorescence spectrum was obtained in the absence of any G4-binding ligands. % TO displacement was then plotted against each of the compound concentrations to give the respective FID curves, from which the DC50 values were determined.The corresponding oligonucleotides were first dissolved in MilliQ water to yield a 20 µM stock solution, and then were diluted in 10 mM potassium cacodylate (pH 7.4)/50 mM potassium chloride (60 mM KMNS_G/C) and mutated  minisatellite concatemers were constructed by ligation and recombination processes. Oligos MNS_G/C and MNSM_G/C were first phosphorylated individually in 10 µl phosphorylation reaction system  at 37°C for 1 hour. Then, phosphorylated oligos MNS_G/C and MNSM_G/C were annealed to each other by a PCR thermocycler (Stratagene) at 95°C for 5 min, then gradually cooling to 25°C over 2 hours. Concatemers with random number of repeat were constructed by self-ligation (first round ligation) of annealed single repeat of E-WT/M minisatellites. 5′linker and 3′linker were phosphorylated and annealed from oligos 5′Linker_G/C and 3′Linker_G/C respectively through the same protocol. Then, annealed 5′linker was ligated to concatemers in a second round ligation, and the 3′linker was added in the third ligation subsequently. All three rounds ligation were carried out in 20 µl system at 16°C for 2 hours. Ligation products larger than 100 bp were extracted by QIAGEN Gel extraction kit after each round of ligation. All enzymes and buffers used in this step were purchased from NEB .Engineered wild-type -WT, hTnIc-3MNS(E)-WT, and hTnIc-1MNS(E)-WT plasmids were constructed by inserting the −299 to +51 fragment into pGL3-Basic-Gateway vectors downstream to the engineered WT minisatellite concatemers with 6 repeats, 3 repeats, and 1 repeat via PstI and XhoI restriction sites. By using similar approach, the vector containing 6 repeats of mutated MNSG4 was constructed as hTnIc-6MNS-M. Vector hTnIc-299-WT was constructed by inserting the −299 to +51 fragment into empty pGL3-Basic-Gateway vector via EcoRI and PstI restriction sites. Vectors hTnIc-80 G4-M, hTnIc-80Sp1-M, and hTnIc-80 G4/Sp1-M were derived from hTnIc-6MNSG(E)-WT by DpnI-mediated site-direct mutagenesis, in which the −80 G4-forming sequence, the Sp1 binding site in the −80 G4 motif, and both of them were mutated respectively. An overall mutant hTnIc-6MNS/80 G4-M was generated from hTnIc-6MNS-M by mutating both −80 G4-forming sequence and the Sp1 binding site in it. Vectors are schematically illustrated in Entry vector containing minisatellite concatemers was made by recombinating the third round ligation products into pDONR221 using Gateway® BP reaction kit (Invitrogen). The minisatellite concatemers were further recombinated into a pGL3-Basic-Gateway vector using Gateway® LR reaction kit (Invitrogen). The insertions were confirmed by sequencing using M13 primer pair. The −299 to +51 fragment of human 2 flasks and grown to 70–80% confluence at 37°C and under 5% CO2 atmosphere in complete medium (Dulbecco Modified Eagle’s Medium (DMEM) supplemented with 4500 mg/L D-glucose, 5.0 mM L-glutamine, 10% fetal calf serum, and 83.3 U/ml of penicillin and streptomycin (Invitrogen)). The cells were harvested by Trypsin-EDTA, and reseeded 2×104 cells/well in 24 well plates with a volume of 300 µl/well complete medium, and the cells were cultured overnight. The medium was replaced by 300 µl fresh medium at least 2 hours before transfection. Transfection was carried out by following calcium phosphate precipitation. Briefly, 20 ng pRL-TK control plasmid (Renilla luciferase reporter vector driven by herpes simplex virus thymidine kinase promoter PHSV-TK) and 150 ng testing pGL3 luciferase plasmid was transfected in each well, and cells were incubated with precipitated DNA for another 24 hours before adding G4-binding ligands. G4-binding ligands were diluted in DMSO to different concentrations as 1000× stock solution. 0.3 µl G4-binding ligand stock solution was diluted to 300 µl by fresh medium to replace the transfection medium in each well. Cells were then incubated with G4-binding ligands for 24 hours before cell lysis for luciferase assays. Experiments were carried out in triplicates.HEK293 cells were inoculated in 75 cmTransfected cells were firstly washed by ice-cold PBS to reduce background signals from the medium, and luciferase assays were performed subsequently according to manufacturer’s instruction (Promega). Generally, cells were lysed by 100 µl passive lysis buffer per well, and 10 µl cell lysate were added to 50 µl luciferase assay reagent. After 3 s’ delay, luciferase signals were collected for 10 s in a Glomax 20/20 luminometer (Promega). After adding 50 µl of Stop and Glo reagent, Renilla signals were collected for 10 s as internal control.The enrichment of G4s in the transcriptional regulatory regions  of all known protein-coding genes was first analysed as a reference point. In total, of 19,633 genes that were analysed, 67.79±0.01% of them were found to contain at least one G4 on both coding strand and template strand, with 52.42±0.02% and 46.91±0.02% containing at least one G4 on the coding strand (G4) and template strand (C4), respectively. Compared with the widely accepted results that around 40% human gene promoters contain G4s et al. The enrichment of conserved G4s in different tissues has been previously investigated by Verma According to the above findings, several points became apparent. Firstly, enrichment of G4 in TRR of genes has a strong tissue-specificity. Secondly, in some tissues , G4s are enriched specifically in certain regions of TRRs (location-specificity) reflecting possible tissue-related regulatory roles of G4s. These tissues, with either tissue- or location-specific enrichment of G4s in TRRs, are worthy of further investigation in the future.F score, and its cumulative frequency: CF) and G4 location significance score , which will be described separately in following sections.From the studies described here, G4s appear to be highly abundant in TRRs of genes active in the cardiac function-related tissues, such as the heart and smooth muscle. To further investigate the biological significance of G4s in the heart, we analysed the abundance and location significance of G4s in TRRs of genes involved in different pathways described within the KEGG (Kyoto Encyclopedia of Genes and Genomes) PATHWAY database, especially those related to cardiac functions. The importance of G4s in each TRR was evaluated by two scores: G4 abundance score  in RefSeq of genes CFcd, CFncd, and CFo values for each transcript were calculated as the cumulative frequency according to the Fcd, Fncd, and Fo histograms  and template (Qncd) strand were calculated according to Qo) was determined as the sum of Qcd and Qncd. Histograms Qcd, Qncd, and Qo for TRRs of all transcripts with redundancy are shown in Q scores on the coding strand also reflect the higher location significance of G4s on the coding strand as compared to the template strand. Transcripts without redundancy were also analysed with 10 iterations of randomly chosen transcripts, and similar results were obtained as compared to the results from transcripts with redundancy  were evaluated. As shown in CF and CQ are plotted as correlation maps. According to the maps, CF values are positively correlated to CQ values. Particularly, in G4-important TRRs , their G4 abundance is more positively correlated to their G4 location significance as compared to G4-less-important TRRs . To investigate whether this positive correlation of G4-important TRRs is only caused by the increase of G4 content or not, G4s found