In this study, we investigated the genes G0S2, CDKN1A and MYC as master examples of primary vitamin D receptor (VDR) targets being involved in the control of cellular proliferation. The chromosomal domains of G0S2 and CDKN1A are 140–170 kb in size and contain one and three VDR binding sites, respectively. This is rather compact compared to the MYC locus that is 15 times larger and accommodates four VDR binding sites. All eight VDR binding sites were studied by chromatin immunoprecipitation in THP-1 cells. Interestingly, the site closest to the transcription start site of the down-regulated MYC gene showed 1,25(OH)2D3-dependent reduction of VDR binding and is not associated with open chromatin. Four of the other seven VDR binding regions contain a typical DR3-type VDR binding sequence, three of which are also occupied with VDR in macrophage-like cells. In conclusion, the three examples suggest that each VDR target gene has an individual regulatory scenario. However, some general components of these scenarios may be useful for the development of new therapy regimens.Genome- and transcriptome-wide data has significantly increased the amount of available information about primary 1,25-dihydroxyvitamin D The immortalized cell models, lymphoblastoid and LX2 cells, essentially capture normal VDR signaling, while THP-1 leukemia cells display significant phenotypic responses towards 1,25(OH)2D3 exposure in terms of triggering differentiation. In contrast, LS180 cells have a resistant phenotype with loss of sensitivity towards the anti-proliferative actions of 1,25(OH)2D3, i.e., they are less suited as a representative cancer model.The hormonal form of vitamin Dor (VDR) , later for (VDR) . In addiunteers) . The numunteers) . These mTraditionally within the field of VDR research, single gene studies had supported the concept that the VDR binds preferentially to sequences formed by a direct repeat of two hexameric binding motifs spaced by three nucleotides (DR3) ,10; this2D3 and then preferentially forms complexes with co-repressor proteins [2D3 to VDR’s ligand-binding domain induces a conformational change to the latter, so that VDR changes its interaction partners, a few of which have chromatin modifying activity like histone acetylation [2D3 signaling [2D3 target genes had been distinguished into those that are up-regulated, down-regulated or not affected by HDAC inhibitor treatment [In order to obtain access to its genomic binding sites, VDR has first to overcome the intrinsic repressive nature of chromatin ,14. At aproteins ,16 and cproteins ,18. Howetylation . Therefoignaling . HDAC inignaling , have threatment .When a transcriptional start site (TSS) lies within open chromatin, a basal transcriptional machinery complex is able to assemble there. In cases when ligand-activated VDR binds to the same chromosomal domain, the looping of the receptor towards the core promoter region can initiate or enhance the transcription of the respective gene. The method Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE) combined with massive parallel sequencing (FAIRE-seq) allows a genome-wide detection of these open chromatin regions ,24. Ther2D3 target genes G0/G1 switch 2 (G0S2), cyclin-dependent kinase inhibitor 1A (CDKN1A) and v-myc avian myelocytomatosis viral oncogene homolog (MYC) in terms of architecture of their TSS and a number of VDR binding sites. Involving genome-wide data in the characterization of 1,25(OH)2D3 target genes participating in the control of cellular growth may help to identify the most important components in cancer-related 1,25(OH)2D3 signaling.For this study, we have selected THP-1 cells as an attractive leukemia model, as it is the only one for which genome-wide VDR data are available. We present analyses of the three primary 1,25(OH)2 incubator. Prior to mRNA or chromatin extraction the cells were grown overnight in phenol red-free RPMI 1640 medium supplemented with 5% charcoal-stripped fetal calf serum. After 72 h treatment with 20 nM phorbol 12-myristate 13-acetate  THP-1 cells become adherent and differentiate into a mature macrophage-like phenotype [2D3 stimulation experiments, cells were treated with 10 nM 1,25(OH)2D3 (Sigma-Aldrich) or solvent (0.001% EtOH). For HDAC inhibition experiments, cells were stimulated with 300 nM trichostatin A (TsA), 2 µM suberoylanilide hydroxamic acid (SAHA), 1 mM valproic acid , 100 nM 1,25(OH)2D3 or solvent (0.16% EtOH or 0.02% DMSO).The human monocytic cell line THP-1  was growhenotype . In 1,25−Ct and were normalized to the internal reference genes B2M, GAPDH and HPRT1 as determined by the geNorm algorithm [ΔCt = 2 by using the sample with the highest expression as a calibrator. For normalization, the relative expression level was divided by the normalization factor that is the geometric mean of the relative quantities (Q) of the three reference genes.Total RNA was extracted using the High Pure RNA Isolation Kit  or the Quick RNA Miniprep Kit . For cDNA synthesis the Transcriptor First Strand cDNA Synthesis Kit (Roche) was applied, where total RNA and oligo(dT)18 primers were denaturated at 65 °C and reverse transcription was carried out for 30 min at 55 °C. qPCR reactions were performed using 250 nM of reverse and forward primers and the LightCycler 480 SYBRGreen I Master mix (Roche). The hotstart Taq polymerase was activated for 10 min at 95 °C, followed by 43 amplification cycles of 20 s denaturation at 95 °C, 15 s annealing at primer-specific temperatures  and 15 slgorithm . Briefly3) for 20 min at room temperature with rotation. Both output and input samples were reverse cross-linked for 5 h at 65 °C in the presence of proteinase K (Roche). The DNA was isolated with the ChIP DNA Clean & Concentrator Kit (Zymo Research). Selected genomic regions containing VDR peaks were analyzed by qPCR using equal DNA amounts of chromatin fragments, 250 nM of reverse and forward primers and the LightCycler 480 SYBRGreen I master mix. The qPCR reactions were performed using the following profile: 10 min at 95 °C, followed by 43 cycles of 20 s at 95 °C, 15 s annealing at primer-specific temperatures (−(ΔCt) *100, where E = amplification efficiency and ΔCt = Ct(output) − Ct(input).After treatment of cells, nuclear proteins were cross-linked to DNA by adding formaldehyde directly to the medium to a final concentration of 1% and incubating for 8 min at room temperature on a rocking platform. Cross-linking was stopped by adding glycine to a final concentration of 0.125 M and incubating for 5 min at room temperature on a rocking platform. The cells were collected, washed with ice-cold PBS and resuspended in lysis buffer  and the lysates were sonicated with a Bioruptor Plus  to result in DNA fragments of 200 to 400 bp. Cellular debris was removed by centrifugation. For output samples, aliquots of the lysate were diluted in ChIP dilution buffer . For input samples, the lysate was diluted 1:10 in ChIP dilution buffer without protease inhibitors and BSA. Anti-VDR antibody  or non-specific IgG  were bound for 3 h to Magna ChIP™ Protein A Magnetic Beads (Millipore). The pre-formed bead-antibody complexes were then washed with ChIP dilution buffer and added to the output chromatin aliquots. The samples were incubated overnight at 4 °C on a rotating platform to form and collect the immuno-complexes. The beads were washed sequentially for 4 min with the following buffers: low salt wash buffer , high salt wash buffer  and LiCl wash buffer . Finally, the beads were washed twice with TE buffer  and the immune complexes were eluted twice using elution buffer 2D3 and displayed one and three VDR peaks, respectively, in reasonable vicinity to their TSS region. For the MYC gene we identified even four VDR peaks, although our microarray data did not indicate any significant regulation of the gene. However, we knew from our previous study [MYC is a primary down-regulated gene.Our microarray and ChIP-seq datasets from undifferentiated THP-1 cells (monocyte-like cells)  list 638us study  in RWPE-G0S2 gene was 27-times lower than that of the MYC gene and 2.6-times reduced when compared with the CDKN1A gene 2D3 target gene, which is already significantly up-regulated after 1 h of ligand treatment (G0S2 gene is more inducible in PMA-differentiated THP-1 cells (5.3-fold after 8 h ligand treatment) than in undifferentiated THP-1 cells (2.6-fold). In both cell types also the CDKN1A gene was significantly induced by 1,25(OH)2D3, but reached during the 8-h time course only a maximal induction of 1.6-fold in monocyte-like cells and 1.3-fold in macrophage-like cells 2D3 target gene [MYC turned out to be an early responding up-regulated (1.6-fold) 1,25(OH)2D3 target gene with a reduced basal expression level.We stimulated both undifferentiated and differentiated THP-1 cells with 1,25(OH)e of 8 h  and obsereatment A. Intereke cells B. The MYget gene , showed 2D3 with the HDAC inhibitors TsA, SAHA and VPA after 2.5 and 24 h 2D3 target (1.4-fold after 2.5 h and 6.1-fold after 24 h) and was only faintly modulated by HDAC inhibitor treatment 2D3 stayed marginal, the gene was strongly up-regulated by HDAC inhibitors, in particular by SAHA, which induced the gene 3.7-fold after 2.5 h and 9.9-fold after 24 h , while after 24 h stimulation SAHA showed the most prominent effect (3.8-fold down-regulation). At this 24 h time point, 1,25(OH)2D3 treatment resulted in a statistically significant 1.4-fold down-regulation of the MYC gene and 24 h . G0S2 wareatment A. In conter 24 h B. InversMYC gene C.G0S2, CDKN1A and MYC respond to 1,25(OH)2D3 but with a differential profile: G0S2 is more prominently up-regulated in macrophage- than in monocyte-like cells, while CDKN1A responds better in monocyte-like cells. Interestingly, MYC is weakly down-regulated in monocyte-like cells but up-regulated in macrophage-like cells. For comparison, in monocyte-like cells G0S2 shows hardly any response to HDAC inhibitors, while CDKN1A is strongly up-regulated after a long-term treatment with the inhibitors and MYC is down-regulated already after a short-term treatment.In summary, the genes G0S2, CDKN1A and MYC. In order to determine, which of these VDR binding site candidates may be involved in the regulation of the genes, we first estimated the size of the chromosomal domains containing the respective TSS regions. Borders of chromosomal domains are defined by DNA looping mediated by the transcription factor CCCTC-binding factor (CTCF) [G0S2 locus on chromosome 1 the largest loop spans over 170 kb and contains one VDR binding site  . CTCF bir (CTCF) . The humr (CTCF) . Importar (CTCF) . We useding site . The resng sites . G0S2 gene, which is located 15 kb upstream of the gene’s TSS in a region of open chromatin, was found both in monocyte- and macrophage-like cells and carries a DR3-type sequence within the summit region of the peak 2D3, while in parallel the region is not associated with open chromatin. At the seven other regions ligand-inducible VDR binding and association with open chromatin was found. However, only at the VDR binding site of the G0S2 gene 1,25(OH)2D3-dependent chromatin opening was observed . At site 1 of the G0S2, CDKN1A and MYC as master examples for demonstrating the complex role of 1,25(OH)2D3 in