Hox genes impart segment identity to body structures along the anterior-posterior axis and are crucial for the proper development of all organisms. Multiple regulatory elements, best defined in Drosophila melanogaster, ensure that Hox expression patterns follow the spatial and temporal colinearity reflected in their tight genomic organization. However, the precise mechanisms that regulate colinear patterns of Hox gene expression remain unclear, especially in higher vertebrates where it is not fully determined how the distinct activation domains of the tightly clustered Hox genes are defined independently of each other. Here, we report the identification of a large number of novel cis-elements at mammalian Hox clusters that can help in regulating their precise expression pattern.Hox clusters that show poor association with histone H3 in chromatin immunoprecipitation (ChIP)-chip tiling arrays. The majority of these elements lie in the intergenic regions segregating adjacent Hox genes; we demonstrate that they possess efficient enhancer-blocking activity in mammalian cells. Further, we find that these histone-free intergenic regions bear GA repeat motifs and associate with the vertebrate homolog of the GAGA binding boundary factor. This suggests that they can act as GAGA factor-dependent chromatin boundaries that create independent domains, insulating each Hox gene from the influence of neighboring regulatory elements.We have identified DNA elements at all four murine Hox clusters. We further demarcate the precise location of several novel cis-elements bearing chromatin boundary activity that appear to segregate successive Hox genes. This reflects a pattern reminiscent of the organization of homeotic genes in Drosophila, where such regulatory elements have been characterized. Our findings thus provide new insights into the regulatory processes and evolutionarily conserved epigenetic mechanisms that control homeotic gene expression.Our results reveal a large number of potential regulatory elements throughout the murine  Hox genes specify segment identity during development: the unique combination of their expression pattern provides correct positional identity along the anterior-posterior (AP) body axis. The distinct organization of the Hox genes was first defined in Drosophila melanogaster[Hox complexes, however, are distinct from those seen in invertebrates. Through genome duplication events, vertebrates have at least four Hox clusters that are more organized, with all the genes transcribed in the same orientation and arranged more compactly than those in lower organisms [Hox genes. Their temporal order of activation, however, shows a difference; in Drosophila, the expression pattern of all the Hox genes is set simultaneously, while mammals show temporal colinearity by expressing their 3′ Hox genes first and then the more 5′ Hox genes sequentially from anterior to posterior during development [Hox gene regulation is highly dependent on genomic organization. It remains unclear how the colinear pattern of Hox gene expression in mammals is governed to provide discrete segment identity during development. In particular, it is not fully determined how the distinct activation domains of successive Hox genes are defined to maintain this spatial and temporal colinearity of expression. Mouse transgenes bearing regulatory regions of Hox genes faithfully recapitulate their expression domains [Hox gene expression are probably located in close proximity to the genes themselves, interspersed between coding regions within the conserved clusters. This arrangement may also allow enhancer sharing and promoter competition between the vertebrate Hox genes, providing an additional layer of regulatory control [Hox regulatory elements has not been clearly mapped in organisms other than Drosophila, where distinct regulatory domains control gene expression; most importantly, boundary elements flank each regulatory domain and define its limits in the bithorax complex [Hox clusters [anogaster and suchanogaster. Specifirganisms . The ordelopment ,5. These domains ,7, indic control . However complex . Chromat complex ,11. Home complex . Epigeneclusters .Hox clusters using custom-designed high-resolution chromatin immunoprecipitation (ChIP)-on-chip tiling arrays to reveal the presence of novel histone H3-free regions as potential regulatory elements. We show that most of these histone-depleted regions are associated with the vertebrate GAGA factor. Further, almost all intergenic regions at the Hox clusters show the presence of such histone-free regions that bear significant enhancer-blocking activity in human cells. These findings establish an association of the GAGA factor at specific intergenic chromatin structures that act as regulatory elements in mammalian Hox clusters. The observation that some of these regions can function as chromatin boundaries indicates a conserved mechanism of Hox gene expression regulated by distinct chromatin domains of each gene.Here, we have explored the chromatin regulatory features across all four murine Hox clusters, we designed a ChIP-on-chip tiling array including all 39 Hox genes along with their intergenic as well as upstream and downstream flanking regions. Synchronized G0 cells from the mouse C2C12 cell line were used to obtain a homogenous assay system for chromatin analysis, minimizing possible effects of cell type or cell cycle distribution and potential variations in the epigenetic state. Chromatin immunoprecipitation (ChIP) experiments with histone H3 antibodies were then performed for hybridization to the custom-designed tiling arrays.To obtain a complete picture of the epigenetic organization of the four murine Hox clusters in a defined pattern, as outlined for 150 kb of each of the Hox clusters in Figure Strikingly, ChIP-on-chip analysis revealed a consistent pattern of histone depletion at intergenic intervals across all arrays. The H3 ‘pan’ antibody against the carboxy terminus of histone H3  recognizes all forms of histone H3 and its modifications. We found that the binding of this antibody was depleted at many regions within the HoxA, HoxC, and HoxD clusters while the HoxB cluster showed the lowest occurrence of such regions. The HoxB cluster is different from the other Hox clusters in that the Hoxb13 gene is separated from the rest of the cluster by ~70 kb of DNA, in contrast with the other homeotic genes, which are closely spaced in all four clusters. Although the HoxB cluster maintains colinear expression of all its genes along the A-P body axis, the distant location of Hoxb13 is believed to contribute to its loss of expression along the secondary body axes, presumably owing to the absence of cis-regulatory features in the large intervening region, which also contains highly repetitive DNA sequences [HoxB cluster could explain the absence of HFRs in this part of the complex. The reason behind the low frequency of HFRs in the cluster as a whole is not clear, although it may suggest a relatively low regulatory complexity for this cluster.Nucleosome organization governs the accessibility of chromatin to regulatory complexes, increasing the binding of nonhistone proteins to target sites. Genome-wide chromatin studies have established the presence of regions with altered nucleosome occupancy, which often coincide with known regulatory elements, such as gene promoters, enhancers and transcription start and termination sites . The disequences . This unHox coding regions. A large number of the intergenic HFRs (64 HFRs) were located at intermediate positions between successive Hox genes or downstream to them. Apart from the Hox coding regions, we also checked the positions of intergenic noncoding transcripts as well as all CpG islands known at the Hox clusters. While 16 of the intergenic HFRs were found within noncoding transcribed regions, the remainder showed no overlap with any of these known intergenic features  of which only 9 were genic  enhancer and the γ-neo gene providing antibiotic resistance blocks promoter activation  that showed high enrichment with the core histone H3 antibody.To determine whether any of the newly identified HFRs marked potential boundary elements at the murine n Figure  inset, te effect . We usedboundary  as a posP < 0.0001) in the number of G-418 resistant colonies when cells were transfected with the target HFRs  and boundary elements [Hox clusters also bear such regulatory elements and this study provides a large-scale identification of such potential elements marked by their modified histone occupancy pattern. Not all the elements tested displayed strong boundary potential and it is possible that the enhancer blocking observed in some cases may be the manifestation of some other activity in their native context, as there are many ways that enhancer-promoter interactions can be disrupted [Hox gene expression in mammals.The disruption of histones exposes tructure . Reducedelements . In thisisrupted ,25. Basein vitro colony formation assay suggests their possible association with key regulatory factors at the murine Hox loci. We therefore subjected all the identified HFRs to sequence analysis and found multiple sites for the GAGA binding factor (GAF in Drosophila) at the histone-free regions, with the GAGAG motif appearing as the most frequent significant hit with a motif P < 0.0005 . Enrichment was assayed using multiple primers designed across 18 HFRs, including 13 that had shown high enhancer-blocking activity, as described in Figure Th-POK binding boundary region between Evx2-Hoxd13 characterized previously , positioned within the Hox gene bodies, did not show similarly robust association with the Th-POK antibody  is the best studied vertebrate boundary factor  and  domains . We ther cluster . CTCF ca cluster . It is pox genes .Drosophila, many cis-regulatory elements including boundaries within the homeotic complex are bound by GAF, and evidence suggests that altering the nucleosome occupancy might be a