in different regions of TRRs were subjected to further investigation. The total number of G4s identified in different regions in G4-important and G4-less-important transcripts were counted and normalised to the length of different regions. If the increase of CQ, the location significance score, was solely dependent on the increase of CF, the G4 abundance score, then the proportion of the normalised total number of G4 found in different regions should be in constant between G4-important and G4-less-important TRRs. We found that the proportion of G4s found in the proximal promoter region (−500 bp to −1) was increased by 20% from less G4-important TRRs to G4-important TRRs . Most well-studied genes containing promoter G4s with potential regulatory functions are in the group of G4-important transcripts in the correlation map, including MYC, VEGF-A, BCL-2, HIF1-α, MYB, PDGF-A, PDGFR-β, KRAS, and TERT  equaling to zero were excluded. Then, in each pathway, percentages of genes with TRRs having both CFo and CQo values higher than 50% were counted. Pathways with more than 50% genes’ transcripts identified as G4-important were regarded as G4-important pathways as listed in CFo and CQo values among iterations of each individual pathway . Based on this criterion, G4-important pathways could be grouped into six categories with distinct functions. As shown in All pathways composed of more than 50 genes available in KEGG PATHWAY database were extracted, and TnIc) as a model system to investigate possible biological functions of cardiac promoter G4s. As one of the central components in cardiac muscle contraction pathway, TnIc is also involved in most heart function related pathways. Furthermore, TRR of cTnI is highly G4 important according to our bioinformatics analysis . In the promoter of human TnIc, two types of G4-forming motifs were identified, which are designated as “MNSG4” (between −528 and −319 bp upstream to the TSS), and “−80 G4” (centred at −80 bp to the TSS)   a. Both TnIc. The fast migrating band of MNSG4-forming sequences (oligos MNS-ITr) in native gels indicated that intramolecular G4(s) is the only conformation at 5 µM oligo concentration. However, at similar concentration, slow migrating bands of −80 G4-forming sequence (oligo -80-IITr) were observed in a native gel, indicating it can adopt a mixture of intramolecular  and intermolecular G4s. EMSA results are shown in EMSA experiments were first used to probe the formation of G4s in the unlabeled MNS and −80 G4-forming sequences from the promoter of human MNS-ITr) may adopt parallel structure(s) in LiCl solution. In KCl solution, it is very likely that the majority of single repeat of MNSG4 adopts a similar folding pattern as the TBA (thrombin binding aptamer) and forms an anti-parallel G4 (or G4s) -80-ITr) may adopt a hybrid parallel/anti-parallel structure similar to the BCL-2 Pu39WT in LiCl solution +) were extracted and subjected to DMS footprinting.Comparative CD spectra analysis was also used to provide primary evidence of the formation and general conformations of both MNSG4 and −80 G4 in solution. Briefly, a single repeat of MNSG4 , by fitting the melting curve obtained at 295 nm, the melting temperature and unfolding enthalpy and entropy of the anti-parallel MNSG4 were derived to be 71.4±0.5°C, 170±11 kJ mol−1 and 494±31 J mol−1 K−1 respectively by a model as previously reported (-80-ITr), the parallel G4 with lower thermal stability, which accounts for 57.3% of CD signals at 263 nm, was almost fully denatured at 90°C, while no denaturing was observed for the other parallel species with high thermal stability. Since it has been shown by EMSA experiments that about 40% of the −80 G4 is able to adopt an intermolecular G4 conformation at 5 µM concentration, it is likely that the undenatured parallel species corresponds to intermolecular parallel G4s . In the process of MNSG4 opening, these fluctuating long loops may partially anneal to the C-rich strand, resulting in a series of relatively “ordered” intermediates with negative entropy, and the invasion of C-rich strand may further destabilise the folded G4 structures without transiting G4 into other partially unfolded structures (more disordered structures with positive entropies).Two subpopulations with different unfolding behaviors were revealed by fitting the unfolding curves of MNSG4, . The fasequation , and theS‡ than the −80 G4-S, the destabilising contribution from the loop  of −80 G4-F is more prominent than that from −80 G4-S, and thus less energy is required for the −80 G4-F to reach the transition state for the full hybridisation to happen. Indeed, a smaller ΔH‡ of −80 G4-F was also found.Similar experiments were carried out on the TnIc −80 G4, and two subpopulations (fast and slow unfolding components) were revealed with different kinetic behaviours . The fas1–3, Once it was established that these sequences can indeed form quadruplex structures, it was of interest to determine whether small molecules could facilitate the formation and stabilise the quadruplex structure. Over the past few years some of us have demonstrated that metal-containing compounds  can be excellent quadruplex DNA binder 2 and 3) bind strongly to MNSG4 with DC50 values under the 0.5 µM threshold for good binders. The mono-platinum compound 1, also displays some interaction but its DC50 value is twice as big as those of 2 and 3. Interestingly, there is a wider range of binding affinities towards the −80 G4 quadruplex with the di-copper compound (3) displaying a very low DC50 (i.e. strong binding), reasonably good affinity of 1 and poor affinity of di-platinum compound 2. Furthermore, we had reported that these compounds are very selective binders to G4 DNA over duplex DNA  assay. The results, which are summarized in Tm) in the presence of the ligand. In 10 µM compound 3, the CD spectrum of MNSG4 dramatically changed from parallel to hybrid of parallel/anti-parallel. The melting temperatures measured at 263 nm and 295 nm are 90.4±0.7°C and 86.2±2.1°C, respectively -WT) and Renilla luciferase ratios of lysates of transfected HEK293 cells incubated in the presence of ligands at different concentrations. Vector hTnIc-6MNS(E)-WT was used because it contains the greater number of G4 repeats, which was predicted to give the most significant response if the ligand-stabilisation of G4s is involved in determining the promoter activity. As shown in 1, showed a weak activating effect towards downstream gene transcription with the promoter activity being increased 2-fold at 100 µM concentration (EC50 = 812 µM). The di-platinum compound 2 exhibited modest activating effects towards downstream luciferase transcription with the promoter activity being increased by more than 3 times at 100 µM concentration (EC50 = 8.6 µM) (3) demonstrated most significant activation effect, which elevated the promoter activity by approximately 5-fold at 100 µM concentration (EC50 = 0.6 µM)   b. By re 0.6 µM)  c. TheseTnIc promoter G4s, firefly and Renilla luciferase ratios of different vectors were measured following incubation with and without the G4-binding ligand compound 3. We found that compared to the engineered wild type construct containing six repeats of consensus MNSG4, human TnIc constructs containing three, one repeat, or no repeat, exhibited similar activities in driving downstream luciferase transcription  has similar transcription activity to the engineered wild type promoter (hTnIc-6MNS(E)-WT). However, when the Sp1 binding site is mutated (hTnIc-80Sp1-M), transcriptional activity decreases by∼25%. Furthermore, when both the −80 G4-forming sequence and