the control of cellular proliferation in this cancer cell model. In this context, we exhibited the utility of publically available data from ENCODE, in order to limit the size of the genomic regions that needed to be screened for VDR binding sites.The availability of genome-wide data, obtained by individual research teams or by larger consortia, such as ENCODE , provideMYC was one of the first genes to be reported as an 1,25(OH)2D3 target [2D3 on MYC gene expression report its down-regulation. This suggests that 1,25(OH)2D3, via the down-regulation of MYC gene expression, may lead to the inhibition of cellular growth and induction of apoptosis. This study agrees with most other studies that the effects of 1,25(OH)2D3 on the down-regulation of MYC mRNA expression are rather modest. However, given the importance of this protein, even modest changes in expression could yield significant biological effects. Therefore, the well-documented effects of 1,25(OH)2D3 and its synthetic analogues on the inhibition of cellular proliferation 2D3, which should then result in cell cycle arrest and the induction of differentiation [MYC gene, the reported effects of 1,25(OH)2D3 on CDKN1A up-regulation are rather modest and will also not explain most of the cell regulatory properties of VDR ligands.The oncogene 3 target . The Myc3 target ) but als3 target . Dependi3 target . Most stiewed in ) and theiewed in  probablyiewed in ) and hasget gene ,44. For ntiation . HoweverMYC and CDKN1A as VDR target genes, even though along with hundreds of other genes. The THP-1 leukemia model revealed at least 408 statistically up-regulated genes and 230 down-regulated genes after 4 h of stimulation with 1,25(OH)2D3 [2D3 are rather in the area of immune function and metabolism than in cell cycle control. This may depend on the cell type, though.The pre-genomic approaches of VDR target gene candidates described above provide only a limited understanding of the anti-proliferative actions of VDR ligands. Nevertheless, it is interesting and important that also genomic and transcriptomic studies list G0S2 is such an example of a gene being not exclusively associated with one physiological function. Reflected by its name, the gene was initially associated with the re-entry of cells from the G0 phase to the G1 phase, i.e., with a clear cell cycle regulatory function, but nowadays the G0S2 protein appears to be multifaceted being involved in proliferation, apoptosis and carcinogenesis but also in inflammation and metabolism [G0S2 is reported to be a target gene for the nuclear receptors peroxisome proliferator-activated receptors [Many recent studies have shown that apparent distinct physiological actions, such as immune function, metabolism and cellular growth, are closer interlinked than assumed before. This means that many genes have a dual or even triple function in physiology. tabolism . Intereseceptors  and retieceptors , which sG0S2 gene was clearly more responsive to 1,25(OH)2D3 treatment than the genes CDKN1A and MYC. Contrary to many observations that indicate a higher responsiveness of a gene when it is relatively low expressed, the 1,25(OH)2D3 inducibility of the G0S2 gene even increased after its basal expression raised during the differentiation of monocytic THP-1 cells into macrophage-like cells. This suggests that in macrophage-like cells the G0S2 gene may be more extensively involved in its non-cell cycle-related functions than in monocyte-like cells. The prominent binding of VDR to the single binding site of the G0S2 gene locus in macrophage-like cells supports this view. The unexpected induction of the MYC gene in macrophage-like cells by 1,25(OH)2D3 may suggest that the Myc protein has a different function in non-proliferating macrophages than in proliferating monocytes. In parallel, in macrophage-like cells VDR appears to bind only to two of its four binding sites within the MYC gene locus. Importantly, site 1, which is close to the MYC’s TSS and is not associated with open chromatin, is not used in macrophage-like cells. This suggests the intriguing possibility that this VDR binding region, being located close to the TSS, plays a major role in the down-regulation of the MYC gene. Finally, the basal expression of the CDKN1A gene increased during the differentiation of monocytes into macrophage-like cells and in parallel the responsiveness of the gene to 1,25(OH)2D3 was reduced. This fits with the observation that the macrophage-like cells are not proliferating anymore and that in them VDR occupies none of its three binding sites within the CDKN1A gene locus.In this study, mRNA inductions showed that the G0S2 and CDKN1A gene loci are in the same order (140–170 kb), while that of the MYC gene is far larger. The latter may be related to the fact that the gene density of the MYC locus is significantly lower than that of most other genes. This feature gives at this locus a lot of space for a number of long-ranging chromatin loops to be formed between rather distant regions, such as the reported regulation of MYC by a very distant binding site of the transcription factor TCF4 [In the past, the limited amount of sequence information and genome annotation led to the assumptions that (I) a transcription factor should bind to the promoter region upstream of the gene’s TSS to regulate mRNA expression and (II) even enhancer regions are in rather close vicinity to the TSS. At latest the results of the ENCODE project  have sigtor TCF4 .MYC TSS [CDKN1A locus TSS, and to sites 2.2 and 4.7 kb upstream of it [2D3 target genes is the different number of VDR binding sites used in their regulation. The G0S2 gene is a simple example with only one VDR binding site within its chromosomal domain, which is used in all published VDR ChIP-seq data sets besides that from colon cancer cells. In contrast, the CDKN1A gene uses in THP-1 cells three VDR binding sites, of which no. 1 and 3 are also occupied in lymphoblastoid cells [MYC gene even four VDR binding sites, none of which are used outside the monocyte/macrophage cellular model. This limited set of examples suggests that—with increased dissection of experimental models representing different tissues and disease states—for VDR binding there is increasingly observed tissue-specific complexity.Due to their more generic function in the 3-dimensional organization of chromatin, CTCF binding sites may represent an extreme in the conservation between tissues and cell types. In contrast, most other transcription factors, such as VDR, show a far more tissue-specific genomic binding pattern. As demonstrated in this study at the example the two rather closely related cellular models, undifferentiated THP-1 cells and PMA-differentiated THP-1 cells, only three or eight VDR binding sites are occupied in each of the two cell types. Therefore, it is no surprise that for the same gene different patterns of VDR binding sites are detected, when shifting from one cellular system to another. For example, ChIP-seq in LS180 colon cancer cells indicated VDR binding sites 139, 146 and 335 kb upstream of the am of it ,50. An a2D3 target genes being involved in the control of cellular growth makes it obvious that no single gene has the potential to play a dominant role in this process, i.e., there will be no chance for a single gene-targeted therapy. The example of three primary VDR target genes, G0S2, CDKN1A and MYC, with important function in cellular growth suggests that each gene has an individual and cell-specific scenario in the regulation by 1,25(OH)2D3 and its receptor VDR. However, there are also unifying principles, such as the dependence or independence from DR3-type VDR binding sites, which may allow a refinement of therapies.The increasing number of 1,25(OH)


Alu RNAs are present at elevated levels in stress conditions and, consequently, Alu repeats are increasingly being associated with the physiological stress response. Alu repeats are known to harbor transcription factor binding sites that modulate RNA pol II transcription and Alu RNAs act as transcriptional co-repressors through pol II binding in the promoter regions of heat shock responsive genes. An observation of a putative heat shock factor (HSF) binding site in Alu led us to explore whether, through HSF binding, these elements could further contribute to the heat shock response repertoire.Alu density was significantly enriched in transcripts that are down-regulated following heat shock recovery in HeLa cells. ChIP analysis confirmed HSF binding to a consensus motif exhibiting positional conservation across various Alu subfamilies, and reporter constructs demonstrated a sequence-specific two-fold induction of these sites in response to heat shock. These motifs were over-represented in the genic regions of down-regulated transcripts in antisense oriented Alus. Affymetrix Exon arrays detected antisense signals in a significant fraction of the down-regulated transcripts, 50% of which harbored HSF sites within 5 kb. siRNA knockdown of the selected antisense transcripts led to the over-expression, following heat shock, of their corresponding down-regulated transcripts. The antisense transcripts were significantly enriched in processes related to RNA pol III transcription and the TFIIIC complex.We demonstrate a non-random presence of Alu repeats harboring HSF sites in heat shock responsive transcripts. This presence underlies an antisense-mediated mechanism that represents a novel component of Alu and HSF involvement in the heat shock response. Alu repeats, which occupy more than one-tenth of the human genome, have been shown to harbor a large number of transcription factor binding sites (TFBSs) -3, many Alu elements not only provide accessory sites for transcription factor binding together with RNA polymerase (pol) II  but can Our results demonstrate that HSF sites in Alu elements are significantly over-represented in heat shock responsive transcripts and these sites also bind HSFs and are responsive to heat shock in minimal promoter constructs. Besides, the density of Alu elements harboring HSF sites are over-represented in the genic regions of down-regulated transcripts compared to up-regulated ones and many of these down-regulated transcripts also have antisense transcripts. This study not only adds a novel dimension of Alu involvement in heat shock response but also highlights the potential of these elements in the evolution of novel regulatory networks in primate lineages.Genome-wide expression analysis in response to heat shock using the Illumina BeadChip revealed 1,284 up-regulated and 2,995 down-regulated transcripts  and down-regulated  transcripts.It is evident from Table We observed a biased distribution of Alu repeats harboring HSF sites according to their orientation, sense or antisense, with respect to the host transcript . In response to heat shock we found increased levels of antisense transcripts, which were alleviated after small interfering RNA (siRNA)-mediated knockdown of the antisense transcripts , such as Alu RNA and B1 and B2 RNAs ,32, haveThere is increasing evidence of involvement of Alu elements at various levels of transcription ,36. ThesGene Ontology (GO) analysis of the differentially expressed transcripts harboring HSF