feature of such binding [Drosophila, which remain associated with HS sites regardless of a heat-shock event triggering the activation of the locus [The association of HFRs observed here appears to be specifically with the vertebrate GAGA factor and could possibly be the outcome of the nucleosome-reorganizing potential of GAF and not solely a feature of boundary activity. In  binding . To detehe locus .Hox genes. It remains to be determined if the histone depletion creates accessibility at these sites for enhancer-blocking function or if the GAF binding elements actively serve as anchors for directing the basic chromatin structure by histone disruption at the Hox complexes. dGAF plays a key role in directing chromatin architecture and driving nucleosome reorganization by recruiting remodeling complexes; its mutation has been shown to effect both histone replacement and associated boundary function at Hox complexes in Drosophila[Hox clusters. Since HFRs can provide sites for a multitude of target proteins and GAF can bind to various proteins to form regulatory complexes, looking for interacting partners at these sites will help identify other regulatory features at the HFRs. Taken together, our findings suggest a correlation between GAGA factor association at the histone-depleted regions and chromatin accessibility, providing functional significance to the presence of HFRs in the intergenic regions of mammalian Hox clusters.We hypothesize that the vertebrate GAF-associated intergenic HFRs described here may be important in maintaining the local chromatin conformation of rosophila. The preHox clusters potentially involved in higher-order chromatin regulatory mechanisms. In Drosophila, multiple elements, such as enhancers, insulators, and PREs, form regulatory units that determine and maintain the segment-specific expression pattern of the associated homeotic genes. In mammals, the regulatory elements driving colinear activation and maintenance of Hox expression have not been delineated. In this context, GAGA factor associated histone-depleted regions identified in the intergenic stretches between murine Hox genes suggest sites of potential regulatory function that could help demarcate their domains of expression. We have previously characterized a GA-rich intergenic tract between the Evx2 and Hoxd13 genes conserved among mouse, human, and zebrafish and demonstrated its functional conservation as an enhancer blocker in both transgenic flies and cultured human cells [HoxD locus [Th-POK as the vertebrate homolog of dGAF and indicated its potential to bind and regulate Hox clusters [Hox clusters with GAF recognition sites and Th-POK binding. These results indicate a strong correlation of HFRs associated with Th-POK binding as a general feature of mammalian Hox gene domain regulation and provide mechanistic insights into the possible role of the mammalian GAGA factor in nucleosome reorganization at the Hox clusters, thereby setting the stage for the binding of regulatory proteins to organize chromatin regulatory activities, including boundaries.This study used an epigenetic approach to identify a novel set of DNA elements at murine an cells . The regxD locus ; we havexD locus . We haveclusters . In thisHox genes across species but delineating the conserved organizational features of the Hox clusters can offer remarkable insights into their regulation. In this study, we have been able to identify over 90 such novel regions in the Hox clusters as HFRs and demonstrate the potential of many of the intergenic HFRs to function as chromatin regulatory elements. Our work indicates a genome-wide association for such structures and demonstrates that a lack of enrichment of histone H3 at specific genomic sites in ChIP-on-chip binding assays can serve as a marker for the identification of novel regulatory elements in a context-specific manner.Finally, sequence comparison might not directly identify homologous regulatory elements of the 5 cells/ml in DMEM containing 1.3% methyl cellulose, 20% FBS, 10 mM HEPES, and 1 × Penicillin-Streptomycin. Suspended cells were harvested after 48 h, during which time 98% of cells were arrested at the quiescent G0 stage [C2C12 skeletal muscle myoblasts were cultured as described previously . UndiffeG0 stage , by dilu7 synchronized cells. Cells were harvested as described and fixed using 1% formaldehyde (Fisher Scientific) in growth medium for 10 minutes at 37°C and quenched with 0.125 M Glycine (Sigma). Fixed cells were washed well with 1 × PBS containing protease inhibitors at 4°C and resuspended in 2 ml lysis buffer supplemented with PMSF, DTT, and protease inhibitor cocktail (Roche). Following 15 min incubation on ice, the sample was sonicated using Bioruptor (Diagnode) to obtain fragments of average size 200 bp to 600 bp. The sonicated chromatin was divided into 200 μl aliquots for chromatin immunoprecipitation (ChIP) using the ChIP assay kit  according to the manufacturer’s protocol. ChIP was performed on precleared chromatin from 106 cells using rabbit polyclonal antibodies against core histone H3 , H3K4me3 , H3K27me3 , Th-POK , or CTCF . Unenriched input fraction was retained as control in each case. ChIP and input samples were subjected to array hybridization or real time qPCR assays to determine enrichment.Chromatin was crosslinked and isolated from 10Hox clusters was designed with 60-mer probes  tiled continuously with a 10 bp overlap between consecutive probes for high resolution (Agilent Technologies). Repeat masking was used to avoid repeat sequences and other probes with cross hybridizing potential. Dual-color microarray hybridization experiments were carried out according to the manufacturer’s protocol. Briefly, samples recovered from the enriched fraction and unenriched whole cell extracts (input DNA) from two parallel experiments were independently pooled to obtain optimal yields for direct array hybridization, thus minimizing bias introduced during ligation-mediated PCR amplification of DNA fragments. The pooled enriched and input fractions were directly labeled with Cy5 and Cy3 dyes, respectively, using an Agilent Genomic DNA labeling kit (5190–0449) and hybridized onto the mouse custom arrays at 65°C for 40 h followed by washing. Scanned microarrays were submitted for background subtraction and data extraction to Agilent’s Feature Extraction. Normalized enrichment values for the probes were identified using DNA Analytics software. Probe data were normalized using default blanks subtraction and intra-array dye-bias median normalization and P values were assigned to groups of neighboring probes using the Whitehead error model.A custom mouse genome microarray chip representing 1.1 Mb of the mouse genome consisting of the four The ChIP-on-chip signals were normalized with input DNA signals hybridized to the same arrays and the NLRs of the probes thus obtained were visualized on the Mouse NCBI37/mm9 Assembly in the UCSC genome browser . AdditioHox clusters from the histone H3 tiling array were used to identify unenriched genomic stretches using an in-house PERL script. The extent of each target region was determined based on a defined cut-off for the number of consecutive probes that showed a negative NLR value with the histone H3 antibody. Briefly, the probe dataset from each cluster was divided into groups of five contiguous probes and each was classified as a ‘low enrichment’ group if at least three probes in the group had an NLR <0. Continuous blocks of low enrichment groups were extended until two or more consecutive high enrichment groups were encountered or if a genomic distance >200 bp was encountered between successive probes. These poorly enriched genomic stretches were classified as histone H3-free regions or HFRs and subjected to further analysis for ChIP-qPCR , NLR values of the probes within the Hox genes and all noncoding transcripts (downloaded from the Tromer database) using Geneious [Genomic sequences of HFR stretches from each of the clusters were extracted from the mouse reference assembly MGSCv37-C57BL/6J of NCBI build 37.2 and subjected to motif search analysis using the MEME Suite of tools . The HFRGeneious .Hox clusters were amplified as test fragments from mouse genomic DNA using primers designed with Xho 1 restriction sites at their 5′ ends  at the Hox clusters (x axis). (A) Large stretches of histone H3 unenriched probes showing negative NLR values across all the arrays are highlighted by boxed regions. Map of all the HFRs (green boxes) further identified by bioinformatics analysis of the probe binding data is presented at the bottom for each cluster. (B) H3K4me3 and H3K27me3 peaks called in the custom tiling arrays show that the HoxB and HoxD clusters are highly enriched for the H3K27me3 mark in G0 cells, as reported previously for proliferating myoblasts and myotubes [HoxA and HoxC clusters do not share this feature but show some association with H3K4me3. These trends are comparable with those seen in the ChIP-seq data from ENCODE using C2C12 cells (brown tracks). Genomic scale bar is indicated at the top. Figure S2. Map of GAGA motifs and CTCF sites across Hox clusters. Schematic map  depicting the location of all the GAGA motifs identified by sequence analysis as well as the CTCF sites identified by ChIP-seq in C2C12 cells from the mouse ENCODE project as obtained from the UCSC genome browser . Green boxes indicate HFRs while red bars mark GAGA motifs and grey bars mark CTCF sites. Blue boxes denote the Hox genes with transcriptional orientation; the large intronic regions of Hoxa3 and Hoxd3 genes have been omitted for clarity. Figure S3. DNaseI HS peaks in context of HFRs at the Hox clusters. Schematic map  depicting the location of all the peaks of DNaseI hypersensitivity identified in skeletal muscle (blue track), mesoderm (black track) and embryonic stem cells (maroon track) from the mouse ENCODE project . Green boxes indicate the HFRs while blue boxes denote the Hox genes with transcriptional orientation; the large intronic regions of Hoxa3 and Hoxd3 genes have been omitted for clarity. Table S1. Classification of HFRs identified in the three histone arrays. Table S2. List of GAGA factor binding motifs at the Hox clusters. Table S3. HFRs overlapping with DNaseI HS sites. Table S4. List of primers for ChIP-qPCR assays. Table S5. List of primers for cloning test fragments for boundary assays.HFRs across all arrays using histone H3 antibodies. Screenshots from the tiling array data obtained using pan histone H3 (blue track), H3K4me3 (pink track) and H3K27me3 (green track) antibodies, visualized using the UCSC genome browser showing normalized log ratio (NLR) values of probes (myotubes ; genes iClick here for fileNormalized log ratio values for probes at Hox clusters.Click here for file