Sp1 binding site are mutated  which disrupts G4 formation, slightly elevated the transcriptional activity of activity  a. The dTnIc is exclusively expressed in cardiomyocytes, we suspect that the formation and stabilisation of these promoter G4s may be associated with certain cardiac-specific proteins or TFs, which are absent in HEK293 cells. Since it has been reported that short proximal promoter of human TnIc is sufficient to confer cardiac-specific expression 3. As shown in 3 for 24 hours before cell lysis, the expression activities of luciferase from all vectors increase differently. Generally, the transcription activity of human TnIc promoter gradually decreases when the number of MNSG4 repeat decreases, while the lowest transcription activities were observed in vectors with mutated −80 G4. It’s worth noting that in the presence of ligand, the overall mutant, hTnIc-6MNS/−80 G4-M, was also activated for about 4 times as compared to the wild type construct hTnIc-6MNS(E)-WT in the absence of ligand. This may relate to the interaction between the ligand and a G-rich region in the TnIc promoter (between −260 and −150 bp), which may adopt multiple two-tetrad G4s.We conclude that in the absence of G4-binding ligand, both the MNSG4 and −80 G4 are not involved in regulating downstream gene transcription in HEK293 cells, and the depressed transcription levels mainly relate to the disruption of the critical Sp1 binding site within −80 G4. As 3 were generated. As shown in 3. When the −80 G4 is intact, the activation effects of downstream luciferase decreases proportionally with the decrease of repeat number of MNSG4 (hTnIc-6MNS(E)-WT>hTnIc-3MNS(E)-WT>hTnIc-1MNS(E)-WT>hTnIc-299-WT). However, when the −80 G4 is mutated , lowest activation effects were observed again. These results suggest that the −80 G4, which is located in a region with high location significance (according to our hypothesis in bioinformatics studies), may operate as a gatekeeper in regulating downstream luciferase expression in HEK293 cells; the MNSG4, on the other hand, acts as to a fine tune regulation when the −80 G4 is intact. It is likely that both types of G4s orchestrate the gene expression of cardiac troponin I in the heart.To further discriminate activation effects of MNSG4 and −80 G4, dose-response curves of different luciferase vectors treated with compound in vivo, such as G4-induced guanine-protection revealed by in vivo DMS footprinting III porphyrin (104-fold) in vivo. However, off-target effects or multi-targeting effects of G4-binding ligands may in turn become advantageous and enhance their therapeutic potential in some cases as mentioned in the Introduction section. This implies that targeting multiple similar G4s in a particular pathway might be feasible, and furthermore, this could be an alternative to overcome selectivity problem of G4 ligands. Therefore, G4-pathway correlation is particularly important in applying G4s as potential targets for the treatment of certain diseases.The correlations between G4s and gene functions, and the regulatory roles of promoter G4s in proto-oncogenes have been thoroughly investigated previously, which has led to the application of several G4-binding ligands as potential anticancer drugs , the location significance of G4  is also considered when evaluating the biological importance of G4s in each TRR. Generally, correlation between F and Q scores in G4-less-important TRRs is not as strong as that in G4-important TRRs. Furthermore, we notice that when G4 importance increases, the probability of finding G4s in the proximal (−500 bp∼−1 bp) promoter regions of TRR increases. Because the majority of promoter G4s with proven regulatory functions locate in the proximal promoter regions, it is highly likely that the accumulation of proximal promoter G4s in pathways with high G4 importance is biologically relevant. In regions downstream the TSS, however, the probability is relatively constant, suggesting that the transcription induced G4 formation might be ubiquitous in different genes.Previous genome-wide studies have found that promoter G4s have a strong positional bias towards TSS in different species G4-important pathways show significant connection with their functions . ParticuTnIc was chosen as a model to investigate possible regulatory functions of G4s in cardiac function-related genes. Two G4 elements, the MNSG4 and −80 G4 were analysed separately. Results from CD, EMSA and DMS footprinting experiments have confirmed formation of these G4 elements in solution. Different folding patterns between these cardiac promoter G4s and proto-oncogene promoter G4s may relate to their distinct biological functions and therefore warrant further investigation by NMR spectroscopy.Because of its high G4 importance and unique expression pattern, the proximal promoter of human Oxytricha telomeric G4 MYC, VEGF, and KIT G4s have already been established, it is reasonable to assume that both TnIc MNSG4 and −80 G4 are stable enough to possess certain biological roles in the promoter of human TnIc in the context of adjacent duplex.The stability of MNSG4 and −80 G4 were both evaluated by their unfolding processes either thermodynamically and kinetically. Both have similar thermal stability  as compaTnIc promoter were mainly measured by comparing the transcription activities of engineered human TnIc promoter in HEK293 cells with and without the G4-binding ligand by dual luciferase reporter assays. This is based on the assumption that the G4-binding ligand, compound 3, is able to directly interact with these TnIc G4 elements in living cells, and subsequently to induce transcription activity changes. However, similar to most studies published so far, direct evidence indicating the interaction between G4-binding ligands and G4s in living cells is extremely difficult to obtain and could not be obtained in this study. However, several pieces of indirect evidence support the conclusion that the positive regulatory roles of these TnIc promoter G4s relate to the stabilisation of these elements by the ligand. The first evidence is the selectivity of the ligand to the TnIc G4 elements as compared to the dsDNA. Previous studies showed that compound 3 exhibits a relatively high selectivity to G4s as compared to dsDNA  and corresponding cumulative frequencies (the CF scores) on coding strand (a), template strand (b), and both strands (c). In the analysis, TRRs from 46,205 transcripts exported from ENSEMBL with redundancy were included. TRRs of transcripts without G4-forming motifs were excluded in calculating the distribution and corresponding cumulative frequency.(DOC)Click here for additional data file.Figure S2Probability distribution and location significance scores (the Q scores) distribution of G4s in TRRs of transcripts. (a) Frequency of PQS  at each position (kW as described in b∼d) Distribution of G4 location significance (lower graphs) and corresponding cumulative frequency (upper graphs) of all transcripts available in ENSEMBL database on the coding strands, template strand, and both strands, respectively. TRRs of transcripts without G4-forming motifs were excluded in calculating the distribution and corresponding cumulative frequency.