binding sites, irrespective of their presence in Alu or non-Alu regions, show significant enrichment of processes that are anticipated to vary in response to heat shock stress Figure . For inscis-antisense to the host gene transcript. Additionally such antisense-oriented Alus could provide HSF binding sites that can act as RNA pol II signals for initiating antisense transcription. We observed that a significant fraction of the down-regulated transcripts  have antisense transcripts using Affymetrix Exon arrays  supplemented with heat-inactivated 10% fetal bovine serum from GIBCO  and 1% antibiotic antimycotic solution from HiMedia  at 37°C in a 5% COTotal RNA was isolated from cultured cells using Trizol reagent  according to the manufacturer's instructions. Subsequent purification using an RNeasy Kit  was carried out to remove residual aromatic compounds that may hinder microarray expression. Total RNA (1 μg) was converted to cDNA using random primers and High Capacity cDNA Reverse Transcription  as per the manufacturer's instructions.In vitro transcription (IVT) of the purified cDNA was carried out by T7 RNA polymerase using biotinylated primers. The concentration of the purified cRNA solution was estimated using NanoDrop and then hybridized to WG-6 v2.0 Human Expression BeadChips  following the manufacturer's instructions. Experiments were carried out using three biological replicates for each treated and untreated condition.An Illumina TotalPrep RNA Amplification Kit was used to prepare the samples for hybridization on Illumina arrays. Briefly, first-strand cDNA was synthesized from 500 ng of total RNA, followed by simultaneous second-strand cDNA synthesis and degradation of residual RNA with DNA polymerase and RNase H, respectively. -ΔΔCT method. Three internal controls, HPRT1, RPS18 and RPL13A, were used for normalization during validation by qRT-PCR. These internal controls were selected from our own microarray dataset, based on the criteria of high expression but minimum differential expression. A list of the primers used is provided in Additional file qRT-PCRs were performed on a 7900HT ABI platform using 2X SYBR Green master mix . The relative mRNA expression level analyses were carried out using the 2SPN (G1), SPINK6 (G2) and HIST1H4A (G3), that harbored high scoring (8.9) HSF binding sites within Alus in the promoter proximal regions for functional validation. For each of these genes, reporter constructs using a firefly luciferase vector with a minimal promoter pGL4.23 (luc2/minP) vector were made with Alus harboring putative HSF sites as insert. An earlier reported functional HSF site in a non-Alu region of the HSPA1A promoter was constructed as a positive control. The templates were amplified by PCR from human genomic DNA followed by gel purification of PCR products using Qiagen columns prior to cloning. The clones were confirmed by sequencing.We considered three genes, G1, G2 and G3 clones were subjected to site-directed mutagenesis using a QuikChange II XL kit  as per the manufacturer's protocol to incorporate desired base changes in the predicted HSF sites within Alus. In each of the clones, the three most-conserved bases were mutated. Site-directed mutagenesis clones were confirmed by sequencing. Details of primer sequences and mutated bases are provided in Additional file 5 cells to achieve optimum confluency. Transfection efficiency was standardized after co-transfection of pGL4.23 firefly luciferase with GFP vector pCM66. Then, 1 μg of each construct in pGL4.23 was co-transfected with 10 ng of pGL4.75 renilla luciferase  as a control. Twenty-four hours after transfection, cells were subjected to heat shock stress, as described above, followed by a 2-hour incubation at 37°C and 5% CO2. Cells were lysed after 2 hours and luciferase activity was measured with a dual luciferase reporter assay system (Promega) according to the manufacturer's protocol. Each experiment was performed in triplicate and repeated three times. The luciferase activity was quantified using a Tecan Luminometer .Transient transfections were performed using Lipofectamine 2000 (Invitrogen) as per the manufacturer's specifications in 12-well tissue culture plates. Prior to transfection, 12-well plates were seeded with 2.5 × 10In order to confirm the binding of HSF to its cognate sites, we performed ChIP. Heat shock treated HeLa cells as described above were fixed with 1% formaldehyde at 37°C for 10 minutes. ChIP was performed following the protocol provided by Upstate Biotechnology  with modifications as in the Fast ChIP protocol. Goat polyclonal antibody raised against HSF1 was used to immune-precipitate chromatin, along with untreated cells. Briefly, cells were lysed and sonicated using a Misonix 3000 sonicator  to achieve DNA sizes ranging from 200 to 700 bp. Lysate was pre-cleared using protein-G sepharose beads. Supernatants were then incubated with anti-HSF1 antibody  at 4°C overnight. Immuno-complexes were purified using herring sperm DNA saturated protein-G sepharose by incubation at 4°C for 3 hours and washed extensively. Chelex-100 resin was used to extract DNA from immune-precipitated chromatin. The cross-linkage between DNA and protein was reversed by heating at 100°C for 10 minutes and protein removed by proteinase K digestion at 55°C for 30 minutes. The immune-precipitated DNAs were recovered using a PCR Purification Kit (Qiagen). In order to confirm the presence of HSF in heat shocked cells and also to confirm the specificity and efficiency of the antibody used for ChIP, we carried out western blotting. The blots were probed with anti-HSF1 . Specific immune-reactive bands were detected using anti-goat secondary antibody conjugated to alkaline phosphatase and detected with BCIP-NBT .HIST1H4A, SPINK6 and ANKRD33 genes, which have a HSF site within an Alu in the upstream region. HSPA1A was used as a positive control as it has a HSF site in a non-Alu region. Input chromatin for both treatments (heat shock versus no heat shock) was used to ensure that an equal amount of chromatin was used for the reactions. In addition, a control ChIP was also performed 'without antibody' to ascertain the enrichment after addition of HSF1 antibody. As a negative control, primers were designed from a region of the genome that does not contain a HSF site and PCR was done with input chromatin, a ChIP sample and no antibody to confirm the specificity. The proximal region of antisense transcripts harboring high-score HSF sites within Alus was also confirmed for its HSF occupancy in response to heat shock by ChIP-PCR. Primers used for all the PCRs are listed in Additional file The specific binding of HSF1 to its site was further validated by ChIP-PCR in both the Alu and non-Alu regions. Primers were designed for We carried out two sets of microarray experiments using Exon arrays to detect antisense transcripts in heat shocked cells. In one of the arrays a standard protocol for expression analysis was performed for detection of all transcripts. In the other, specifically antisense transcripts were profiled where the first cycle cDNA synthesis and the IVT amplification process were omitted and the experiment started directly from the second cycle cDNA synthesis . Each ofSense strand expression profiling was performed according to the recommended protocol of Affymetrix's GeneChip Whole Transcript Sense target labeling assay manual . We used 1 μg of total RNA as starting material. Ambion's Whole Transcript Expression kit  was used for preparation of cDNA. Prior to cDNA preparation, this kit also carries out ribosomal RNA reduction. Briefly, double-stranded cDNA is synthesized with random hexamers , coupled with a T7 promoter sequence. This is used for preparation of cRNA through IVT amplification with T7 RNA polymerase. In the second cycle cDNA synthesis, random primers are used in reverse transcription to convert the cRNA into single-stranded DNA. The single-stranded cDNAs (6 μg) are then fragmented, labeled, and hybridized to the array.The sample preparation for profiling antisense transcripts was done as described earlier . CompareAntisense transcripts with proximal HSF sites (within 2 kb) were selected for knockdown using siRNAs. For each transcript, three siRNAs were made for the probe selection regions that have signal in the antisense exon array. Primer sequences are listed in Additional file A large number of computational approaches for analysis of experimental methods and bioinformatics strategies for functional analysis of HSF sites in the genome, in both repetitive and non-repetitive regions, were used. These were carried out using available as well as in-house-developed algorithms in C++ and Perl languages.Illumina BeadChip expression arrays were analyzed using BeadStudio software. Background subtraction was done and average normalization was applied. For selection of differentially expressed genes, we used the Illumina Custom error model and the recommended cutoff of ±13 diff. score.chr*_random and chr*_hap. The coordinates of Alu elements were obtained using the Repeat Masker track of the Table Browser (hg18). The start and end positions of Alu elements in the sense orientation and those in the antisense orientation to the host transcript were classified separately. A random set of RefSeq transcripts were selected and their upstream 5 kb and genic sequences were also retrieved similarly. Comparison of Alu density in the upstream and genic regions of up-regulated and down-regulated transcripts was carried out using a two tailed t-test.We retrieved the 5 kb upstream and genic sequences of each of the differentially regulated transcripts using the UCSC Table Browser  . In ordeHSPA1A gave a score of 8.9 and hence, for our analysis, we set a threshold of 8.7 to locate the most probable biologically significant regions.Using an in-house developed tool, Promotif (implemented in C++), HSF sites were detected based on a position weight matrix generated using the Gibbs Motif Sampler. The program generates a score for every site detected . Analysit-test.HSF sites detected at and above the threshold score were mapped into Alu and non-Alu regions of the upstream and genic regions. The differentially regulated transcripts were thus categorized into three classes for both upstream and genic regions: (i) HSF sites in both non-Alu and Alu regions, (ii) HSF sites in non-Alu regions; and (iii) HSF sites in Alu regions only. In this analysis also we retained Alu strand specificity with respect to the orientation of the host transcript. HSF sites for a given sequence in the upstream region are represented in counts per kilobase. These counts per kilobase were then averaged for the gene number in each class, for example, upstream region and up-regulated transcripts to give counts per kilobase per gene. A scaling factor was applied for genic stretches, and the density was expressed as counts/10 kb/gene. This was done since genic regions are much larger than the upstream 5 kb regions and this scaling makes the genic HSF site density of comparable magnitude to the upstream HSF site density. Comparison of HSF site density between various classes was carried out using a two tailed Local alignment of Alu elements with HSF sites in the consensus