Ewing's sarcoma family tumors (ESFT) are characterized by specific chromosomal translocations, which give rise to EWS-ETS chimeric proteins. These aberrant transcription factors are the main pathogenic drivers of ESFT. Elucidation of the factors influencing EWS-ETS expression and/or activity will guide the development of novel therapeutic agents against this fatal disease. EWS-ETS gene rearrangements affecting EWSR1 and genes of the ETS-family of transcription factors, predominantly FLI1 characterizing 85% of cases [ESFT comprise a group of undifferentiated, highly malignant small blue round-cell pediatric tumors. They are genetically characterized by of cases , 3 and iof cases –6. It haof cases , 8. WhilSince, due to its tumor-specific expression, EWS-FLI1 protein is considered an ideal therapeutic target , signifiEWS comprising the EWS activation domain (EAD). The EAD structure consists of multiple degenerate hexapeptide repeats (consensus SYGQQS) with a conserved tyrosine residue. However, systematic mutagenesis of the EAD revealed that the overall sequence composition and not the specific sequence of the degenerate hexapeptide repeat confer EAD activity [EWS-fusion proteins contain at least the N-terminal 7 exons of activity . The C-tactivity . Mutatioactivity .Transcriptional regulation is tightly controlled by transcription factor binding to regulatory regions within DNA as well as recruitment of cofactors. Although ETS transcription factors bind predominantly as monomers to a GGAA/T core motif in promoter or enhancer regions of their target genes, functional interaction between ETS proteins and other factors is crucial to enhance or modulate DNA binding . Even thin vitro [However, transcriptional control also involves complex upstream signaling pathways that converge on the posttranslational modification of transcription factors and their interacting cofactors. Phosphorylation and glycosylation are two examples of posttranslationally modifying mechanisms affecting EWS-FLI1 activity. The EWS portion of about 20% of EWS-FLI1 fusion proteins (those that retain EWS amino acids 256 to 285) contains a conserved calmodulin-binding motif within the IQ domain with a phosphorylated internal Protein Kinase C recognition site at Ser 266 . Mutatioin vitro , 10. Furin vitro . Glycosyin vitro . EWS-FLIin vitro . In addiin vitro . The higin vitro , 52. Lovin vitro . Since bin vitro , and sinBiochemical purification and analysis identified EWS-FLI1 as an intrinsically disordered protein , 78. Intin vivo and in vitro, a potential novel therapeutic strategy [in silico analyses reveal a significant enrichment of E2F binding sites in EWS-FLI1 upregulated genes suggesting an important role of the E2F family of transcription factors in EWS-FLI mediated transcriptional regulation [EWS-FLI1 is generally perceived as a transcriptional activator –81. Consstrategy , 53. Intstrategy . It is lstrategy . Recent in vitro and in vivo via interaction with the EWS amino terminal domain [In addition to transcriptional activation, an at least equal number of genes are downregulated by EWS-FLI1 as are upregulated . One expl domain . In addil domain . Since El domain , the funp53 or p16/p14ARF are found in approximately 10% and 25% of cases, respectively. As in most pediatric malignancies, the majority of ESFT express wild-type p53 and p16/14ARF genes [The p53 and INK4A (p16/p14ARF) pathways are critical in promoting cell cycle arrest in response to mitogenic signals, and mutations in their key components facilitate tumor progression in most cancer types , 90. In RF genes –32. FuncRF genes .α [α-dependent manner [α-mediated EWS-FLI1 accumulation involved protein regulation at the FLI1 moiety, since the observed protein accumulation was restricted to EWS-FLI1 and neither observed for full-length EWS nor for an alternative EWS fusion to ERG. On the transcriptional level, however, the upregulation of EWS-FLI1 protein did not simply result in a reinforcement of the EWS-FLI1 transcriptional signature, but showed a more complex effect with both synergistic and antagonistic consequences on EWS-FLI1 regulated genes [α and necrotic areas in an ESFT tissue array, suggesting a role for hypoxia in in vivo induction of HIF-1α [Hypoxia is a common condition in solid tumors. It drives cancer cells towards a coordinated set of survival responses altering the transcriptional regulation of many genes , stimulaα , to chemα , and to α . Interest manner . HIF-1α-ed genes . Anotherf HIF-1α . Data thin vitro [in vivo [The autocrine loops encompassing (IGF-1)/(IGF-1R) and (IGF-2)/(IGF-2R) play a crucial role in the proliferation and survival of ESFT cells via activation of AKT and ERK1/2 –40. Notain vitro  and in v[in vivo , blocks [in vivo , induces[in vivo , and inc[in vivo . A further growth factor positively interacting with EWS-FLI1 activity is basic fibroblast growth factor (bFGF). bFGF was demonstrated to trigger EWS-FLI1 expression in serum-depleted ESFT cells. A neutralizing antibody against bFGF was able to disrupt this upregulation and inhibit expression of the fusion protein in a broad panel of ESFT cell lines . No deteMost recently, a further putative signalling molecule that is expressed on the cell surface, the bladder cancer associated protein BLCAP, carrying a putative Ser-Pro-X-X motif and a proline-rich area, was reported to modulate EWS-FLI1 expression . The mecMicroRNAs (miRNAs) are small (21–24 nucleotides), single-stranded, and noncoding RNAs that regulate gene expression in a variety of cellular processes . By bindWhile the role of aberrantly expressed miRNAs is well established in adult cancers, only few studies exist for pediatric malignancies in general and sarcomas in particular –109. OneHowever, a recent global miRNA profiling study in the A673 ESFT cell line did not confirm miR-145 among EWS-FLI1 suppressed miRNAs but described a group of EWS-FLI1 repressed miRNAs  with predicted targets in the IGF-1/IGF-1R signaling pathway , a key gId2 [p53 or p16/p14ARF mutations form a subset with particularly poor prognosis, highly aggressive behaviour, and poor chemoresponse [The existence of tumor-specific alterations in several cancers presents a unique opportunity for pharmacological intervention to therapeutic benefit. Although EWS-FLI1 has only been identified in tumor cells and therefore provides a potential ideal therapeutic target, ESFT has so far remained a targetable disease without a targeted drug , 114. SuId2 . A betteId2 . As suchId2 . Some esId2 –65 and aId2  and resiId2  the receId2  may raisId2 –58 or inId2  showing Id2 . A meta-response , 141. Nuresponse , 67. As response , 142–145response , Mithramresponse , and ARAresponse  althoughresponse . MethodsWhile attempts to understand the pathobiology of ESFT have focused mainly on identifying EWS-FLI1 target genes and downstream pathways, there are still many important unresolved questions regarding factors modulating EWS-FLI1 activity. Manipulation of these factors may offer therapeutic promise since it is difficult to directly target a transcription factor. This may be achieved by applying high throughput compound screening technologies as has been performed to block EWS-FLI1 interaction with RNA helicase A , 53, andin vivo to achieve tumor growth inhibition was demonstrated in this study [The list of agents influencing EWS-FLI1 fusion protein activity and/or expression is consistently enriched. Some of them show crosstalk, as has been demonstrated between a group of EWS-FLI1 repressed miRNAs and targets of IGF-1/IGF-1R pathway . Since vis study . For a b


Cellular differentiation entails reprogramming of the transcriptome from apluripotent to a unipotent fate. This process was suggested to coincide with aglobal increase of repressive heterochromatin, which results in a reduction oftranscriptional plasticity and potential. Here we report the dynamics of thetranscriptome and an abundant heterochromatic histone modification,dimethylation of histone H3 at lysine 9 (H3K9me2), during neuronaldifferentiation of embryonic stem cells. In contrast to the prevailing model, wefind H3K9me2 to occupy over 50% of chromosomal regions already in stemcells. Marked are most genomic regions that are devoid of transcription and asubgroup of histone modifications. Importantly, no global increase occurs duringdifferentiation, but discrete local changes of H3K9me2 particularly at genicregions can be detected. Mirroring the cell fate change, many genes show alteredexpression upon differentiation. Quantitative sequencing of transcriptsdemonstrates however that the total number of active genes is equal between stemcells and several tested differentiated cell types. Together, these findingsreveal high prevalence of a heterochromatic mark in stem cells and challenge themodel of low abundance of epigenetic repression and resulting global basal leveltranscription in stem cells. This suggests that cellular differentiation entailslocal rather than global changes in epigenetic repression and transcriptionalactivity. per se unique in regards to heterochromatinabundance and transcriptional plasticity as compared to somatic cells. Instead,focal changes in chromatin might help