(DOC)Click here for additional data file.Figure S3Correlation between the location significance (the CQ score) and abundance (the CF socre) of G4s identified in TRRs of all transcripts with redundancy. (a∼c) Correlation between G4 location significance and G4 abundance on the coding strand (CQcd vs. CFcd), template strand (CQncd vs. CFncd), and both strands (CQo vs. CFo), respectively. In each map, transcripts with the TRRs CQ and CF scores larger than 50% are identified as G4-important transcripts, and those with both values smaller than 50% are G4-less-important (or less G4-important) transcripts. Correlation coefficients between CF and CQ on coding strand (CFcd vs. CQcd), template strand (CFncd vs. CQncd), and both strands (CFo vs. CQo) are 0.57, 0.50, and 0.61, respectively. However, corresponding correlation coefficients for G4-important TRRs are 0.61 (coding strand), 0.58 (template strand), and 0.66 (both strands), respectively, while those for G4-less important TRRs are 0.10, 0.09, and 0.34 respectively. Apparently, in G4-important TRRs, their G4 abundance is more positively correlated to their G4 location significance.(DOC)Click here for additional data file.Figure S4Native and denaturing gel electrophoresis indicating the formation of G4s. (a) TnIc MNSG4, 1 repeat: Lane1 and 2 are oligos MNS-IITr (C-rich) and MNS-ITr (G-rich) run in a native gel. Lane 3 and 4 are oligos run in a denaturing gel as controls. (b) TnIc −80 G4: Lane1 and 2 are oligos -80-IITr (C-rich) and -80-ITr (G-rich) run in a native gel. Lane 3 and 4 are oligos run in a denaturing gel as controls. Formation of intramolecular G4s is proved by species with fast mobility under native conditions (indicated by black arrows) but not under denaturing conditions. Intermolecular G4s formed by the −80 G4 forming sequence are indicated by gray arrows in (b).(DOC)Click here for additional data file.Figure S5DMS footprinting results of TnIc MNSG4 and −80 G4. (a) DMS footprinting of MNSG4 (oligo MNS-ITr). Strong DMS protection is observed at G1∼G3, G5∼G7, G11∼G13, and G14∼G15. Two guanines at the 3′ of MNSG4  are not involved in G4 formation. Compared to other guanines involved in loops , G10 is partially protected from DMS. Because G13 is fully protected from DMS, this partial protection of G10 may be due to the gyration hindrance from the adjacent G4 structure, which blocks its access by DMS. (b) DMS footprinting of −80 G4 (oligo MNS-ITr). In the first 5′ run of guanines (G1∼G5), partial protection of guanines is apparent. Meanwhile, in the second and third runs of guanines (G9∼G12 and G13∼G16), partially protected flanking guanines in each G-run are also found (G9/G12 and G12/G16) with two fully protected guanines in the middle (G10∼G11 and G14∼G15). This poorly defined footprinting pattern of −80 G4 element is possibly due to the long first loop (at least 7 nucleotides) which induces flexibility of the G4 conformations. Together with CD experiments, it’s highly likely that this sequence can fold into a mixture of exchanging parallel intramolecular G4s with different loop arrangements in KCl solution. Furthermore, in the second and third G-runs, it is clear that G12 and G13 are better protected from DMS than G9 and G16, which may reflect the preference of different intramolecular G4s.(DOC)Click here for additional data file.Figure S6CD melting of the two promoter G-quadruplex sequences. (a) single-repeat MNSG4. (b) −80 G4.(DOC)Click here for additional data file.Figure S7Arrhenius plot for unfolding of TnIc G4s. (a) Arrhenius plot for the slow decaying component identified in the unfolding process of TnIc MNSG4. Empty circles represent opening rates measured at different temperatures, and red line is the result fitted by Arrhenius equation. The activation energy is determined to be 22.1±0.4 kJ mol−1. (b) Arrhenius plot for the slow and fast decaying components identified in the unfolding process of TnIc −80 G4. Empty triangles and squares represent opening rates of the fast and slow decaying components, respectively, and red lines are results fitted by Arrhenius equation. The activation energies for the fast and slow decaying components are 86.1±23.7 and 100.6±6.6 kJ mol−1, respectively, as determined by the fits.(DOC)Click here for additional data file.Figure S8CD melting of TnIc MNSG4 and −80 G4 in the presence of the G4-binding ligand (complex 3). (a) CD melting spectra of TnIc MNSG4  in the presence of 10 µM complex 3. (b) CD signal changes of TnIc MNSG4 (oligo MNS-I)Tr at 295 nm (black dots) and 263 (red dots) nm wavelengths in response to temperature changes, both of which were fitted by a sigmoidal model (indicated by red line and black line respectively). The melting temperature measured at 265 nm and 295 nm are 90.4±0.7°C and 86.2±2.1°C respectively (c) CD melting spectra of TnIc −80 G4  in the presence of 10 µM complex 3. (d) CD signal changes of TnIc −80 G4 (oligo -80-I)Tr at 295 nm (black dots) and 263 (red dots) nm wavelengths in response to temperature changes, both of which were fitted by a sigmoidal model (indicated by red line and black line respectively). All experiments were carried out in 10 mM Tris-HCl buffer (pH 7.4) containing 100 mM K+.(DOC)Click here for additional data file.Figure S9Comparison of the transcription activities of human TnIc promoters containing variable number of MNSG4. Transcription activities of human TnIc promoters containing 6 repeats of consensus MNSG4 (hTnIc-6MNS(E)-WT), 3 repeats of consensus MNSG4 (hTnIc-3MNS(E)-WT), 1 repeat of consensus MNSG4 (hTnIc-1MNS(E)-WT), and no repeat of MNSG4 (hTnIc-299-WT). No transcription activity difference was found among these human TnIc promoters .(DOC)Click here for additional data file.Figure S10Transcription activities of human TnIc promoters with wild type and mutated −80 G4. Mutation of −80 G4 alone (hTnIc-80 G4M) did not change the transcription activity, while the mutation of Sp1 binding site (hTnIc-80sp1M-1/2) led to∼25% depression in the transcription activity. When both G4 formation and Sp1 binding sites were mutated (hTnIc-80 G4/sp1M), 50% decrease of the transcription activity was found (* P<0.05 and ♯ P≥0.05 no significant differences).(DOC)Click here for additional data file.Table S1The rankings and scores of G4 enrichment in TRRs of genes active in different tissues. G4s in the full-length TRR (Whole TRR), distal promoter region , proximal promoter region (−500∼−1 bp), and downstream region  were searched and the procedure was repeated randomly for five times.(DOC)Click here for additional data file.Table S2CFo and CQo values of TRRs of genes containing well-studied promoter G4s.(DOC)Click here for additional data file.Table S3Parameters obtained from curve fittings of TnIc MNSG4 and −80 G4 unfolding in solution.(DOC)Click here for additional data file.Protocols S1Supporting protocols including G4-binding ligand synthesis, Electrophoretic mobility shift assay, CD characterization, DMS footprinting, unfolding kinetics and the human genome sequence data bases used in the bioinformatic analysis.(DOC)Click here for additional data file.


Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1), encoded by the var gene family, plays a crucial role in disease virulence through its involvement in binding to various host cellular receptors during infection. Growing evidence suggests that differential expression of the various var subgroups may be involved in parasite virulence. To further explore this issue, we have collected isolates from symptomatic patients in south China-Myanmar border, and characterized their sequence diversity and transcription profiles over time of var gene family, and cytoadherence properties from the time of their initial collection and extending through a two month period of adaptation to culture. Initially, we established a highly diverse, DBLα (4 cysteines) subtype-enriched, but unique local repertoire of var-DBL1α sequences by cDNA cloning and sequencing. Next we observed a rapid transcriptional decline of upsA- and upsB-subtype var genes at ring stage through qRT-PCR assays, and a switching event from initial ICAM-I binding to the CD36-binding activity during the first week of adaptive cultivation in vitro. Moreover, predominant transcription of upsA var genes was observed to be correlated with those isolates that showed a higher parasitemia at the time of collection and the ICAM-1-binding phenotype in culture. Taken together, these data indicate that the initial stage of adaptive process in vitro significantly influences the transcription of virulence-related var subtypes and expression of PfEMP1 variants. Further, the specific upregulation of the upsA var genes is likely linked to the rapid propagation of the parasite during natural infection due to the A-type PfEMP1 variant-mediated growth advantages. Plasmodium falciparum is the most virulent species of malaria that infects humans. Erythrocytes infected with this parasite adhere to different types of endothelial cells in the deep vasculature of the body to avoid being cleared by the spleen P. falciparum erythrocyte membrane protein 1 (PfEMP1), encoded by members of a multi-gene family (the var genes) in vivo which serves to compromise the immune defense of the host Var gene family can be separated into three major groups based upon conserved sequence features  upstream of the protein coding region var genes are associated with severe children malaria, while group C var genes are linked to asymptomatic malaria. In support, large-scale sequence analysis of var-DBL1α domains revealed that the lack of 1 or 2 cysteines in this region, most belonging to group A or B/A var genes, was associated with severe malaria var genes play a crucial role in the pathogenesis of different forms of malaria, little is known of the underlying mechanism.P. falciparum contains approximately 60 copies of this gene family, and the collection of clonal types of field isolates that constitute the global population of this parasite seems to be nearly endless. Nevertheless, studies on geographically diverse populations support the existence of structured var repertoires among various geographic areas, although their sequences are highly diverse within each repertoire var repertoires of field isolates in Africa and South America, however, little is known of the parasites in southern China-Myanmar border, a highly epidemic area in Asia The individual clonal type of in vitro cultivation. For that reason, much of the information we have about var genes comes from transcriptional data. The direct investigation of protein properties would be ideal, but most often such experiments are not done due to the degree of difficulty involved in studying each member and the high number of molecules involved. Further, the study of PfEMP1 in vitro is potentially impacted by artifacts relating both to the effects on the parasite of extended periods in culture and the technical necessity to equate RNA expression with protein presence and hence function. Peters et al have shown such effect on var gene transcription of experimentally infected 3D7 strain during adaptive cultivation in vitro adaptation of patient isolates to laboratory populations where the dominant selective forces are different than those affecting the parasite in its native state.In a clonal population the most abundant transcript(s) found in each blood-stage cycle is thought to be expressed and therefore reflective of adherent specificity during var gene transcripts, their transcription patterns during the life cycle of the parasite, and their cytoadherent characteristics from in vivo to in vitro over the course of ∼2 months. In so doing we hoped to clarify the influence of the adaptive process on the transcription as well as expression of var genes, and look for potential link between PfEMP1 expression and parasite characteristics starting from each isolate's collection point, and extending through many generations of in vitro culture. Our data revealed a potential correlation between the predominant transcription of upsA-subtype var genes and the parasitemia of parasites found in the blood when the isolates were collected, which partially reflected the growth rate of parasite in vivo. We therefore suggest that A-type PfEMP1 variants-mediated high parasitemia contributes to the virulence of parasites in natural infection.In this study, we investigated the composition of var transcripts from 9 clinical isolates collected from symptomatic malaria adult patients with multi-infection history in the Yunnan province of south China . In contrast, the overall distribution of these motifs in var transcripts was similar to that of non-severe malaria cases found elsewhere Initially, we analyzed the th China  and S1, p<0.01). It is worth noting that the African children analyzed here were generally severe malaria patients including cerebral malaria, whereas the 3D7 clonal type has been adapted for cultivation condition in vitro for numerous generations. This result further demonstrates that the specific transcription of var subgroup with 4 cysteines in their DBL1α domain is associated with non-severe malaria under selection of host immune pressure. Further, a phylogenetic analysis with all of the DBL1α tags from Yunnan isolates revealed a unique cluster corresponding to upsA var genes in 3D7 strain. n-PoLV4-length” his area  [19], [2MSP-2), by PCR-RFLP analysis as described previously var-DBL1α cDNA sequence reads per sample by sequencing of clones  (var-DBL1α sequences cloned from their genomic DNAs did not indicate a higher proportion of upsA var genes (data not shown). Isolates with upsB or upsC dominant var transcripts exhibited much lower parasitemia in peripheral blood.Among these samples, interestingly, three isolates with higher parasitemia, i.e. A15, A16 and A19, exclusively transcribed dominant (p<0.01) , while tupsA var transcripts and higher density of ring-stage parasites in peripheral blood. This raises the question of whether the transcription status of upsA and other vars are constant during adaptation to culture. Previously it has been reported that the overall abundance of upsA, -D and -E transcripts of ex vivo samples declined dramatically after a short period (the first ∼10 days) of in vitro cultivation var gene families at both ring and trophozoite stages of individual isolates over a two month period of in vitro cultivation through quantitative reverse transcription PCR (qRT-PCR) with var subtype-specific primers. Due to the limited material of parasites in the initial stage during cultivation, two assays were designed for different analysis strategies. Six isolates were cultivated for 14∼16 days and entire culture were used to monitor var transcription at both ring and trophozoite stages of development, whereas the other eight isolates were maintained in culture for up to ∼2 months while monitoring both adhesive properties and trophozoite-stage transcription over the entire period , in which one sub-clone had taken over the culture in vitro, no significant decrease of the two above-mentioned subtypes had occurred in these samples , F08B-34 (30 days) and LZF22 (45 days). Interestingly, isolate F08B-33 bound to ICAM-1 at the start of the study and then switched to CD36 over the first week in culture. Combined with the transcription analysis of these isolates corresponding to these timepoints, we observed a potential link between the ICAM-1 binding phenotype and dominant transcription of ar genes  and S2.var primary sequences through frequent recombination among field strains, and the switching expression of var genes in different generations contribute to the complexity of the malaria