subfamily sequence from RepBase (release 15.07) was used to assign the actual position of HSF sites within Alu elements. This was performed using the Matcher program from the EMBOSS suite. Positional conservation was checked separately for Alu elements in the sense and antisense orientations.For generating a consensus motif of the HSF site within Alu subfamilies the 13-bp stretch was retrieved from the upstream/genic Alu sequences of the differentially expressed transcripts. From these, a position-specific scoring matrix was generated using the WEBLOGO program . Motif gab initio gene predictions in addition to the 'core' and 'extended' exons. To check the quality of the data, we compared the sense and antisense arrays using the various matrices in Expression Console as previously described [The status of antisense transcripts in response to heat shock was inferred from the Exon arrays. The Exon array. cel files were analyzed using the Robust Multi-array Analysis algorithm  and quanescribed .cis-antisense signal in the antisense arrays. A significant detection  of probe signal was considered to count as an antisense signal. In order to correlate antisense signal to HSF binding, we applied a threshold criteria of a 5 kb distance between the HSF site coordinates and the antisense signal . To further the interpretation, we analyzed cases where the HSF site was upstream of the antisense signal.Analysis was carried out on a common set of transcripts that were observed to be down-regulated in both the Illumina microarray and Exon arrays in response to heat shock. In this set we next identified the coordinates of HSF sites within the Alus in the genic region through an informatics approach and looked for GO analysis was performed using DAVID . BrieflyIn accordance with our strategy to determine HSF site distribution in Alu and non-Alu regions Table , we perfIllumina whole genome expression profiling BeadChip and Affymetrix Exon array datasets are publicly available on the Gene Expression Omnibus database with accession codes GSE26776 and GSE27127, respectively.bp: base pair; ChIP: chromatin immunoprecipitation; GO: Gene Ontology; HSF: heat shock factor; IVT: in vitro transcription; ncRNA: non-coding RNA; qRT-PCR: quantitative real-time PCR; RNA pol: RNA polymerase; SINE: short interspersed nuclear element; siRNA: small interfering RNA; TFBS: transcription factor binding site; TFIIIC: transcription factor IIIC complex;MM conceived, designed, supervised, carried out analysis and wrote the manuscript. RP performed all the molecular biology experiments, carried out analysis of microarray and real-time data and participated in manuscript preparation. AKM performed global data analysis and interpretation, including annotation and GO analysis, and participated in manuscript preparation. VJ assisted in bio-informatics analysis, including mapping HSF sites. All authors read and approved the final manuscript.The authors declare that they have no competing interests.Genes differentially expressed in response to heat shock stress. This file contains a list of genes differentially expressed in response to heat shock stress using Illumina BeadChip, analyzed using Beadstudio software.Click here for filePositional conservation of HSF sites. This file contains the data for the positional preference of HSF sites within Alus in sense and antisense orientations.Click here for fileBiased HSF site distribution for Alu orientation in upstream and genic regions. This file contains HSF site distribution data for Alu and non-Alu sequences in the upstream and genic regions of differentially regulated genes.Click here for fileHSF density for upstream and genic regions. This file contains per gene HSF site density for both Alu and non-Alu sequences in the upstream and genic regions.Click here for fileCorrelation of HSF sites to antisense signals. This file contains the HSF sites positions relative to the antisense signal co-ordinates from the exon array for down-regulated genes.Click here for fileGene Ontology analysis. This file contains the GO category analysis using DAVID for differentially regulated genes. The genes are binned on the basis of the presence of HSF sites exclusively in Alu regions or exclusively in non-Alu regions or in both regions.Click here for fileGenes with HSF sites only in Alu regions. This file contains a list of all the up-regulated genes where the HSF sites in the upstream region are present exclusively in Alu sequences.Click here for filePrimers used for validation. This file contains all the primers used for experimental validation of the inferences from genome-wide expression profiling and subsequent bio-informatics analysis.Click here for file


Salmonella enterica serovar Typhimurium (S. Typhimurium) requires expression of the extracellular virulence gene expression programme (STEX), activation of which is dependent on the signalling molecule guanosine tetraphosphate (ppGpp). Recently, next-generation transcriptomics (RNA-seq) has revealed the unexpected complexity of bacterial transcriptomes and in this report we use differential RNA sequencing (dRNA-seq) to define the high-resolution transcriptomic architecture of wild-type S. Typhimurium and a ppGpp null strain under growth conditions which model STEX. In doing so we show that ppGpp plays a much wider role in regulating the S. Typhimurium STEX primary transcriptome than previously recognised.Invasion of intestinal epithelial cells by S. Typhimurium open reading frames (ORFs). The TSS mapping enabled a genome-wide promoter analysis resulting in the prediction of 169 alternative sigma factor binding sites, and the prediction of the structure of 625 operons. We also report the discovery of 55 new candidate small RNAs (sRNAs) and 302 candidate antisense RNAs (asRNAs). We discovered 32 ppGpp-dependent alternative TSSs and determined the extent and level of ppGpp-dependent coding and non-coding transcription. We found that 34% and 20% of coding and non-coding RNA transcription respectively was ppGpp-dependent under these growth conditions, adding a further dimension to the role of this remarkable small regulatory molecule in enabling rapid adaptation to the infective environment.Here we report the precise mapping of transcriptional start sites (TSSs) for 78% of the S. Typhimurium and finer definition of the key role ppGpp plays in regulating Salmonella coding and non-coding transcription should promote the understanding of gene regulation in this important food borne pathogen and act as a resource for future research.The transcriptional architecture of  Salmonella continue to pose an unacceptable worldwide threat to the health of humans and livestock. Infection of humans with S. Typhimurium results in a debilitating case of severe gastroenteritis that may result in death in immunocompromised individuals. There are about 1.3 billion cases of non-typhoidal salmonellosis worldwide each year and it is estimated that there are 17 million cases and over 500,000 deaths each year caused by typhoid fever . Whilstmologue) . Previoutenuated . It has rculosis ,11, Listytogenes , Legionemophilia ,14, Vibr cholera  and Pseuruginosa . A complruginosa .70 resulting in an increase in the availability of RNAP to bind alternative stress-response sigma factors . We a. We aS. ectively ,65. Prevectively ,66. In cRhizobium etli and Staphylococcus aureus [Of the total known and predicted sRNAs we found that 18% of the TSSs (18) were ppGpp-dependent out of a total of 100 start sites, and 25% (15) of the new candidate sRNAs were ppGpp-dependent out of a total of 65 start sites  showed a similar level of ppGpp-dependency to the antisense and sRNA TSSs (19%).Of the 302 asRNAs that were directly opposite ORFs, we note that 32 were ppGpp-dependently elevated and 32 repressed (Table S. Typhimurium ORFs during growth conditions in which model the extracellular virulence gene expression programme (STEX). To date this is the most extensive and accurate map of the TSSs for this bacterium. Our analysis also identified secondary TSSs for many genes and operon structures. Our MEME based promoter analysis of the first genes of operons identified conserved regions in the promoters which were found to closely resemble consensus binding sites for σ24, σ28, σ32, σ38 & σ54 factors; many of the predicted sigma factor-dependent genes had previously been experimentally verified in either E. coli or Salmonella. We verified the expression of 38 out of 87 predicted sRNAs and 45 out of 62 known sRNAs [S. Typhimurium genome by 55. Of the predicted sRNAs we were unable to verify, it is possible that they were not expressed under the growth condition studied here. We also observed that the location of the TSSs of a subset of the predicted sRNAs did not correspond to the predicted start sites; from this we infer the bioinformatic approach used to identify the TSSs may require experimental-based refinements to enhance accuracy. We identified 302 candidate antisense transcripts for the S. Typhimurium genome for which we defined a conserved -10 hexamer upstream of the TSS. Although from this study, we cannot rule out the possibility that the expression of asRNAs are a result of promiscuous transcription, other work suggests this is not the case, at least for H. pylori [We have determined the TSSs for 78% of the wn sRNAs . We hypothesise that the ppGpp-dependent activation of RNaseP may result in reduced tRNA processing in the ΔrelAΔspoT strain and subsequent removal of incorrectly processed tRNAs via RNA quality control mechanisms [It is generally accepted that elevated levels of ppGpp during amino acid starvation (stringent response) result in repression of stable RNAs (rRNA and tRNA). Consistent with this we observed repression of the rRNA operons in the wild-type compared to the Δal phase . It is p[E. coli . In suppchanisms .E and σ54 in E. coli [70 dependent and perhaps reflects the major role sRNAs play in maintaining house-keeping functions and regulating virulence determinants. In contrast to the discriminator regions of ppGpp-repressed genes, we were unable to identify a conserved GC rich region in the set of ppGpp-repressed sRNAs. Several of the ppGpp-repressed sRNAs  have been shown to act as repressors of genes encoding porins and outer membrane proteins (OMPs) suggesting that ppGpp may indirectly activate these target genes. OMPs are important virulence factors and play a significant role in the bacterial adaptation to environmental conditions. Other highly ppGpp-repressed sRNAs shown to play a role in Salmonella virulence include IsrI, IsrP and CsrB. In addition, the sRNA chaperone, Hfq was ppGpp-repressed by 5.6-fold thus expanding the role of ppGpp in the regulation of Salmonella virulence gene expression  and -35 (TTGaCA) regions upstream of the predicted TSSs Figure . A manua E. coli . This suhimurium . The SPIhimurium . Our dathimurium , we notehimurium . It is shimurium . OmpD hall lines ,79. PoteS. Typhimurium genome under the growth conditions studied here. Similarly, a considerable abundance of asRNA transcription was also discovered in E. coli and H. pylori [hilA and hilD  was highly ppGpp-activated by a factor of at least 34-fold. HilD has been implicated in cross-talk between SPI1 