to stabilize cellular states at anydevelopmental stage.Epigenetic modifications of DNA and bound histones are major determinants of celltype–specific gene expression patterns. A prevalent model in stem cellbiology suggests that the loss of pluripotency entails global increase inheterochromatin and coinciding shutdown of lineage unrelated genes. We performedanalysis of both H3K9 dimethylation pattern and the global transcriptome in anadvanced murine neuronal differentiation model. In this paradigm, we do not findevidence for a global increase in heterochromatic H3K9 dimethylation orreduction of transcriptome complexity as stem cells become terminallydifferentiated post-mitotic neurons. This suggests that pluripotent embryonicstem cells are not  Resetting of the transcriptional program is the key driver for cell typespecification during organismal development Here, we set out to test the model of widespread heterochromatinization viamonitoring of the differentiation-coupled dynamics of H3K9me2, a repressiveepigenetic modification, which appears to be the most abundant heterochromaticmodification and has recently been reported to cover large domains in differentiatedcells invitro neurogenesis model To asses differentiation associated dynamics of the repressive histonemodification H3K9me2 we made use of a highly pure and robust murine Given the high prevalence of H3K9me2, we next asked how its presence relates to adistinct repressive chromatin modification, namely trimethylation of H3K27(H3K27me3). This mark is set by the Polycomb pathway and often occurs in domainsof several kilobases We further related H3K9me2 occupancy to regions with transcriptional activity orpresence of the active modification H3K4me2. Active regions are mutuallyexclusive with H3K9me2 in ES cells but surprisingly to a lesser extent inneurons . Thecomin vitrodifferentiation system, we grouped the genes that could not clearly be assignedto the on or off state, into a separate class of genes expressed at low tobackground level . RNAseq in ES cells andderived neurons revealed the expected down regulation of stem cell specificgenes and induction of neuron specific genes . Furthernd level . This anic cells ,their nic cells . Moreoveic cells .Embryonic stem cells are characterized by their potential to differentiate into anycell type of the three germ layers in the developing embryo, while somatic cellslose this developmental plasticity upon lineage-commitment. Despite its relevancefor our understanding of development and disease, the molecular determinants ofpluripotency are still not fully understood and the factors responsible for thisuniqueness of stem cells are actively debated These findings disagree with a recent report that suggested absence of large H3K9me2domains in ES cells and found a striking increase in differentiated cells Widespread low-level expression in stem cells has previously been reported andinterpreted as a sign of pluripotency In summary, our analysis suggests to revisit the model of massiveheterochromatinization during cellular differentiation via a global increase inrepressive histone marks Our data together with previous reports on dynamics of DNA methylation, H3K9me3 andthe Polycomb pathway between pluripotent and somatic cells Wild-type embryonic stem cells (129Sv-C57Bl/6) were cultured and differentiatedas previously described Peptide sequences can be found in ChIP experiments were performed as described before H3K9me2 ChIP samples were hybridized to custom designed microarrays representingall well-annotated promoters, several large multi-gene loci and the completechromosome 19 with an average probe spacing of 100 bp and a total of 2.1 millionfeatures .Sample labeling, hybridization and array scanning were performed by NimbleGenSystems Inc. according to standard procedures. For analysis, raw fluorescentintensity values were used to calculate log2 of the bound/input ratios for eachindividual oligo. Subsequently, for comparison all arrays were normalized to amedian log2 = 0 and scale normalized to have the samemedian absolute deviation using the “LIMMA” R/Bioconductor packageMusmusculus transcriptome and normalized to transcript length andsequencing library size .Microarray and deep sequencing data were deposited at NCBI's Gene ExpressionOmnibus and are accessible through GEO Series accession number GSE27866 were spotted ontopolyvinylidene difluoride membranes (GE) and probed with (A)anti-dimethyl-H3K9  or (B) anti-dimethyl-H3K9 (Abcamno. 1220) at 1∶1000 dilution each. Both antibodies are highly specifictowards H3K9me2.(TIF)Click here for additional data file.Figure S2High similarity of ES cell H3K9me2 datasets. (A) Comparison of our H3K9me2enrichment profiles in ES cells to a previously generated ES cell profile. (B) Venn diagram illustrating the overlap ofH3K9me2-occupied regions between the two ES cell datasets from (A) (definedby an HMM approach). The overlap agrees with the high correlation for thispreviously generated ES cell dataset with our two ES cell replicates.(TIF)Click here for additional data file.Figure S3H3K9me2 enrichments on chromosome 19 are representative of the entire genome.(A) H3K9me2 enrichments in ES cells from a previously generated dataset . The boxplots show H3K9me2 enrichment values for all probesseparated by chromosome, with chromosome 19 highlighted in blue. (B) H3K9me2enrichments per 900 bp promoter windows  in EScells. The boxplots represent average enrichments at promoters separated bychromosome with chromosome 19 highlighted in blue.(TIF)Click here for additional data file.Figure S4H3K9me2 enriched regions are robustly identified independent of HMMparameters and H3K9me2 domain size is highly similar in ES cells andneurons. (A) Shown is the comparison of H3K9me2 enrichments in ES cells andneurons using a 3 state HMM to define non-occupied (low), intermediately andhighly occupied domains (top). Importantly, the state specific HMMdistribution parameters (mean and variance of H3K9me2 enrichment) are verysimilar between ES cells and neurons (bottom). Note that with a 3 state HMMthe percentage of domains in the high state does not change between ES cellsand neurons (TN). However, we detect an overall increase of the intermediatestate of around 10%. (B) H3K9me2 domains were defined by HMM see. While n(TIF)Click here for additional data file.Figure S5Regions that lose are smaller than regions that gain H3K9me2 duringdifferentiation and gaining regions often overlap with gene bodies. (A andB) Histograms displaying the size distributions of regions that lose (A) andgain (B) H3K9me2 during neuronal differentiation. Adjacent 500 bp windowsbeing in a low HMM state in both ES cell replicates and in a high HMM statein the neuron replicates were grouped into H3K9me2 losing and gainingregions, respectively. (C) Pie chart illustrating the percentage of large(>10kb) H3K9me2 gaining regions within (grey) and outside (white) ofgenes (left). This overlap is significantly higher than for all regions thathave no H3K9me2 in ES cells, i.e. which are in a HMM low state in bothreplicates (right). (D) Boxplot showing expression levels of all genes that gain H3K9me2in neurons. Note that the median expression does not change significantlybetween ES cells and neurons (TN), indicating that there is no global trendtowards either up- or down-regulation upon accumulation of H3K9me2 in thegene bodies of these genes.(TIF)Click here for additional data file.Figure S6Hprt, which does not carry H3K9me2. Theloss of enrichment in neurons is small, though reproducible.Regions losing H3K9me2 during differentiation are close to background.(A–C) Shown are representative genomic regions that significantly loseH3K9me2 as defined by HMM analysis. (D) ChIP-real time PCR validation of theregions shown in (A–C). Note that H3K9me2 enrichments are already lowin ES and only slightly above background as exemplified by the activehousekeeping gene (TIF)Click here for additional data file.Figure S7H3K9me2 in neurons rarely overlaps with promoter regions of active genes. (Aand B) Pie chart illustrating the percentage of promoters (1 kb up- anddownstream of TSS) (A) and gene bodies (B) of transcribed genes that overlapH3K9me2-occupied regions in neurons. Note that promoters are rarely H3K9dimethylated when the gene is actively transcribed.(TIF)Click here for additional data file.Figure S8Overlap of low-level expressed genes and expression of transcripts perchromosome. (A) Venn diagram illustrating the overlap of transcriptsexpressed at a low level (log2 RNAseq reads between 2 and 5) in at least oneof the examined cell types. Note that areas are not drawn to scale. (B)Boxplots showing expression levels of transcripts per chromosomes.(TIF)Click here for additional data file.Figure S9Absence of difference in transcriptome complexity is not a function of samplesize in next generation sequencing. Shown is the number of detected Refseqtranscripts (at least 32 reads) relative to the number of sampled reads.Number of detected transcripts is shown as the mean of 100 rounds of randomsubsampling with the same total read numbers. Irrespective of the samplesize, a random sampling of RNAseq reads from ES cells (green line), neurons(dark green line) and MEFs (red line) revealed a smaller number of detectedtranscripts than an artificial sample with pooled reads from all three celltypes (blue line) at any given sample size.(TIF)Click here for additional data file.Figure S10H3K9me2 domain definition by different statistical methods leads to similarresults. (A) HMM-independent quantification of genomic coverage of H3K9me2in ES cells and neurons. Shown is the percentage of chromosome 19 that lieswithin H3K9me2 peaks defined by a simple threshold method Click here for additional data file.Table S1List of real time PCR primers.(TIF)Click here for additional data file.Table S2Peptides used in dot blots in (TIF)Click here for additional data file.Text S1Supplementary methods.(DOC)Click here for additional data file.