pathogen var gene sequences have been extensively investigated in terms of conserved features of functional regions as DBL1α domain in highly epidemic area in Africa or South America var gene repertoire in this area with limited overlap to other populations. This observation points to the existence of geographic population structures in various areas as previously observed by analysis of microsatellite or single nucleotide polymorphism var gene types was under selection of host immune pressure The worldwide high diversity of var gene expression and severity of malaria disease investigated in several geographical isolates from Africa, it is recognized that the expression of upsA- and partial upsB (B/A)-subtype var genes correlates to the severe malaria disease upsB and upsC vars were appeared to be overlapping, however, upsA vars could be distinguished from other subtypes. It was therefore feasible to investigate the possible link between upsA vars and parasite virulence. Interestingly, we found that the upsA vars transcription had a potential link to the higher parasitemia of isolates in peripheral blood by different strategies (cDNA cloing/sequencing and qRT-PCR). Since these samples are collected from those patients under the same criteria including the symptom, age, sampling location and time point after the occurrence of disease, infection history, etc., it is likely that the expression of group A PfEMP1 confers the more effective growth rate on the parasites, probably due to better sequestration to avoid the clearance by the host immune system. This point is supported by another independent study with ex vivo samples which showed that NF54 parasites expressing group A and B vars had expanded more effectively in vivo compared to those expressing other var genes in experimentally infected humans upsA vars would not be the only determinant to control the growth rate of parasites in natural infection. As we observed, the isolate F08B-33 exhibited a dominant transcription of upsA vars as well as ICAM-I-binding activities, however, it did not show a significantly higher parasitemia compared with other isolates. Hence, further experiments using more malaria isolates with various severities are needed to confirm the correlation between in vivo growth rate and var gene expression pattern (transcription and protein level) and the underlying mechanism. In addition, dynamic transcription analysis by qRT-PCR at different developmental stages in individual cycles revealed a link between the ICAM-1 binding phenotype and transcription of upsA vars, which supports the previously observed association between upsA-subtype vars and severe malaria since ICAM-1-mediated cytoadhesion has been implicated in pathogenesis of severe malaria Although there are some inconsistency among those studies on the association between P.falciparum clone selected by a monoclonal antibody against a specific PfEMP1 or a unique receptor as CSA, it has been generally accepted that only one var gene is dominantly transcribed throughout the blood-stage cycle, and translated into the specific PfEMP1 protein which is exported onto the surface of the iRBC and mediates the cytoadhesion phenotype of the culture var gene in a single cycle is expected to be translated into the PfEMP1 mediating a specific phenotype. However, due to the qRT-PCR technique with subtype-specific var primers for var transcription profiling had been validated only in rings, the transcriptional dominance order among various vars in trophozoites might not reflect the actual status. It has also been demonstrated that var transcriptional levels in trophozoites are 10–100 times lower than that in rings upsBC1 level was almost similar between rings and trophozoites. Considering that the upsBC1 and BC2 primer pairs are targeting the exon 2 region of var genes var transcripts due to the intron promoter activity as reported previously var gene transcription profile in this stage might be biased by the sterile transcripts. Therefore, since the PfEMP1 product appeared on the iRBC surface at ∼16 hr post invasion var transcripts in rings, including the uspA vars, would be responsible for the cytoadhesion phenotypes in the late stage, which is consistent with our observation that the higher transcription level of uspA vars in rings is linked to the higher parasitemia in vivo and ICAM-1-binding in vitro.In a homogeneous laboratory vars expression pattern in culture in vitro was considered as an obstacle in evaluating their functions. A recent study with “ex vivo” 3D7 samples had shown a rapid down-regulation of overall transcription level of var genes at ring stage, especially the upsA, -D and -E had a significantly faster rate of transcriptional reduction in the first ∼10 days of culture upsB vars. In addition, the transcription profiling in trophozoites were not performed. In the present study, transcription measurement of var genes at both ring and trophoziote stages over the course of ∼2 month post-thaw did undergo a rapid turn over event for upsA subset as well as upsB/A vars in the second cycle, indicating the virulence-related var subtype are more sensitive to the absence of immune pressure or other signals in host during the first cycle in vitro. Surprisingly, the declined vars were up-regulated again immediately after the fourth cycle in culture, which was not observed in the previous “ex vivo” 3D7 samples. It seems that the naturally infected isolates are able to adapt to the in vitro culture condition more rapidly than the parasites of passive infection.The potential turn over of var genes encode CD36-binding PfEMP1 variants in 3D7 strain in vitro even though no apparent difference of var transcription in trophozoites was observed, which may be also linked to the role of upsA var transcripts in rings.It is well known that the CD36-binding phenotype was the most common in cultivated field isolates from patients with various symptoms, and group B and C var repertoire, a dynamic transcription profile of the different subsets of var genes, and a cytoadherence analysis of parasites from malaria patients during a adaptive cultivation in vitro. Our results showed a restricted var-DBL1αrepertoire in this area, and a greater proportion of var genes containing a Cys4 DBL1α domain than seen in similar studies in Africa. This work extends the global database of var gene repertoire in various geographic isolates. Further, our data raised a new role of the ring-stage transcribed subset of var genes (upsA subtype) in development of malaria parasite in patients. Here we suggested the A-subtype PfEMP1 variants might be linked to the rapid growth rate of isolates in vivo. Finally, it should be cautious in interpreting the experimental data and understand the nature of var gene family from the in vitro cultivated parasites due to the observation of a rapid switching of var transcription and cytoadherent phenotype of field isolates during the initial cultivation process.In summary, we conducted a systematic analysis of sequence diversity of the In this study, patients who sought medical care at the local Center for Disease Control and Prevention (CDC) in Yunnan from 2006 to 2008 were recruited with written informed consent, and the clinical protocol was approved by the Internal Review Board of Second Military Medical University, China.Plasmodium falciparum FCC1/HN line was isolated from Hainan Island, China, established as a laboratory culture in 1979 and subsequently adapted to cultivation in RPMI 1640 medium (Invitrogen) containing 25 mM Hepes, 2 mM L-glutamine, and supplemented with 0.1 mM hypoxanthine (Sigma), 20 µg/ml