and SPI2 expression [EX and STIN virulence gene expression programmes.We discovered extensive antisense transcription within the . pylori ,54. Intepression . Under tS. Typhimurium wild-type and ppGpp0 strain during growth conditions where the invasion (SPI1) genes are expressed. We identify the precise location of the TSSs for 78% of the S. Typhimurium genome, the reannotation of 60 start codons and the identification of 23 potential new ORFs. The nucleotide position of the TSSs enabled us to perform a promoter analysis, which resulted in the prediction of binding sites for 6 sigma factors, the analysis of 5' leader lengths and the prediction of 625 operons. The definition of the ncRNA transcriptome resulted in confirmation of the expression of 83 predicted and known sRNAs under these growth conditions and the prediction of 55 new candidate sRNAs, for which potential targets were inferred. Extensive asRNA transcription was also discovered for 302 candidate asRNAs, 18 and 11 of which were opposite virulence genes and candidate sRNAs respectively. The dRNA-seq predicted ppGpp-dependent TSSs and ppGpp-dependent expression for the SL1344 genome and we showed that ppGpp is involved in regulating an average of 20% of S. Typhimurium ncRNA expression.Here we used dRNA-seq to define the transcriptomic architecture for an S. Typhimurium strain SL1344 (31) was provided by F. Norel (Institut Pasteur) and re-isolated from the spleens of infected BALB/c mice. The SL1344 ΔrelAΔspoT strain was a kind gift from Dr. Karsten Tedin, Freie Universität, Berlin, and was constructed by lambda red mutagenesis [relA and spoT genes and intactness of flanking regions were determined by sequencing; antibiotic resistance markers were removed after construction (pers. comm. Dr. K. Tedin). Bacterial cultures were grown overnight in Luria-Bertani broth (LB) at 37°C, 250 rpm, from -70°C glycerol stocks and used to inoculate into 50 ml of fresh LB in 250 ml conical flasks. The cultures were grown aerobically at 37°C with shaking at 250 rpm to an OD600 of 2.1, , conditions previously shown to induce SPI1 gene expression [relAΔspoT strains have almost identical growth rates in LB under these growth conditions  phenol in ethanol), and incubated on ice for 30 min to stabilize total RNA [http://www.vertis-biotech.com) as described [relAΔspoT non-enriched (DM-NE) and ΔrelAΔspoT enriched (DM-EN). Each library was tagged with a different barcode at the 5' end to enable multiplexing during sequencing. Four of the Roche-454 cDNA libraries were pooled and sequenced , yielding a total of ~400,000 reads. Similarly, four of the Illumina-Solexa libraries were pooled and sequenced in a single lane using 36 single-read cycles on an Illumina Genome Analyzer II sequencing machine , yielding a total of ~107 reads.To differentiate primary transcripts with a 5' triphosphate end (5' PPP) from processed transcripts with a 5' monophosphate end (5' P), total RNA from each strain was divided into equal amounts and one half was treated with Terminator™ 5'-phosphate-dependent exonuclease  as previously described . TEX speescribed . For eacS. Typhimurium SL1344 genome (Genbank ID. FQ312003.1) including the three native virulence plasmids  using the segemehl program [The mapping statistics for both the Roche-454 and Illumina-Solexa cDNA libraries are shown in additional file  program . Mapped  program .Northern blotting was performed essentially as described in . Hybridi®-T Easy vector (Promega) and sequenced using standard protocols. All primers used are detailed in additional file The transcriptional start sites of selected genes were determined using 5' RACE as described previously . BrieflyrelAΔspoT strains as well as a genomic DNA negative control. Primers used are listed in additional file In general we found that Northern blotting failed to detect non-coding RNAs (ncRNAs) which had Solexa read numbers of less than 200. We therefore employed an RT-PCR technique to selectively amplify predicted ncRNAs and thus confirm their existence. Primers complementary to the 3' end of putative ncRNA but including a universal 5' adaptor sequence were used to prime cDNA synthesis from total RNA samples. RNA (0.5 μg) was mixed with 2 pmol of the RT primer and reverse transcribed at 55°C for 1 hour using AffinityScript (Agilent) according to the manufacturer's instructions. Following heat denaturation of the enzyme, 2 μl of the reaction was used as a template in a PCR reaction using a primer matching the 5' end of the putative ncRNA and a second universal primer (U5), matching the 5' adaptor sequence of the RT primer. For each target, PCR reactions were carried out with cDNA from both wild-type and ΔS. Typhimurium SL1344 wild type and isogenic ΔrelAΔspoT strains as described above under identical growth conditions and grown to the same OD. The RNA was labelled and hybridised to IFR SALSA2 whole ORF microarrays (http://www.ifr.ac.uk/Safety/Microarrays/default.html#protocols), and data processed and analysed using GeneSpring™ (Agilent). The data was from 3 biological replicates, statistically filtered (P = 0.05) and a 2-fold cut off applied.Microarray analysis was performed as described previously . RNA washttp://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse34269).The microarray data discussed in this publication are MIAME compliant and have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE34269 ; ORFs: open reading frame(s); ncRNA: non-coding RNA; sRNA: small RNA; asRNA: anti-sense RNA; SPI: The authors declare that they have no competing interests.AT and VKR designed the study. VKR prepared RNA for sequencing and VKR and CSM wrote custom PERL scripts for mapping and data analysis. NS performed experimental validation of dRNA-seq data. AT, VKR, JJJ and NS manually identified TSSs. AT, VKR and NS wrote the manuscript. All authors read and approved the final manuscript.Supplementary Tables . Table S1: Mapping statistics for wild-type and ΔrelAΔspoT libraries. Table S2: Primers used for 5' RACE identification of TSSs. Table S3: Comparison of published Salmonella TSSs and dRNA-seq TSSs. Table S4: Probes and primers used for detection of ncRNAs.Click here for fileSupplementary Tables S1, S2, S3, S4, S5, S6, S7, S8, S9. Table S1: Master table of TSSs and ppGpp-dependent expression levels for S. Typhimurium SL1344 ORFs. Table S2: Leaderless transcripts. Table S3: TSSs and ppGpp-dependent expression of known and predicted small RNAs. Table S4: TSSs and ppGpp-dependent expression of new candidate small RNAs. Table S5: TSSs and ppGpp-dependent expression of candidate antisense RNAs. Table S6: TSSs and ppGpp-dependent expression rRNAs and tRNAs. Table S7: Predicted new ORFs. Table S8: Comparison of ppGpp-dependent expression from microarray and dRNA-seq data. Table S9: Re-annotated ORFs.Click here for fileSupplementary Figures S1, S2, S3, S4, S5, S6, S7, S8, S9. Figure S1: 5' RACE identification of transcriptional start sites. Figure S2: Functional category analysis of 1932 promoters of annotated SL1344 ORFs that contain a predicted -10 motif. Figure S3: Functional category analysis of 1932 promoters of annotated SL1344 ORFs that contain a predicted -10 and -35 motif. Figure S4: Functional category analysis of 264 promoters of annotated SL1344 ORFs that contain conserved motif 1. Figure S5: Northern Blot detection of non-coding RNAs. Figure S6: Adapter assisted PCR detection of asRNAs. Figure S7: Functional category analysis of ORFs opposite to candidate asRNAs. Figure S8: Growth curves for S. Typhimurium SL1344 wild-type ΔrelAΔspoT strains. Figure S9: Invasion of S. Typhimurium SL1344 wild-type and isogenic ΔrelAΔspoT strains in HeLa cells at 2 h and intracellular replication at 6 h post-infection.Click here for file


In this work we describe an unusual enzyme from Leishmania major (Arabinokinase/Pyrophosphorylase) that catalyzes the synthesis of GDP-D-arabinopyranose (GDP-D-Arap) via a D-arabinose-1-phosphate intermediate in the presence of ATP and GTP. Our data indicate GDP-D-Arap transport in vivo by the LPG2 multispecific nucleotide sugar transporter into the Leishmania Golgi apparatus, in which it can be used by glycosyltransferases as a donor substrate for glycosylation. It is known that both bacteria (Bacteriodes) and plants (Arabidopsis) can synthesize GDP-L-Fuc from L-fucose (L-Fuc) via intermediate L-fucose-1-phosphate using a bifunctional enzyme L-fucokinase/GDP-L-fucose pyrophosphorylase , 4. SincThe open reading frames lmjF16.0440 and lmjF16.0480 correspond to putative polypeptides composed of 1,187 aminoacid residues with a calculated molecular mass of 126.5 kDa. The only difference (three aminoacid residues) between these two proteins is the segment 196-199, namely PheGlnAsnHis in LmjF16.0480 and LeuGlnAspTyr in LmjF16.0440. The N-terminal sequences of these proteins contain a highly conserved segment Val100-Lys117 that closely resembles the conserved pyrophosphorylase motif Lys(X)2GlyXThrXMet(X)4Lys [The lmjF16.0440 and lmjF16.0480 genes were cloned in the pET16b plasmid vector for further examination of the activities of the putative enzymes. The recombinant LmjF16.0440 and LmjF16.0480 were expressed in E.coli BL21 (DE3)-RIPL cells and tested for enzyme activity  and maximum reaction velocity (Vmax), were determined for recombinant LmjF16.0440 and LmjF16.0480. These parameters are shown in The human genome contains genes that are partially homologous to the bifunctional enzyme from Leishmania. In particular, the locus NP 659496 encodes a protein composed of 1,185 aminoacid residues with 44% homology with the kinase C-end, whereas its N-end has no significant resemblance with pyrophosphorylase domains. The gene was cloned, and its recombinant product was tested for GDP-D-Arap synthesizing capability. This test has shown no activity. The absence of pyrophosphorylase activity for the human protein is not surprising considering the low homology of the human protein N-end with the pyrophosphorylase domains. The D-arabinose-activating capability was also lacking, despite the close resemblance between the kinase C-end and both LmjF16.0440 and LmjF16.0480.In most cases, activated carbohydrates are synthesized in cytoplasm and subsequently transported into the Golgi lumen, in which they are utilized by corresponding glycosyltransferases as substrate donors in glycosylation reactions. Earlier, the LPG2 protein found in the Leishmania Golgi apparatus membrane was classified as a multispecific transporter that can transport not only GDP-Man, but also GDP-D-Arap and GDP-L-Fuc . To makeThus, our data very likely suggest GDP-D-Arap transport from cytoplasm (in which it is synthesized) into the Golgi lumen by the multi-functional transporter protein LPG2. We have also classified the L. major lmjF16.0480 gene product as a bifunctional arabinokinase/pyrophosphorylase that can synthesize GDP-D-Arap from D-Arap via the intermediate D-arabino-1-phosphate in the presence of both ATP and GTP. The study was supported by the Program of Presidium of Russian Academy of Sciences "Molecular and Cell Biology." The authors are grateful to Prof. H. Guo  for assistance in identification and cloning of Leishmania major and human genes and to Prof. S. Turco  for fruitful discussions.