NF-kappaB transcriptional activation is required for skeletal muscle disuse atrophy. We are continuing to study how the activation of NF-kB regulates the genes that encode the protein products that cause atrophy. Using ChIP-sequencing we found that Bcl-3, an NF-kB transcriptional activator required for atrophy, binds to the promoters of a number of genes whose collective function describes two major aspects of muscle wasting. By means of bioinformatics analysis of ChIP-sequencing data we found Bcl-3 to be directing transcription networks of proteolysis and energy metabolism. The proteolytic arm of the Bcl-3 networks includes many E3 ligases associated with proteasomal protein degradation, including that of the N-end rule pathway. The metabolic arm appears to be involved in organizing the change from oxidative phosphorylation to glycolysis in atrophying muscle. For one gene, MuRF1, ChIP-sequencing data identified the location of Bcl-3 and p50 binding in the promoter region which directed the creation of deletant and base-substitution mutations of MuRF1 promoter constructs to determine the effect on gene transcription. The results provide the first direct confirmation that the NF-kB binding site is involved in the muscle unloading regulation of MuRF1. Finally, we have combined the ChIP-sequencing results with gene expression microarray data from unloaded muscle to map several direct targets of Bcl-3 that are transcription factors whose own targets describe a set of indirect targets for NF-kB in atrophy. ChIP-sequencing provides the first molecular explanation for the finding that Bcl3 knockout mice are resistant to disuse muscle atrophy. Mapping the transcriptional regulation of muscle atrophy requires an unbiased analysis of the whole genome, which we show is now possible with ChIP-sequencing. Skeletal muscle atrophy is the result of a metabolic shift that increases the rate of proteolysis and/or decreases the rate protein synthesis in the cells that make up muscle. The initiating triggers for this shift are varied, but fall into two main categories: the result of a disease or pathology such as cancer, diabetes, HIV, major body burns, and sepsis, or the loss of muscle as a result of immobilization, bed rest, diaphragm breathing assistance, or decreases in gravity as in space travel Investigations into the signaling pathways activated by muscle disuse due to the removal of weight bearing  discovered that nuclear factor-kappaB (NF-kB) activity was increased early and continuously In the present study, we focused on finding the direct target genes of NF-kB transcription factors during muscle unloading in order to identify the genes producing atrophy. We used chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), a recently developed method in which the location of particular transcription factors is mapped to the whole genome during physiological or pathological changes. The active molecules of NF-kB consist of a protein complex with two or more subunits. In the case of p50 and Bcl-3 the active molecule is thought to consist of a homodimer of p50, which contains the DNA recognition and binding activity, and a bound molecule of Bcl-3 which has two transactivation domains for the induction of gene expression For the gene expression array and for ChIP-seq, 7-week-old female wild type mice (C57BL/6J) were purchased from the Jackson Laboratory . Animals were provided with chow and water ad libitum and housed individually in Boston University Animal Care Facility. After 3 days of acclimation, mice were randomly assigned to weight-bearing (WB) or hind limb unloaded (HU) groups. Mice in the HU group had their hind limbs elevated off the cage floor for 5 days to induce unloading induced muscle atrophy, as described previously For reporter activity measurements, 7-week-old female Wistar rats from Charles River Lab  were used. 40 µg of wild type or mutant MuRF1-promoter reporters were transfected into rat soleus muscle as previously described Gastrocnemius and plantaris muscles were isolated from weight bearing  or 5 day hind limb unloaded mice. Freshly dissected muscle was minced and cross-linked in 1% formaldehyde for 15 minutes, quenched with glycine and then frozen in liquid nitrogen. Tissues from four legs were pooled, homogenized, and chromatin isolated as we detailed previously For the Bcl-3 ChIP we pooled two separate ChIP-seq experiments by combining.bam forms of the alignments. There were 40 million sequence reads in the control samples, of which 20.4 million were unique, and there were 52 million sequence reads in the unloaded samples of which 25.9 million were unique. The aligned sequences converted to.sam format were uploaded to the peak finder program in ChIPseeqer T values of the unknown sample to the gene-specific standard curve and normalized to the expression of beta-actin.Gastrocnemius and plantaris muscles harvested from anesthetized wild type mice from control and HU groups (n = 6 per group) were snap frozen in liquid nitrogen and stored at −80°C before use. Total RNA was isolated using the Qiagen miRNeasy Mini kit  according to manufacturer’s instructions. Extracted total RNA was treated with RNase-Free DNase I , quantitated by UV spectrophotometry, and quality checked by a 1% denaturing agarose gel as previously described P-value ≤0.05 and q-value ≤0.05 were used to identify genes that were significantly differentially expressed with hind limb unloading. The microarray data reported in this paper have been deposited in the NCBI Gene Expression Omnibus (GEO) with accession no. GSE40578.Whole-genome gene expression profiling experiments were carried out by the Boston University Microarray Core Facility. Each group (control and unloaded) included 4 independent total RNA samples with a minimal RIN number 8.0 verified by Bioanalyzer 2100 . Each total RNA sample was amplified, labeled, and hybridized on a mouse Affymetrix Gene 1.0 ST array  per manufacture instructions to measure expression of 28,853 well-annotated genes. A total of 8 array images were acquired by GeneChip Scanner 3000 7G and quality assessed by Affymetrix Expression Console . Gene expression signals were generated by robust multi-array analysis (RMA) In silico analysis of transcription factor binding sites in this 4.4 kb MuRF1 promoter region was performed by Clover ctg aaa agt GAG ttt tct agt gac aat ccc aaa gag-3′, κB2 5′- ccc aaa gag cac aga ctt aCT Caa gtt cca gcg cta cca g-3′, κB3 5′- ccg ccc atg tgg gaa ctt GAG cat ctc acc ctt tga ctt-3′. A reaction was performed by mixing 100 ng of each phosphorylated primer, 100 ng MuRF1-luc, 1.25 U PfuUltra High-fidelity DNA polymerase (Agilent), and 20 U Taq DNA ligase  and then the PCR was carried out in a thermal cycler set as follows: 95°C for 2 min (denature), 30 cycles of 95°C for 50 sec, 60°C for 50 sec, and 68°C for 5 min, and followed by a final incubation at 68°C for 5 min (extension). After DpnI treatment, amplified PCR products were transformed into XL10-Gold Ultracompetent bacteria (Agilent) according to manufacturer’s instructions. The DNA sequences of the wild type MuRF1 reporter, MuRF1 deletant, and the MuRF1 3 κB mutant constructs were verified by Genewiz sequencing services .The mouse MuRF1 promoter luciferase plasmid which contains 4.4 kb of the 5′ upstream MuRF1 promoter region was a gift from S. Shoelson Soleus muscles transfected with plasmid DNA were homogenized in 1 mL passive lysis buffer . Homogenates were centrifuged at 5,500 g at 4°C for 20 min. Supernatant was collected, diluted 1∶20, and mixed with 100 µl luciferase assay reagents (Promega). Luciferase activity was measured by a TD-20/20 illuminometer (Turner Designs Inc), which reflected total muscle luciferase activity.P value less than 0.05 was considered statistically significant.For RT-qPCR and luciferase activity, a two-tailed independent t-test was performed to determine statistical significance between WB and HU groups. A Since transcriptional activation of the p50-Bcl-3 complex will not happen without Bcl-3 We then took the sequence alignments from unloaded muscle Bcl-3 ChIP-seq and compared them to weight bearing muscle sequences in order to find peaks that were at least 2-fold increased using the peak finder in ChIPseeqer. By using this level of stringency for peak finding we obtained 2,817 Bcl-3 peaks in unloaded compared to weight bearing muscle. Phastcon analysis using the Cistrome/Galaxy program To find the important functional groups of genes that show increased Bcl-3 binding with muscle unloading, we evaluated the peaks found in unloaded compared to control muscle for gene ontology terms/pathways. To