gentamicin (Sigma), 15% rabbit serum and 2–4% (v/v) type O+ erythrocytes under the condition of 5% CO2 at 37°C P. falciparum infection than the rest of the population because their occupation leads to exposure to Anopheles minimus, a potent malaria vector. Blood samples came from patients who sought medical care at the local Center for Disease Control and Prevention (CDC) in Yunnan from 2006 to 2008. Malaria diagnosis was done by microscopic examination of blood smears. Parasitemia was measured relative to leukocyte numbers per µl of blood, with an average of 5000 leukocytes/µl of blood. In this study, we selected symptomatic malaria patients who were >5 years of age (most were adult). In general, they had P. falciparum in peripheral blood with parasitemia >1000 infected red blood cells (iRBC) per µl of blood, an axillary temperature <40°C, and a history of fever. Basically, patients with severe malaria, including cerebral and placental malaria, were treated immediately and hence excluded from this study except two samples with symptom between mild and severe malaria  and Myanmar. Malaria in this area is subject to seasonal variation with an increased incidence level occurring from July to September. Adult male farmers are at higher risk for var-DBL1α domain by cDNA clone and sequencing. Hence, the fresh blood samples from patients were mixed with anticoagulant, EDTA and RNAlater solution, a RNA protection reagent (Ambion). Then the samples were frozen at −80°C until total RNA extraction. Totally 22 samples were collected for this aim, and 15 isolates were randomly selected for total RNA extraction. However, only 9 samples were analyzed for var gene diversity since others did not produced sufficient var-DBL1αsequences by cDNA cloning with total RNAs of poor quality . Cultures were grown in media with type O+ erythrocytes at a 3% hematocrit under 2% O2, 5.5% CO2, 92.5% N2 at 37°C Frozen isolates from malaria patients were thawed for analysis as described previously in vitro cultured samples. For the cultivated parasites, the rings of 10–20 hr or trophozoites of 25–35 hr post invasion were harvested, respectively. RNA was extracted with Trizol (Invitrogen) according to the manufacturer's instruction with modification as described elsewhere var-DBL1α domain DBL1α sequences were amplified using the following primers: DBLαAF, 5′GCACG(A/C)AGTTT(C/T)GC3′, and DBLαBR, 5′GCCCATTC(G/C)TCGAACCA3′ Total RNA was isolated both directly from frozen patient blood samples and from http://www.ebi.ac.uk/clustalw/) using the default settings . Unrooted phylogenetic trees (based on amino acid sequences) were constructed by p-distance/neighbour-joining (NJ) method with 1000 bootstrap replicates using MEGA version 3 Sequences edited with DNAstar software (version 6) aligned in batches using ClustalW analysis . All primers had amplification efficiencies (E) between 1.80 and 2. The relative copy numbers of amplified subtype var genes by these primers were compared to the internal single-copy control gene, Seryl-tRNA synthetase. The amplification efficiency for field isolate gDNA was similar to that for 3D7 gDNA for upsA1, A2, A3, B2, BC1, C2, Var1 (upsD) and Var2 (upsE). Because there are overlapping members between BC1 and BC2, C1 and C2, respectively, we used the primers of upsA2, B2, BC1, BC2, C1, C2, D and E subgroup in this study.Primers specific for subtype or individual PF07_0073) to confirm the lack of genomic DNA contamination. 500 ng total RNA was subjected to reverse transcription reaction with a mixture of oligo dT and random hexamer primers as reverse primers in a 20 µl reaction according to the manufacture's recommendations (Invitrogen). Negative control reactions were performed in the same conditions without reverse transcriptase. All runs were performed using an Applied Biosystem 7300 detection system in a 20 µl reaction contained 0.5 µl cDNA, 1×SYBR Green I Mastermix, 0.2 µM specific primer pair for individual gene or var gene subtypes tested, and each reaction was run in duplicate. Seryl-tRNA synthetase was used as endogenous control gene. The qRT-PCR reaction conditions were as follows: 95°C for 10 s, followed by 40 cycles of 94°C for 20 s, 50°C for 20 s and 62°C for 20 s.Parasite cultures were tightly synchronized by sorbitol lysis for total RNA extraction. Total RNA of synchronous parasite culture was extracted using Trizol reagent (Invitrogen) according to the protocol as described previously Ct) is defined as the cycle number at which the quantity of fluorescence product passes a pre-determined threshold. The relative amounts were calculated using the equation: ΔCt  =  Ctvar subtype - CtSeryl-tRNA synthetase. ΔCts were then converted to relative copy numbers with the formula 2ΔCt-. Dissociation curves were generated and the homogeneity of the products were verified by observation banding pattern after electrophoretic separation of the reaction mix.Transcripts were quantified as follows: the threshold cycle (2) were counted in 25 continuous fields by light microscopy.Cytoadherence assays were carried out as described upsA and other group. Difference was considered significant if P value was <0.05 (2-tailed). The distribution analysis of var-DBL1α sequences were were compared using χ2 test. “*”: p<0.01 between tested group and control.SPSS16.0 software was used to perform Mann-Whitney U test to evaluate the difference of parasitemia between Figure S1Transcriptional pattern and cytoadherent features of unselected P.falciparum FCC1/HN line. (A) Synchronized trophozoite-stage parasites were used to measure the transcriptional level of various subtype var genes. (B) Cytoadherence assay of FCC1/HN line with CD36, ICAM-1, CSA, and HA purified receptors with BSA as negative control.(TIF)Click here for additional data file.Figure S2The ring-stage transcription profile of var gene family in LZF22 isolate. The analysis was started after two weeks post-thaw based on the stuff amount. The Seryl-tRNA synthetase gene was used as the endogenous control. The time point when the upsA vars were dominantly transcribed is indicated by arrow.(TIF)Click here for additional data file.Table S1Clinical assessment of symptomatic malaria patients recruited in this study (supplementary to (DOC)Click here for additional data file.Table S2Plasmodium falciparum DBL1α contigs of var transcripts in field isolates from symptomatic patients in Yunnan-Myanmar area.(DOC)Click here for additional data file.Table S3Genotyping of six isolates during the period of adaptive cultivation with microsatellite assay (linked to (DOC)Click here for additional data file.