Two plant-specific transcription factors, NAC and YABBY, are involved in important plant developmental processes. However their molecular mechanisms, especially DNA binding sites and co-regulated genes, are largely unknown during soybean seedling development.In order to identify genome-wide binding sites of specific members of the NAC and YABBY transcription factors and co-regulated genes, we performed Chromatin Immunoprecipitation Sequencing (ChIP-Seq) and RNA Sequencing (RNA-Seq) using cotyledons from soybean seedling developmental stages. Our RNA-Seq data revealed that these particular NAC and YABBY transcription factors showed a clear pattern in their expression during soybean seedling development. The highest level of their expression was found in seedling developmental stage 4 when cotyledons undergo a physiological transition from non-photosynthetic storage tissue to a metabolically active photosynthetic tissue. Our ChIP-Seq data identified 72 genes potentially regulated by the NAC and 96 genes by the YABBY transcription factors examined. Our RNA-Seq data revealed highly differentially expressed candidate genes regulated by the NAC transcription factor include lipoxygense, pectin methyl esterase inhibitor, DEAD/DEAH box helicase and homeobox associated proteins. YABBY-regulated genes include AP2 transcription factor, fatty acid desaturase and WRKY transcription factor. Additionally, we have identified DNA binding motifs for the NAC and YABBY transcription factors.Genome-wide determination of binding sites for NAC and YABBY transcription factors and identification of candidate genes regulated by these transcription factors will advance the understanding of complex gene regulatory networks during soybean seedling development. Our data imply that there is transcriptional reprogramming during the functional transition of cotyledons from non-photosynthetic storage tissue to metabolically active photosynthetic tissue. Understanding the transcriptional regulatory network during developmental stages has been a focus for many years at the single gene level. Recently genome-wide mapping of protein–DNA interactions enables of complete understanding of transcriptional regulation. A precise map of binding sites for transcription factors and other DNA-binding proteins is vital for deciphering the gene regulatory networks that underlie various biological processes -4. TransTo study the genome-wide profiling of transcription factor binding sites, chromatin immunoprecipitation followed by sequencing (ChIP–Seq) has become one of the principal techniques ,2,10. OwGlycine max) is one of the most economically important crops cultivated all over the world. It is an excellent source of vegetable oil and protein. However, the regulation of gene expression during soybean seedling development is still largely unexplored. Thus it is important to investigate how the genes are regulated during different developmental stages of soybean seedlings. The soybean genome was sequenced about two years ago ) [C[GA][TC][GA]CC which contains the previously identified motif in Arabidopsis, thus corroborating our discovery of DNA binding motifs for the NAC transcription factor in soybean.The NAC transcription factor is a plant specific transcription factor family which plays important roles in plant growth, development and stress responses -25. Glycproteins ,23. AlthCGT[GA]) . One of To dissect the gene regulatory network of a particular transcription factor, it is important to study the expression of co-regulated genes. In this study, we have identified 72 genes potentially regulated by a NAC transcription factor based on our ChIP-Seq and RNA-Seq data Table . Using oAmong those highly differentially expressed genes, lipoxygenase has been proposed to be involved in reserve lipid mobilization during soybean seed germination ,50,51. OAnother important gene regulated by the NAC transcription factor is the DEAD/DEAH box helicases which are ubiquitous enzymes that catalyze the unwinding of energetically stable duplex DNA (DNA helicases) or duplex RNA secondary structures (RNA helicases) -60. MostGlycine max has multiple isoforms of the YABBY transcription factor; however there is not much known about the molecular mechanisms for this transcription factor specifically its DNA binding sites and co-regulated genes. Our RNA-Seq data revealed that there are ten members of the YABBY transcription factor family expressed during the physiological transition. We performed a multiple sequence alignment among the ten members of the YABBY transcription factors. Two of them showed high sequence homology and they are closely related  seeds were planted per small pot (4.5 inches) containing Universal SB300 soil mix. A total of 25 pots (100 seeds) were initially used to collect and pool 6 individual cotyledon samples per developmental stage. Plants were grown for approximately 7–8 days with regular watering. A biological replicate was performed with another 25 pots to collect tissues in a similar way. Seven different stages during the development of soybean seedlings were defined based on time, size of radicles, hypocotyls, roots and appearance of germinating cotyledons. Stage 1: Imbibed seed for 24 hours; pre-emerging hypocotyls. Stage 2: Yellow cotyledons; emerging radicle 8–10 mm long. Stage 3: Yellow cotyledons with slightly green edges; hypocotyls15-20 mm long. Stage 4: Yellow-green cotyledons; hypocotyls 30–35 mm long. Stage 5: Yellow-green cotyledons above the ground; primary roots starting to develop. Stage 6: Mostly green cotyledons above the ground; growing straight from the hypocotyl. Stage 7: Fully green cotyledons; plants 6–7 cm long above the ground; the root system fully developed; cotyledons upright; unifoliolate exposed. For the RNA-Seq experiment, cotyledons from each of these developmental stages were collected and then frozen in liquid nitrogen. Subsequently the tissue was freeze dried and stored at −80°C. For ChIP-Seq experiment, fresh cotyledons from stage 4 and stage 5 were used.Total RNA was extracted separately for seven different developmental stages from freeze dried cotyledons using a modified McCarty method  using phCotyledons from soybean seedling developmental stage 4 and stage 5 were collected for the ChIP-Seq experiment performed using previously described methods ,81. Bried/2 toward the 3′ ends to get the most likely protein-DNA interaction sites [Sequencing of ChIP-Seq libraries produced millions of raw reads which were aligned to the reference soybean genome using the ultrafast Bowtie aligner  to get ton sites ,11,35,37on sites  using a on sites .A motif search was performed using the most widely used MEME software . For MEMThe high-throughput sequencing data for ChIP-Seq libraries are available under NCBI-GEO  series aThe authors declare that they have no competing interests.MS designed experiments, performed RNA extractions, conducted ChIP-Seq experiment, analyzed RNA-Seq and ChIP-Seq data and drafted the manuscript. LOV designed initial approach, obtained funding, led and coordinated the project, and edited the manuscript. All authors read and approved the final manuscript.Peaks detected for NAC transcription factor binding sites by MACS software.Click here for filePeaks detected for YABBY transcription factor binding sites by MACS software.Click here for fileComplete list of candidate genes potentially regulated by NAC transcription factor during soybean seedling development.Click here for fileComplete list of candidate genes potentially regulated by YABBY transcription factor during soybean seedling development.Click here for fileMultiple sequence alignment of four members of NAC family expressed during the functional transition of the cotyledons.Click here for fileMultiple sequence alignment of ten members of YABBY family expressed during the functional transition of the cotyledons.Click here for fileList of 53 gene models encoding WRKY transcription factors expressed at level ( ≥ 10 RPKM) in at least one of seven stages of soybean seedling development.Click here for file


Conserved upstream open reading frames (uORFs) are found within many eukaryotic transcripts and are known to regulate protein translation. Evidence from genetic and bioinformatic studies implicates disturbed uORF-mediated translational control in the etiology of human diseases. A genetic mouse model has recently provided proof-of-principle support for the physiological relevance of uORF-mediated translational control in mammals. The targeted disruption of the uORF initiation codon within the transcription factor CCAAT/enhancer binding protein β (C/EBPβ) gene resulted in deregulated C/EBPβ protein isoform expression, associated with defective liver regeneration and impaired osteoclast differentiation. The high prevalence of uORFs in the human transcriptome suggests that intensified search for mutations within 5′ RNA leader regions may reveal a multitude of alterations affecting uORFs, causing pathogenic deregulation of protein expression. Defective translational control of protein expression is increasingly recognized as an important mechanism in the etiology of human diseases A growing body of evidence obtained from bioinformatic and genetic studies suggests that, in particular, uORF-mediated translational control may serve as a comprehensive mechanism of protein expression control. Recently, the targeted genetic ablation of the translational start site in the uORF of the transcription factor CCAAT/enhancer binding protein β (C/EBPβ) validated the physiological relevance of uORF-mediated translational control in an animal model This paper aims to provide a brief overview on uORF-mediated translational control in general. Moreover, we show how aberrant uORF regulation may translate into (patho)physiology, as illustrated by data obtained from analyses of C/EBP transcription factors. Finally, we outline how contemporary sequencing technologies may help to unravel the implications of uORF-mediated translational control in a multitude of as-yet-unexplained human diseases.iMet) ternary complex and additional eIFs, engages with the 7-methyl-guanosine (m7G) mRNA cap structure located at the 5′ end of a transcript iMet anticodon matches a functional AUG codon. Joining of the 60S ribosomal subunit completes the assembly of a fully functional ribosome and permits initiation of translation. Initially it was assumed that scanning ribosomes would generally initiate translation at the m7G-cap proximal AUG initiation codon Translation of eukaryotic transcripts follows a coordinated sequence of events, as summarized in the ribosomal scanning model of translation The yeast transcription factor GCN4 represents the best-studied example of uORF-mediated translational control and illustrates how uORFs can facilitate the paradoxical induction of GCN4 protein expression under conditions of reduced global translation Mechanistically, the expression of GCN4 is determined by the combined effects of leaky scanning and reinitiation events, which are sensitive to changing global translational conditions. Data obtained from the GCN4 transcript showed that the length of a uORF, the sequence context adjacent to its termination codon and the distance to the downstream initiation codon modulates the inhibitory effect of the uORF on ribosomal reinitiation in vivo and confirmed changing translation rates of the uORFs and the MCS of GCN4 in response to altered nutritional conditions Bioinformatic surveys have now identified uORFs in 35–49% of