do this we used the iPAGE algorithm, a module of the ChIPseeqer set of computational programs . iPAGE whttp://www.broadinstitute.org/igv/) and are shown in The most abundant group with 14 genes in 11 GO pathways was for protein catabolism. The genes are ones that function in several aspects of catabolism in muscle including several E3 ligases of the ubiquitin proteasome pathway, and importantly, two genes that contribute to the cell catabolism driven by the N-end rule. Those genes are Ubr1/E3α, the N-end recognin E3 ligase, and Ate1, the arginyltransferase responsible for modifying several amino acid amino termini for Ubr1 recognition. The sequence alignments and locations for the peaks for these two genes have been visualized by use of Integrative Genomics Viewer (IGV) Also found in the GO pathways and shown in The advantage of iPAGE is that it can find the most important functions of the overrepresented genes having peaks with unloading in an unbiased fashion. However, there are other genes with Bcl-3 peaks in the promoter region that are likely to be important to atrophy. For example, several proteolytic pathway genes not identified by iPAGE also show Bcl-3 peaks with unloading . For transcription factors, Foxo1, Foxo3, and Cebpa show peaks as well as several translation initiating genes including Eif4b and Eif3f. All of the genes with unloading-induced increased Bcl-3 binding in their promoters are listed in Since we were interested in further describing direct and indirect targets of the Bcl-3 transactivator at the genome-wide level, we used the algorithms of ChIPArray In a previous paper, we found genes to be direct or indirect targets of Bcl-3 based on gene expression in unloaded muscle from wild type vs. Bcl3 knockout mice. We selected several of these genes for further study that were thought to be involved with the atrophy process. We identified NF-kB sites in these genes in silico and we found ChIP-PCR support for increased Bcl-3 binding In weight bearing and unloaded muscle, we compared the MuRF1 promoter-reporter activity from the 4.4 kb promoter and a smaller MuRF1 reporter in which the 5′ end was deleted by removing the 2 kb upstream region containing all 3 NF-kB sites. We also compared a MuRF1 reporter in which site mutagenesis was used to abolish the 3 NF-kB sites located at −3.1, −4.1, and −4.2 kb of the 4.4 kb promoter . From thThe location of unloading-induced Bcl-3 binding in promoters across the genome demonstrates a remarkable molecular genetic association between this NF-kB transcription factor and the atrophy process in unloaded muscle. The most impressive finding is the degree to which protein catabolic pathways were targeted by this Bcl-3 regulatory network. The impartial gene ontology algorithm called iPage was able to indicate that the major part of the over-represented genes with Bcl-3 peaks due to unloading were involved in protein degradation or its signaling. Of the 23 GO terms found, 11 were catabolic. In those groups there were 14 genes. Six of these genes were E3 ubiquitin protein ligases. Of interest is that one of the E3s is Ubr1, the gene also known as E3α ligase. It is one of the major recognition ligases for ubiquitinating proteins that have destabilizing amino acids at their N termini. It is noted in the literature that the ubiquitination present in atrophy is largely due to the activation of the N-end rule pathway For one E3 ubiquitin ligase, MuRF1, we investigated the importance of the NF-kB sites in the promoter region, found by our ChIP-seq data and by in silico analysis, with MuRF1 promoter-reporter activity due to muscle unloading. Deletion of the distal 2 kb region of the 4.4 kb MuRF1 promoter construct contained all the putative NF-kB sites. Unloading induced activation of MuRF1 was abolished in this deletant MuRF1 reporter. The remaining 2.4 kb of the proximal MuRF1 promoter contains consensus sites for other factors such as Foxo (not shown) suggesting that it is not required for unloading regulation of MuRF1. We found that consistent with our ChIP-seq binding data, the mutagenesis of NF-kB sites also eliminated unloading-induced activation of the MuRF1 reporter.A number of GO pathways identified in our results are involved with glucose metabolism, and the genes include phosphofructokinase, the rate limiting enzyme of the glycolysis pathway, and muscle glycogen phosphorylase, the enzyme responsible for liberating glucose from muscle glycogen stores. In a separate study, phosphofructokinase was found upregulated in unloaded rat muscles, reflecting a change to increased glycolysis and use of glycogen stores with disuse http://wanglab.hku.hk/ChIP-Array). Previously we postulated that our results from gene expression arrays for unloading in wild type vs. Bcl3 knockout mice had indicated a set of indirect and direct targets. We felt that the use of ChIP-seq would determine, by showing binding of Bcl-3 to complexes on the target genes, that these were direct targets. With that accomplished we knew that some of the direct targets of Bcl-3 should be the factors that cause the gene expression array changes in the indirect targets. This is difficult to determine by searching within the results of ChIP-seq, but ChIPArray is able to show these relationships. From the ChIP-Array results we have found 5 new candidate transcription factors, most notably including Max, that appear to extend the Bcl-3 gene activation network in muscle atrophy.In order to further explore the combination of our ChIP-seq data and that from our extensive work on the changes in gene expression with unloading, we used the network-available algorithms for ChIP and expression array analysis available from ChIPArray We have provided, in the plots of sequence alignments and peaks, the location of alignments for p50. It is thought that Bcl-3 binds to DNA by an association with p50 or p52 homodimers With this first assay of the binding of Bcl-3 to promoter regions of genes during muscle atrophy it is quite clear that Bcl-3 regulates transcriptional networks of the genes involved in muscle catabolism and metabolism. These data provide the molecular evidence to explain why Bcl-3 knockout mice do not show unloading atrophy. Our data describe Bcl-3 as a global regulator both of the proteolysis and the change in energy metabolism that are essential components of muscle atrophy due to disuse. We have identified for the first time, gene networks that are determined by the binding of a transcription factor (Bcl-3) that is required for muscle atrophy. Gene networks of other transcription factors involved in disuse and other causes of muscle atrophy are yet to be identified but their study, using methods similar to the ones we have pioneered here, will be of great interest in order to complete our understanding of the molecular biology of skeletal muscle atrophy.Figure S1Galaxy/Cistrome-found distribution of Bcl-3 peaks over the mouse genome for each chromosome. Red vertical lines show the peak heights and indicate the low stringency 49,000 Bcl-3 peaks that were greater in unloaded vs. control muscle. The position of each peak is plotted from the beginning to end of the chromosome with scale indicated in base pairs by a ruler at the bottom of the graph.(TIF)Click here for additional data file.Figure S2A graph of the results of transfecting MuRF1-luciferase reporter plasmids into Bcl3−/− fibroblasts with and without addition of a Bcl-3 expression vector. A cell line of fibroblasts was isolated from the gastrocnemius muscles of a Bcl3 knockout mouse by enzyme dissociation. The cells were transfected with Effectene (Qiagen) and luciferase activity was measured after 48 hours. Luciferase activity is induced by 11 fold when Bcl-3 is supplemented to the reporter-transfected cells, while mutagenesis of the three NF-κB sites in that reporter reduces this induction by 40%.(TIF)Click here for additional data file.Table S1A table of the 858 genes with ChIPseeqer-defined Bcl-3 binding peaks in their promoter regions (−4kb to +2kb relative to TSS). The 845 peaks in promoters from the 2817 total peaks of unloading vs. control Bcl-3 binding map to 858 genes since some peaks are within guideline distances of the TSS of two genes. A cursory assignment of gene categories and functions was carried out using the Gene database of NCBI (http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene). The columns are A, Functional Category (in the broad sense); B, Gene Symbol; C, Gene Function Description; and D–H supplemental and alternative functional information for some of the genes.(XLSX)Click here for additional data file.