PAF complex (PAFc) is an RNA polymerase II associated factor that controls diverse steps of transcription. Although it is generally associated with actively transcribed genes, a repressive PAFc has also been suggested. Here, we report that PAFc regulates the transition from transcription initiation to transcription elongation. PAFc repressed IL-6-induced, but not TNF-α-induced, immediate early gene expression. PAFc constitutively associated with the 5′-coding region of the c-Fos locus, then transiently dissociated upon IL-6 stimulation. When CTR9, a component of PAFc, was depleted, higher levels of serine 5-phosphorylated or serine 2-phosphorylated forms of RNA Polymerase II were associated with the unstimulated c-Fos locus. We also observed an increased association of CDK9, a kinase component of the pTEF-b elongation factor, with the c-Fos locus in the CTR9-depleted condition. Furthermore, association of negative elongation factor, NELF, which is required to proceed to the elongation phase, was significantly reduced by CTR9 depletion, whereas elongation factor SPT5 recruitment was enhanced by CTR9 depletion. Finally, the chromatin association of CTR9 was specifically controlled by IL-6-induced kinase activity, because a JAK2 kinase inhibitor, AG-490, blocked its association. In conclusion, our data suggest that PAFc controls the recruitment of NELF and SPT5 to target loci in a signal- and locus-specific manner. Transcription occurs in three phases: initiation, elongation, and termination. General transcription factors recognize promoter sequences and recruit RNA polymerase II (Pol II) to form a preinitiation complex (PIC), the first step of messenger RNA (mRNA) synthesis c-Fos, junB, and c-myc, which are rapidly induced by external stimuli Among these blocked genes are the immediate early genes (IEGs), such as While moving through the template DNA, eukaryotic RNA Pol II encounters nucleosomes. The concerted actions of histone modifying enzymes, ATP-dependent chromatin remodelers, and histone chaperones are necessary for the efficient movement of RNA Pol II through nucleosomes in vitroPAFc is an evolutionarily conserved RNA Pol II-associated complex that is composed of Paf1, Ctr9, Cdc73, Rtf1, and Leo1 in yeast c-Fos transcription was explored.Previously, we reported that PAFc participates in the transcriptional activation of acute phase protein (APP) genes through the direct interaction of CTR9 and STAT3 c-Fos gene, 1.3 kb fragment containing 0.4 kb promoter and 1.1 kb coding region of c-Fos, and a total 3.5 kb c-Fos genomic region fragment were obtained by PCR with appropriate primer sets and cloned into pGL3 basic vector . 0.9 kb c-Fos first intron was obtained by PCR with appropriate primer sets and cloned into pGL3 control vector . The sequences of the primers for PCR are provided in A full-length cDNA of mouse Ctr9 was obtained in the laboratory of S. Desiderio, as previously described 2 atmosphere. For cytokine stimulation, cells were treated with rhIL-6 (20 ng/ml) plus IL-6sR (20 ng/ml) for indicated times . Transient transfection was carried out using Lipofectamine 2000  according to the manufacturer's instructions.HepG2 cells were maintained in MEM  supplemented with 10% fetal bovine serum  and maintained at 37°C in a 5% CO5′-UUCUCCGAACGUGUCACGUTT-3′, CTR9: 5′-CCGUGUGGCUCCAAACUUUATT-3′, LEO1: 5′-GCCGGUAGCUUCUGAUAAUTT-3′, CDC73: 5′- GGUACAUGGUAAAGCAUAATT-3′, PAF1: 5′-GCAG UUUACCGAGGAAGAATT-3′, NELF-E: 5′-GACCCAGAUUGUCUACAG UTT-3′, SPT5: 5′-GGACUGUCAAAUGUAAGAUTT-3′.Oligomer sequences used for RNA interference are as follows; Control: 15 primer or random hexamer , respectively, and M-MLV reverse transcriptase . For the Nuclear/Cytoplasmic fractionation, PARIS kit  was used, according to the manufacturer's instructions. The sequences of the primers for PCR are provided in Total RNA was extracted from cells using the RNAiso Plus . For conventional or real time PCR, 1 µg of total RNA was reverse-transcribed using oligo-d (T)ChIP was performed as previously described 3VO4 (5 mM) were added additionally to detect phosphorylated forms of RNA polymerase II during the immunoprecipitation. Antibodies against CTR9, PAF1, CDC73, and LEO1 were purchased from Bethyl Laboratory . Antibodies against STAT3, phospho-STAT3(Y705), TBP, c-Myc and NELF-E were purchased from Santa Cruz Biotechnology. Antibody against GAPDH was purchased from Chemicon .HepG2 cells were lysed in lysis buffer . Total cell lysates (40 µg per sample) were resolved using SDS-polyacrylamide gels. For immunoprecipitation, 1 mg of lysate was incubated with 2 ug of antibody overnight. NaF (25 mM), β-glycerol phosphate (25 mM) and Na2, 10 mM PIPES (pH 6.8), 1 mM EGTA, 0.2% Triton X-100, and protease inhibitors . Cells were then centrifugated, and the supernatant was collected as the “unbound” fraction. The remaining pellet was further incubated with 0.5 U/µl DNaseI containing buffer 37°c for 30 min, centrifugated, and the supernatant was collected as the “bound” fraction.Chromatin-bound and –unbound fractions were prepared as previously described fibrinogen (FGG) and haptoglobin (Hp), by stabilizing the binding between STAT3 and chromatin at promoters c-Fos, which is transcriptionally induced by IL-6 in hepatocytes. The proto-oncogene c-Fos contains a canonical STAT3 binding site in its promoter region and is known to be directly controlled by IL-6-activated STAT3 c-Fos transcription under both basal and IL-6-induced conditions  genes, such as nditions A and 1Bnditions A [17].  pathway C. In coc-Fos mRNA prepared from the cytoplasmic fraction, the most dramatic effect was observed in the RNA prepared from the nuclear fraction. The knockdown effect of CTR9 on c-Fos transcription was observed in unspliced transcripts, and overexpression of mouse CTR9, which is insensitive to human CTR9 siRNA, successfully reversed the hyper-induction of c-Fos in the CTR9 knockdown condition (c-Fos significantly (A). Since CTR9 is relatively abundant than other PAFc components in yeast c-Fos transcription . These data demonstrate that PAFc plays a negative role in the transcriptional control of c-Fos in the nucleus.PAFc is known to be involved in multiple transcriptional steps, including initiation, elongation, and the 3′-end processing of mRNA ondition E. Howevficantly A. Sincecription F. Althopression B. Thesec-Fos, the elongation step is critical c-Fos is pre-occupied by RNA Pol II to form a pre-initiation complex that is stalled by an elongation block present in the first intron of c-Fosin vitroc-Fos transcription.During the transcriptional control of c-Fos genomic locus was first examined by ChIP analysis using antibodies that detect the serine 5-phosphorylated or serine 2-phosphorylated forms of RNA Pol II. RNA Pol II phosphorylated on the serine 5 residue of the CTD (Ser5P RNA Pol II) was mainly detected in the TSS region of c-Fos under basal conditions, and this association was further enhanced by IL-6 stimulation  complex is known to inhibit elongation of the c-Fos gene c-Fos locus using the ChIP assay. Under basal conditions, significant amounts of NELF-E were present only in the TSS region, while almost no signal was detected in the 3′ region. Upon IL-6 stimulation, NELF-E rapidly dissociated from the TSS  complex, with the mulation C. Howevmulation D. Baseded cells E. Howeved cells F. Takenc-Fos transcription directly, we examined the chromatin association patterns of PAFc with the c-Fos locus under basal and IL-6 stimulated conditions. CTR9 was primarily associated with the TSS region of c-Fos in the absence of stimulation  for the indicated length of time. Left, western blot assay was performed to detect exogenous Myc-CTR9. Right, c-Fos mRNA levels were measured by RT-qPCR analysis. Expression levels were normalized to β-Actin. B. Cells were transfected with Myc-Paf1 or Myc-Cdc73. 48 hours later, cells were treated with IL-6 plus IL-6sR (20 ng/ml each) for 1 hour and PAF1, CDC73 and GAPDH proteins levels were analyzed by westernblot analysis using endogenous antibodies. c-Fos mRNA levels were measured by RT-qPCR analysis.(EPS)Click here for additional data file.Figure S2Top, diagram of the Hp genomic loci. PCR primers used for ChIP analyses are shown as two-sided arrows. HepG2 cells were treated with IL-6 plus IL-6sR (20 ng/ml each) for the indicated length of time. Soluble chromatins were immunoprecipitated with anti-CTR9 antibodies, and the bound DNAs were analyzed by quantitative PCR using primers specific to Hp loci. Error bars represents SD (n = 3).(EPS)Click here for additional data file.Table S1Primer sequences used for PCR experiments.(DOC)Click here for additional data file.