human and rodent transcripts 7G-cap, terminating upstream or downstream of the MCS initiation codon), sequence (no common uORF sequence motif has been identified) and secondary structure. In approximately half of the uORF-bearing transcripts, a single uORF precedes the MCS initiation codon uORFs are extremely diverse in both structural features and regulatory functions. As exemplified for humans, uORFs vary in length (average of 48 nt), number per transcript (0–13), position  and the full-length isoforms p42 and LAP)  and LAP RCCAUGG (Kozak consensus sequence), with a purine base in position −3 and a guanine base in position +4 as most important for initiation In most tissues, C/EBPα-p42 and C/EBPβ-LAP are the most abundant protein isoforms, despite the presence of two preceding translational initiation codons and despite a suboptimal initiation codon context . An optie.g. the differentiation of osteoclasts Several lines of evidence showed that the C/EBPα and β uORFs integrate the signaling status of a cell to modulate the expression ratio of isoforms. One key component in adjusting the activity of the translational machinery to environmental changes is the mammalian target of rapamycin kinase (mTOR). Many nutritional and signaling pathways downstream of growth factor-, cytokine-, or hormone receptors alter the activity of the mTOR kinase. Activated mTOR signaling is associated with enhanced global translational conditions and increased activity of important eIFs, including eIF4E Together, these data suggested that the uORF initiation codon may serve as a physiologically important sensor of global translational conditions, shifting the isoform expression ratio toward the truncated isoforms under favorable conditions and to the full-length isoforms under unfavorable conditions. This function may be due to the suboptimal Kozak context that surrounds the uORF initiation codon , which aΔuORF), now confirmed the concept of uORF-mediated isoform expression in vivo and contributed to a deeper understanding of how changes in the isoform ratio of C/EBPβ affect mammalian physiology ΔuORF mice were generated using homologous recombination into the endogenous c/ebpβ gene locus. The ΔuORF mutation eliminates the uORF initiation codon and thus disrupts its function as molecular switch to induce the truncated LIP isoform, without alteration of the amino acid sequence of C/EBPβ. Data obtained from the C/EBPβΔuORF homozygous mice showed that the C/EBPβ isoform production becomes unresponsive to extracellular stimuli, such as lipopolysaccharide treatment, which normally increases the LIP to LAP ratio LIP), the endogenous c/ebpβ gene locus was replaced by the coding sequence of the LIP isoform only, resulting in complete loss of expression of LAP* and LAP. The exclusive expression of LIP in these animals rescued both the expression of cell cycle genes and the entry of hepatocytes into S phase LIP mice displayed enhanced differentiation of bone-resorbing osteoclasts, while in turn, the decreased LIP to LAP isoform ratio in C/EBPβΔuORF mice showed an impaired osteoclast differentiation. The C/EBPβ LAP isoform was found to induce the expression of the transcription factor MafB in monocytes. MafB inhibits or sequesters other transcription factors that are known to mediate osteoclastic differentiation, including Fos, Nfatc1, and Mitf. In contrast, LIP downregulates MafB expression, resulting in increased availability of those osteoclastic transcription factors ΔuORF mouse comprises the first genetic animal model that confirms the physiological significance of uORF translation in vivo and its action as a molecular switch driving cell fate decisions by modulating isoform expression ratios. The in vivo data support the idea that the abundance of individual C/EBPβ isoforms is regulated by uORF-mediated integration of cellular signals, resulting in tissue-specific functions that depend on the cellular context.The recent generation of genetically altered mice, carrying a single nucleotide exchange of the ATG uORF initiation codon to TTG in the C/EBPβ gene  start sites are conserved, but the uORFhyp terminates five bases upstream of the p30 initiation codon only in humans, while in cow and mouse it overlaps the p30-coding sequence by 85 nucleotides. Given that all three potential uORF start sites are surrounded by intermediate or favorable Kozak consensus sequences, uORF-mediated translational control might be an additional level of C/EBPɛ expression regulation.Another example of how isoform expression ratios affect cell fate decisions comes from C/EBPɛ, the third C/EBP family member that is produced as various N-terminally truncated isoforms. The C/EBPɛ gene differs structurally from C/EBPα and β in that it contains introns. In addition to alternative translational initiation, the expression of four alternative C/EBPɛ isoforms  was attributed to differential promoter usage and alternative splicing. Similar to the short C/EBPα and β isoforms, the short C/EBPɛ isoforms display less trans-activation potential, with the shortest isoform (p14) virtually lacking trans-activating domains ΔuORF mice, naturally occurring uORF mutations in other genes may cause physiological alterations by deregulating translation of the affected transcript. Such mutations could either change the presence of a uORF by generating or deleting an initiation codon upstream of the MCS start site, or could affect translational control by changing one of the structural features of an existing uORF physiological importance of uORF translation in mice added a new level of significance to this cis-regulatory mechanism of translational control. C/EBPα and β transcription factors represent well-established examples of how translational control by uORFs may affect cell fate decisions. Accumulating evidence suggests that deregulated uORF function might be a widespread mechanism underlying the development of human diseases. The rapid progress in advanced sequencing technologies will permit screening approaches to identify causative uORF mutations in primary material derived from patients. Malignancies of the blood might be among the most suitable types of diseases to start such an analysis, as cell samples are readily accessible. One would, proteins . Given t


Drosophila, these repressors are recruited to sequence elements by DNA binding proteins associated with Polycomb repressive complex 2 (PRC2). However, the sequences that recruit PRC2 in mammalian cells have remained obscure. To address this, we integrated a series of engineered bacterial artificial chromosomes into embryonic stem (ES) cells and examined their chromatin. We found that a 44 kb region corresponding to the Zfpm2 locus initiates de novo recruitment of PRC2. We then pinpointed a CpG island within this locus as both necessary and sufficient for PRC2 recruitment. Based on this causal demonstration and prior genomic analyses, we hypothesized that large GC-rich elements depleted of activating transcription factor motifs mediate PRC2 recruitment in mammals. We validated this model in two ways. First, we showed that a constitutively active CpG island is able to recruit PRC2 after excision of a cluster of activating motifs. Second, we showed that two 1 kb sequence intervals from the Escherichia coli genome with GC-contents comparable to a mammalian CpG island are both capable of recruiting PRC2 when integrated into the ES cell genome. Our findings demonstrate a causal role for GC-rich sequences in PRC2 recruitment and implicate a specific subset of CpG islands depleted of activating motifs as instrumental for the initial localization of this key regulator in mammalian genomes.Polycomb proteins are epigenetic regulators that localize to developmental loci in the early embryo where they mediate lineage-specific gene repression. In  Key developmental genes are precisely turned on or off during development, thus creating a complex, multi-tissue embryo. The mechanism that keeps genes off, or repressed, is crucial to proper development. In embryonic stem cells, Polycomb repressive complex 2 (PRC2) is recruited to the promoters of these developmental genes and helps to maintain repression in the appropriate tissues through development. How PRC2 is initially recruited to these genes in the early embryo remains elusive. Here we experimentally demonstrate that stretches of GC-rich DNA, termed CpG islands, can initiate recruitment of PRC2 in embryonic stem cells when they are transcriptionally-inactive. Surprisingly, we find that GC-rich DNA from bacterial genomes can also initiate recruitment of PRC2 in embryonic stem cells. This supports a model where inactive GC-rich DNA can itself suffice to recruit PRC2 even in the absence of more complex DNA sequence motifs. Polycomb proteins are epigenetic regulators required for proper gene expression patterning in metazoans. The proteins reside in two main complexes, termed Polycomb repressive complex 1 and 2 (PRC1 and PRC2). PRC2 catalyzes histone H3 lysine 27 tri-methylation (K27me3), while PRC1 catalyzes histone H2A ubiquitination and mediates chromatin compaction Drosophila, where sequence elements termed Polycomb response elements (PREs) are able to direct these repressors to exogenous locations Drosophila genome Proper localization of PRC1 and PRC2 in the pluripotent genome is central to the complex developmental regulation orchestrated by these factors. However, the sequence determinants that underlie this initial landscape remain obscure. Polycomb recruitment is best understood in Drosophila PREs appear to be lacking in mammalian genomes Drosophila have functional homologs in mammals. The most compelling candidate has been YY1, a Pho homolog that rescues gene silencing when introduced into Pho-deficient Drosophila embryos While protein homologs of PRC1 and PRC2 are conserved in mammals, DNA sequence homologs of Recently, researchers identified two DNA sequence elements able to confer Polycomb repression in mammalian cells. Sing and colleagues identified a murine PRE-like element that regulates the MafB gene during neural development In addition to these locus-specific investigations, genomic studies have sought to define PRC2 targets and determinants in a systematic fashion. The Ezh2 and Suz12 subunits have been mapped in mouse and human ES cells by chromatin immunoprecipitation and microarrays (ChIP-chip) or high-throughput sequencing (ChIP-Seq) Drosophila PREs and lacks YY1 binding sites, but rather corresponds to an annotated CpG island. Based on this result and a genome-wide analysis of PRC2 target sequences we hypothesized that large GC-rich sequence elements lacking transcriptional activation signals represent general PRC2 recruitment elements. We tested this model by assaying the following DNA sequences: (i) a ‘housekeeping’ CpG island which was re-engineered by removal of a cluster of activating motifs; and (ii) two large GC-rich intervals from the E. coli genome that satisfy the criteria of mammalian CpG islands. We found that all three GC-rich elements robustly recruit PRC2 in ES cells. We propose that a class of CpG islands distinguished by a lack of activating motifs play causal roles in the initial localization of PRC2 and the subsequent coordination of epigenetic controls during mammalian development.Here we present the identification of multiple sequence elements capable of recruiting PRC2 in mammalian ES cells. This was achieved through an experimental approach in which engineered bacterial artificial chromosomes (BACs) were stably integrated into the ES cell genome. Evaluation of a series of modified BACs specifically identified a 1.7 kb DNA fragment that is both necessary and sufficient for PRC2 recruitment. The fragment does not share sequence characteristics of To identify DNA sequences capable of recruiting Polycomb repressors in mammalian cells, we engineered human BACs that correspond to genomic regions bound by these proteins in human ES cells.in situ hybridization (FISH) confirmed integration at a single genomic location  locus, which encodes a developmental transcription factor involved in heart and gonad development location .de novo recruitment of Polycomb in ES cells.We used ChIP and quantitative PCR (ChIP-qPCR) with human specific primers to examine the chromatin state of the newly incorporated hZfpm2 locus. This analysis revealed strong enrichment for K27me3 and K4me3 . In addiin vitroA key function of Polycomb repressors is to maintain a repressive chromatin state through cellular differentiation. To determine if the integrated BAC is capable of maintaining K27me3, the hZfpm2 transgenic ES cells were differentiated to neural progenitor (NP) cells We next sought to define the sequences within the hZfpm2 BAC required for recruitment of Polycomb repressors. First, we re-engineered the 44 kb hZfpm2 BAC to remove 20 kb of flanking sequences that contained distal non-coding conserved sequence elements . When weWe next asked whether the hZfpm2 CpG island is sufficient to recruit Polycomb repressors to an exogenous locus. To test this, we selected an unremarkable gene desert region on human chromosome 1 that shows no enrichment for PRC1, PRC2 or K27me3 in ES cells . We alsoThe functionality of a CpG island in PRC2 recruitment is consistent with prior observations that a majority of PRC2 sites in ES cells correspond to CpG islands Drosophila. We focused on motifs recognized by YY1, the nearest mammalian homolog of the Drosophila recruitment proteins. Notably, both of the recently described mammalian PREs contain YY1 motifs trans, it does not appear to be directly involved in PRC2 recruitment in ES cells.First, we searched for sequence motifs analogous to the PREs that recruit PRC2 in We previously reported that CpG islands bound by PRC2 in ES cells could be predicted based on a relative absence of activating transcription factor motifs (AMs) in their DNA sequence To obtain direct experimental support for the general sufficiency of large GC-rich elements lacking AMs in PRC2 recruitment, we carried out the following experiments. First, we tested whether a K4me3-only CpG island could be turned into a PRC2 recruitment element by removing activating motifs. We targeted a 1.3 kb CpG island that overlaps the promoters of two ubiquitously expressed genes – Arl3 and Sfxn2. Neither gene carries K27me3 in ES cells, or in any other cell type tested . We hypoE. coli, reasoning that there would be no selection for PRC2 recruiting elements in this prokaryote given the complete lack of chromatin regulators. We arbitrarily selected three 1 kb segments of the E. coli genome. Two with GC contents above the threshold for a mammalian CpG island but that each contained few AMs, and one AT rich segment as a control  that a motif devoid segment of an active ‘housekeeping’ CpG island can recruit PRC2; and (ii) that arbitrarily selected GC-rich elements from the E. coli genome can themselves mediate PRC2 recruitment when integrated into the ES cell genome.We find that DNA sequence is sufficient for proper localization of Polycomb repressive complexes in ES cells, and specifically identify a CpG island within the Zfpm2 locus as being critical for recruitment. We provide evidence that GC-rich elements lacking activating signals suffice Drosophila, as we do not find evidence for involvement of PRE-like sequence motifs or mammalian homologues such as YY1.Several possible mechanistic models could explain the causality of GC-rich DNA elements in PRC2 recruitment . First, It should be emphasized that PRC2 localization does not necessarily equate with epigenetic repression. Indeed virtually all PRC2 bound sites in ES cells, and all CpG islands tested here, are also enriched for K4me3, and presumably poised for activation upon differentiation. Epigenetic repression during differentiation may require PRC1 and thus depend on additional binding determinants. YY1 remains an intriguing candidate in this regard, given prior evidence for physical and genetic interactions with PRC1 BAC constructs CTD331719L (‘Zfpm2 44’), CTD-2535J16 (‘Pax5’) and CTD-3219L19 (‘Gene Desert’) were obtained from Open Biosystems. Recombineering was done using the RedET system (Open Biosystems) in DH10B cells. Homology arms 200–500 bp in length were PCR amplified and cloned into a PGK; Neomycin cassette (Gene Bridges). This cassette was used to recombineer all BACs to enable selection in mammalian cells. The 22 kb hZfpm2 BAC was created by restricting the hZfpm2 BAC at two sites using ClaI, and re-ligating the BAC lacking the intervening sequence. The CpG island was excised from the 22 kb hZfpm2 BAC by amplification of flanking homology arms, and cloned into a construct containing an adjacent ampicillin cassette . After recombination, the ampicillin cassette was removed using Flp-recombinase and selection for clones that lost ampicillin resistance . PCR across the region confirmed excision of the CpG island. For the Gene Desert BACs, the Zfpm2, Arl3, Sfxn2 and E. coli CpG islands were amplified with primers containing XhoI sites and cloned into the Frt-amp-Frt vector that contains homology arms from the Gene Desert region. The final constructs were confirmed by sequencing across recombination junctions. All primers used for CpG islands and recombineering homology arms are listed in 6 mouse ES cells, and selected 7–10 days with 150 µg/ml Geneticin (Invitrogen) on Neomycin resistant MEFs (Millipore). Individual resistant colonies were picked, expanded and tested for integration of the full length BAC by PCR. Differentiation of hZfpm2 ES cell clone 1 into a population of neural progenitor (NP) cells was done as previously described ES cells (V6.5) were maintained in ES cell medium  supplemented with 15% fetal calf serum (Hyclone), 0.1 mM ß-mercaptoethanol (Sigma), 2 mM Glutamax, 0.1 mM non-essential amino acid  and 1000U/ml recombinant leukemia inhibitory factor . Roughly 50 µg of linearized BAC was nucleofected using the mouse ES cell nucleofector kit (Lonza) into 10For each construct, between one and three ES cell clones were expanded and subjected to ChIP using antibody against K4me3 (Abcam ab8580 or Upstate/Millipore 07-473), K27me3 (Upstate/Millipore 07-449), Ezh2 (Active Motif 39103 or 39639), or Ring1B  as described previously 7 cells using antibody against YY1 (Santa Cruz Biotechnology sc-1703). ChIP DNA was used to prepare libraries which were sequenced on the Illumina Genome Analyzer. Density profiles were generated as described http://genome.ucsc.edu) were classified as positive for YY1, H3K4me3 or H3K27me3 if the read density was significantly enriched (p<10−3) over a background distribution based on randomized reads generated separately for each dataset to account for the varying degrees of sequencing depth. ChIP-Seq data for YY1 are deposited to the NCBI GEO database under the following accession number GSE25197 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GSE25197). Sites of Ezh2 enrichment (p<10−3) were calculated genomewide using sliding 1 kb windows, and enriched windows within 1 kb were merged. DNA methylation levels were calculated using previously published Reduced Representation Bisulphite Sequenced (RRBS) libraries Genomewide maps of YY1 binding sites were determined by ChIP-Seq as described previously −5. Candidate CpG islands for TF motif analysis were identified by scanning annotated CpG islands (http://genome.ucsc.edu) for asymmetric clustering of motifs related to transcriptional activation in ES cells E. coli K12 genome were selected by calculating %GC and CpG O/E in sliding 1 kb windows. Sequences matching the criteria for mammalian CpG islands while simultaneously being depleted of motifs related to transcriptional activation YY1 motifs were identified using the MAST algorithm Figure S1A schematic of the transgenic chromatin assay that was used to examine the role of DNA sequence in determining histone modification patterns in embryonic stem cells.(0.34 MB PDF)Click here for additional data file.Figure S2Transgenic mouse ES cells and associated mouse feeder cells were probed by FISH using Human BAC CTD331719L (hZFPM2), labeled with Cy3-dUTP (red), and a control mouse probe BAC , labeled with FITC-dUTP (green) along with DNA stained with DAPI (blue). A MEF feeder cell (A) shows two copies of the mouse probe (green arrows), and lacks a copy of hZfpm2. A transgenic ES cell (B) shows two copies of the mouse probe (green arrows) and one copy of hZFPM2 probe (red arrow).(0.51 MB PDF)Click here for additional data file.Figure S3(A) Two additional mES cell clones containing the 44 kb hZfpm2 locus were examined using ChIP-qPCR similar to (0.25 MB PDF)Click here for additional data file.Figure S4in vitro methylated BAC DNA are shown as controls. The underlined bases indicate sites of CG dinucletides.(A) Composite plots showing the lack of DNA methylation at both bivalent and K4me3 only promoters in mouse ES cells. (B) Schematic showing the CpG island of the Zfpm2 BAC remains free of DNA methylation upon integration into mouse ES cells. (C) The raw data used to create (B) shows aligned sequencing reads of Zfpm2 ES cell genomic DNA that was bisulfite treated see . Unmethy(0.22 MB PDF)Click here for additional data file.Figure S5(A) One additional mES cell clone containing 22 kb of the hZfpm2 locus was examined using ChIP-qPCR. As seen with the first clone  this clo(0.15 MB PDF)Click here for additional data file.Figure S6(A) The GC-richness and locations of YY1 motifs for the Zfpm2 locus are shown. (B) The 1.7 kb CpG island contains 4 conserved motifs see . (C) PRC(2.21 MB PDF)Click here for additional data file.Figure S7(A) Analysis of gene promoters with high CpG content (HCPs) shows Ezh2 positive promoters have significantly lower RNA-Seq scores compared to Ezh2 negative promoters. The dashed line represents the highest expression seen at LCPs. All transcriptionally inactive HCPs containing a single CpG island were scored for Ezh2 enrichment (see text and (0.41 MB PDF)Click here for additional data file.Figure S8One additional mES cell clone containing gene desert BAC with the Sfxn2 CpG island was examined using ChIP-qPCR. As seen with the first clone  this clo(0.15 MB PDF)Click here for additional data file.Figure S9(A) One additional mES cell clone for each E. coli DNA construct was analyzed by ChIP-qPCR. As seen with the first clones  the CpG (0.22 MB PDF)Click here for additional data file.Figure S10ChIP-qPCR shows Jarid2 enrichment signal at the CpG island (primer 6) of the 44 kb BAC (A), the Zfpm2 CpG island (primer Z1) within the Gene Desert BAC (B) and the GC-rich element  from E. Coli (C). Error Bars represent SEM (n = 2).(0.15 MB PDF)Click here for additional data file.Table S1YY1 bound sites in mouse ES cells and NS cells.(0.07 MB XLS)Click here for additional data file.Table S2Primer sequences used for recombineering and qPCR.(0.02 MB XLS)Click here for additional data file.Table S3E. Coli GC-rich and AT control segments.Motifs and sequences of (0.01 MB XLS)Click here for additional data file.