Mycobacterium tuberculosis. The transcriptional programs and cellular pathways that are regulated by IRF8 in response to IFNγ and that are important for defenses against M. tuberculosis are poorly understood. These were investigated by transcript profiling and chromatin immunoprecipitation on microarrays (ChIP-chip). Studies in primary macrophages identified 368 genes that are regulated by IRF8 in response to IFNγ/CpG and that behave as stably segregating expression signatures (eQTLs) in F2 mice fixed for a wild-type or mutant allele at IRF8. A total of 319 IRF8 binding sites were identified on promoters genome-wide (ChIP-chip) in macrophages treated with IFNγ/CpG, defining a functional G/AGAAnTGAAA motif. An analysis of the genes bearing a functional IRF8 binding site, and showing regulation by IFNγ/CpG in macrophages and/or in M. tuberculosis-infected lungs, revealed a striking enrichment for the pathways of antigen processing and presentation, including multiple structural and enzymatic components of the Class I and Class II MHC (major histocompatibility complex) antigen presentation machinery. Also significantly enriched as IRF8 targets are the group of endomembrane- and phagosome-associated small GTPases of the IRG (immunity-related GTPases) and GBP (guanylate binding proteins) families. These results identify IRF8 as a key regulator of early response pathways in myeloid cells, including phagosome maturation, antigen processing, and antigen presentation by myeloid cells.IRF8 (Interferon Regulatory Factor 8) plays an important role in defenses against intracellular pathogens, including several aspects of myeloid cells function. It is required for ontogeny and maturation of macrophages and dendritic cells, for activation of anti-microbial defenses, and for production of the Th1-polarizing cytokine interleukin-12 (IL-12) in response to interferon gamma (IFNγ) and protection against infection with  Mycobacterium tuberculosis.IRF8 is a member of the Interferon Regulatory Factor family that is expressed in myeloid cells such as macrophages and dendritic cells and that activates or represses gene transcription upon stimulation with interferon gamma (IFNγ), lipopolysaccharide (LPS), and other microbial stimuli. IRF8 plays an important role in several aspects of myeloid cells, including differentiation and maturation of early progenitor cells, expression of intrinsic anti-microbial defenses, and production of the interleukin-12 (IL12) cytokine, which is essential for priming of early T cell– mediated immune response. IRF8 mutant mice are susceptible to a number of intracellular infections including pulmonary tuberculosis. The transcriptional and cellular pathways regulated by IRF8 and essential for resistance to infections were studied by a combination of genome-wide methods, including transcriptional profiling and chromatin immunoprecipitation (ChIP-chip). These studies identified phagosome maturation, antigen processing, and antigen presentation as critical pathways in early host–pathogen interactions regulated by IRF8 in macrophages exposed to IFNγ/CpG and in lung tissues infected with  The defense mechanisms of mononuclear phagocytes that are circumvented by successful intracellular pathogens are poorly understood Mycobacterium, Salmonella and Leishmania, is determined in part by the natural resistance-associated macrophage protein 1 (Nramp1) gene (Slc11a1). In resistant mice, Slc11a1 functions as an efflux pump for Fe2+ and Mn2+ ions at the membrane of microbe-containing phagosomes formed in macrophages, thereby restricting microbial access to these essential nutrients SLC11A1 have been associated with differential susceptibility to mycobacterial infections including tuberculosis, leprosy, and Buruli ulcer SLC11A1 alleles associated with tuberculosis susceptibility in field studies, display reduced functional activity of the SLC11A1 protein Slc11a1 identified the BXH2 mouse strain as highly susceptible to Mycobacterium bovis  infection despite presence of resistance-associated Slc11a1 alleles (Gly169Slc11a1) R294C) in the interferon regulatory factor 8 (IRF8) (Ensembl:ENSMUSG00000041515) In inbred mouse strains, susceptibility to infection with several intracellular pathogens including GGAAnnGAAA), the ETS-IRF response element  or to the IRF-ETS composite sequence GGAA) ex vivo infection with M. bovisSalmonella typhimuriumLegionella pneumophila+CD8α+ DCs and pDCs +CD8α+ and CD8α− DCs present in these mice remain immature and fail to up-regulate co-stimulatory molecules and to produce key cytokines in response to microbial products −/−IRF8 mice do not produce IL-12p40, lack Th1 polarization , and are susceptible to in vivo infection with intracellular pathogens IRF8 is one of 9 members of the Interferon Regulatory Factor (IRF) family. IRF8 has a DNA binding domain  of the helix-turn-helix type that binds to ISRE (Interferon Stimulated Response Elements) sites present in the proximal promoters of type II IFN-regulated genes. IRF8 also has an IRF association domain (IAD) that serves as a recruitment module for other transcription factors. IRF8 is expressed primarily in macrophages and dendritic cells, but is also detected in T and B lymphocytes R294CIRF8 isoform of BXH2 behaves as a partial loss-of-function which is associated with impaired IL-12p40 production by BXH2 splenocytes, and loss of trans-activation of a IL-12p40 reporter construct in vitro. The R294CIRF8 mutation results in increased M. bovis (BCG) multiplication both early and late during infection, with uncontrolled replication linked to inability to form granulomas in infected liver and spleen. The R294CIRF8 mutation also causes susceptibility to S. typhimurium to a level comparable to that seen for mice lacking functional Nramp1 or Tlr4 (Toll-like receptor 4), and impairs innate and adaptive immune defenses against the blood-stage malarial parasite Plasmodium chabaudi AS Mycobacterium tuberculosis, showing uncontrolled intracellular pathogen replication in lung macrophages, impaired granuloma formation, rapid dissemination of the infection to distant sites, and rapid necrosis of infected tissues, and early death. There was complete absence of IL-12p40 induction, severely reduced IFNγ production, and impaired T cell priming in the lungs of infected BXH2, highlighting the critical role of IRF8 in this response We have shown that the in vivo. In these studies, we incorporated an experimental strategy based on the co-segregation of IRF8-dependent differential gene expression in macrophages from [BALB/c×BXH2] F2 animals selected for homozygosity for either wild-type  or mutant (C294IRF8) IRF8 alleles. These studies have identified a critical role for IRF8 in regulating expression of genes and associated cellular pathways responsible for early interaction with pathogens, phagosome maturation, antigen processing and antigen presentation to CD4+ and CD8+ T cells.In this study, we have used transcript profiling with microarrays and chromatin immunoprecipitation (ChIP) hybridization on genomic DNA arrays (ChIP-chip) in macrophages from normal and IRF8-deficient mice, to systematically identify genes transcriptionally regulated by IRF8 a) during ontogeny and maturation of macrophages, and b) in response of these cells to combined exposure to IFNγ and Tlr9 (Toll-like receptor 9) ligand (CpG), and c) during pulmonary tuberculosis IRF8 (R294C). For this, we used bone marrow-derived macrophages (BMDMs) from individual [BALB/c×BXH2] F2 mice of mixed genetic background but that were identified as homozygote for either wt (R294IRF8) or mutant (C294IRF8) IRF8 alleles. This strategy IRF8 genotypes but that show mixed genetic background , can distinguish true IRF8-dependent effects from irrelevant ones caused by differences in genetic background of the two parental mouse strains. This strategy is well suited to study eQTLs caused by absence versus presence of a transcription factor such as IRF8. In this approach, individual F2 mice  are used both as biological and technical replicates, to increase the stringency of the analysis. BMDMs from wt and C294IRF8 F2 mice were stimulated or not with IFNγ/CpG, and RNA was isolated and used for transcript profiling.To identify transcriptional targets of IRF8 that play a role in a) macrophage maturation, and b) in activation in response to IFNγ and microbial products, we used transcript profiling to compare RNA expression in macrophages bearing either a wild-type (wt) or a mutant allele at IRF8 have defects in these cell types IRF8 mutant F2 mice  identified a total of 454 genes differentially expressed in an IRF8-dependent fashion in these cells at basal level , b) cytokines and chemokines production and signaling , c) growth regulation (Csf3r), d) tissue remodeling , and e) rapid response to microbial insults  –, [3s virus)  [38]. KEs virus) . Finallys virus)  [39]– F2 mice of mixed genetic background but genotyped for the two IRF8 alleles. This was done to increase the stringency of the analysis, and to distinguish true IRF8-dependent effects on gene expression from irrelevant ones resulting from differences in genetic background of the wt (C57BL/6J) and mutant animals . This approach has been shown to be well suited to map genome-wide eQTLs that segregate as a result of presence or absence of a specific transcription factor C294IRF8 mutant mice, and corresponds to genes which basal level of expression in macrophages is influenced by IRF8 (n = 454). However, because IRF8 plays an important role in maturation of the myeloid lineage C294IRF8 mutant mice treated with IFNγ/CpG (IRF8 genes regulated during macrophage activation). Two sub-lists were generated, one obtained by pairwise comparison, and the other generated by a 2×2 interaction (Anova) analysis which takes into account IRF8-dependent differences in basal level of expression in absence of IFNγ/CpG stimulation (n = 368). Using ChIP-chip experiments with chromatin prepared from IFNγ/CpG activated macrophages and immunoprecipitated with anti-IRF8 antibodies, we identified a total of 319 IRF8 binding events  on a promoter tiling array. From this information, we further extracted two overlaps and associated critical gene lists. The first one contains 145 genes and corresponds to IRF8 targets (bound by IRF8) that are regulated by exposure to IFNγ/CpG in wt F2 macrophages in vitro. The second one contains 359 genes and corresponds to IRF8 targets (bound by IRF8) that are regulated during pulmonary infection with M. tuberculosis in vivo. The above-mentioned lists were generated by comparing wt cells to those from BXH2 that bear the severely hypomorphic C294Irf8 allele; nevertheless, small amounts of residual activity may remain in C294Irf8 and gene lists obtained with this mutant may differ somewhat from those obtained by comparing wt cell to cells bearing a null −/−Irf8 allele.In this study, we have used transcript profiling and chromatin immunoprecipitation on microarrays (ChIP-chip) to investigate the role of IRF8 in macrophage function, activation by IFNγ/CpG, and response to M. tuberculosis in vivo. A striking feature of these lists is the preponderance of IRF8 targets associated with antigen recognition, processing and presentation by antigen presenting cells (APCs). APCs include dendritic cells, macrophages and B lymphocytes. These cells capture either soluble or particulate antigen by scanning different areas of the body including epithelial surfaces, degrade this antigen and present to T-lymphocytes to activate immune responses. Although virtually all cells can present processed peptide antigens to T cells in association with Class I MHC molecules, so-called “professional APCs” present a wide range of antigens to T cells in association with Class II MHC molecules. Many of the genes coding for proteins involved in antigen recognition, antigen degradation, translocation to a suitable secretory compartment and Class I and Class II molecules are encoded by genes within the major histocompatibility locus (MHC) on mouse Chr. 17 and human Chr. 6.These two gene lists are the most biologically relevant with respect to the role of IRF8 in macrophage function and defenses against + T cells leading to destruction of the infected cells. In addition, Class I MHC antigen presentation is up-regulated by INFα, β, and γ as well as by LT and TNFα. As shown in M. tuberculosis-infected mice in vivo. These include the PA28 subunit of the proteasome, the TAP1/TAP2 transport system and associated tapasin (Tapap), ER aminopeptidase (Erap1), as well as Class I MHC a chain, β2 microglobulin and associated ER chaperone Calnexin.Presentation of cytosolic peptides via association with Class I MHC molecules occurs in all cells, and is critical for protection against viral infection. It involves proteasome-mediated degradation of viral or other proteins into short peptides, which are then translocated into the endoplasmic reticulum (ER) via the tapasin-associated (Tapap in the ER lumen) ABC transporter heterodimer TAP1/TAP2. Such peptides entering the ER are further trimmed by ER-specific aminopeptidases to fit on the Class I MHC binding site formed by the Class I α chain in association with β2 microglobulin. Peptide-bound Class I complexes are then released from tapasin-chaperone complexes to be delivered to the cell surface, where they can interact with cytolytic CD8+ helper T cells to induce production of effector T cells, activation of macrophages to microbicidal function, and antibody production depending on the type of APC involved. The process of Class II MHC antigen presentation can itself be stimulated by secretory products of APCs (e.g IL12) or T cells (IFNγ). As shown in Tlr4/9/13, members of the Cathepsin family of proteases, Class II MHC molecules, Ii, and HLA-DM. Together, these results establish a critical role for IRF8 in regulation of the key programmes of antigen presentation in APC. These results are in good agreement with the reported profound defect of IRF8 mutant mice in the DCs compartment, as they lack both CD11c+CD8α+ DCs and pDCs, and the small number of CD11c+CD8α+ and CD8α− DCs present in these mice remain immature and fail to up-regulate co-stimulatory molecules and produce key cytokines in response to microbial products in vitro and in vivo during pulmonary tuberculosis in vitroOn the other hand, antigen presentation via the Class II MHC pathway is carried out by specialized APCs. It involves antigen capture via the endosomal or phagosomal routes through initial interaction with specific cell surface receptors of the TLR (Toll-like receptor), C3R (complement-3 receptor), FcR (Fc receptor) and Ig (immunoglobulin) families. These antigens are digested by members of the cathepsin family of Cys/Asp proteases in acidic endosomes, lysosomes and phagolysosomes. Class II MHC α and β chains stabilized by chaperones are associated with non-polymorphic Ii protein which prevents antigen binding at the α/β interface. Delivery of this complex to antigen-containing acidified endosomes/lysosomes causes proteolytic degradation of Ii (Cd74), leaving only the CLIP (Class II-associated invariant chain peptide) portion of Ii in the antigen binding site. This CLIP peptide is then removed by the HLA-DM  protein (H2M in mice), freeing up the antigen binding site. Antigen-bound Class II complexes are delivered to the cell surface where they can interact with CD4M. tuberculosis infection in vivo and that contain a IRF8 binding site in their vicinity map to the MHC locus (9 fold enrichment), with 12 IRF8 binding sites mapping near 27 regulated genes  is a non-DNA binding co-activator that binds to the so-called “MHCII enhanceosome” multiprotein complex and that serves as a master control factor for MHCII gene expression Ciita expression is up-regulated by IFNγ in a STAT1-dependent fashion; through the presence of GAS (Gamma interferon activation site) element in the proximal PIV responsive promoter in the Ciita gene Ciita expression is tightly regulated by IFNγ/CpG in an IRF8-dependent fashion in macrophages from F2 mice . Therefore, it is possible that IRF8-mediated control of MHC gene expression involves amplification by other transcriptional regulators such as Ciita.Many of the genes implicated in Class I and Class II MHC antigen presentation are located within the boundaries of the MHC locus. In this locus, we note a striking over-representation of binding sites for IRF8 and the number of genes which expression is regulated by IFNγ/CpG in macrophages. In the case of genes bound by IRF8 and regulated by IFNγ/CpG in macrophages , ∼10% of them map to the MHC region on Chr. 17, with 11 binding sites mapping near 16 regulated genes. This concentration of direct IRF8 targets genes corresponds to a 14 fold enrichment over genome-wide representation of these 145 genes. Likewise, ∼10% of the genes regulated by ed genes . The regM. tuberculosisToxoplasma gondii2) and PI3,4,5P3in vivo in M. tuberculosis infected lungs  , p65 (GBPs) and Dynamin (Mx) families which are known to be essential for protection against intracellular bacterial, parasitic and viral infections  [40]. Thed lungs , but we ct SLIP) , and Gbpct SLIP) , with moct SLIP) . Althougde novo IRF8 binding motif described herein  or mutant  IRF8 allele were identified and used in the transcript profiling experiments. IRF8 alleles were identified by genotyping for the proximal marker D8Mit13 using oligonucleotide primer pairs 5′-CCTCTCTCCAGCCCTGTAAG-3′ and 5′-AACGTTTGTGCTAAGTGGCC-3′, which distinguishes between BALB/cJ and C57BL/6J, the strain background of the IRF8 genomic segment onto which the R294C mutation appeared in BXH2 D8Mit13 alleles were carried out as described C57BL/6J (B6) mice were purchased from the Jackson Laboratory . Recombinant inbred BXH2 mice were originally derived by B. Taylor at the Jackson Laboratory 2-containing humidified air. BMDMs were isolated from femurs of 8- to 12-week-old mice and were cultured in DMEM (Sigma) containing 10% heat-inactivated fetal bovine serum (HI-FBS), 20% L-cell-conditioned medium (LCCM), 100 U/ml penicillin, and 100 µg/ml streptomycin in bacteriological grade dishes (Fisher) at 37°C in a humidified atmosphere containing 5% CO2. Seven days later, cells were harvested by gentle washing of the monolayer with phosphate-buffered saline containing citrate. Cells were plated in 150-mm tissue culture-grade plastic plates  in DMEM containing 10% HI-FBS, 10% LCCM, 100 U/ml penicillin, and 100 µg/ml streptomycin. In some experiments, macrophages were primed with IFNγ (50 U/ml) for 18 hrs, prior to stimulation (3 hrs) with recombinant mouse IFNγ , and CpG DNA oligonucleotides (5′-TCCATGACGTTCCTGACGTT-3′) used at a concentration of 400 U/ml and 1,5 µg/ml, respectively. IFNγ and CpG stimulate both the IFNγ receptor and Tlr9, and engagement of both receptors stimulates IRF8 expression, via STAT1, NFKB and possibly other pathways The mouse macrophage cell line J774 was grown in Dulbecco's modified Eagle's medium  supplemented with 10% heat-inactivated fetal bovine serum , 100 U/ml penicillin, and 50 µg/ml streptomycin (Invitrogen) at 37°C, in 5% COt test p value of 0.05 and a fold-change cutoff of 1.5X. Hierarchical clustering based on complete linkage method was applied to evaluate the effect of the different sources of variability . Complete microarray data (accession no. E-MEXP-2962) has been deposited in the ArrayExpress database (www.ebi.ac.uk/microarray-as/ae/).Total RNA was extracted from BMDMs obtained from 6 individual mice per experimental group, either prior to or 3 hrs following stimulation of BMDMs with IFNγ (400 U/ml) and CpG DNA . IFNγ/CpG-stimulated macrophages were initially primed with IFNγ (50 U/ml) for 18 hrs. Purified RNAs were analyzed for integrity by gel electrophoresis, and were then hybridized to microarrays (Illumina Mouse WG-6 v2.0 Expression BeadChip) according to the manufacturer's recommended experimental protocol. To minimize technical variability, RNA processing steps  were executed in parallel for all samples. The GeneSifter™ microarray data analysis system  was used to examine data generated from comparisons between control (unstimulated) and IFNγ/CpG-stimulated (3 hrs) groups. Log transformed data were normalized and transcripts showing differential expression were identified by pairwise, or two-way (2×2 interaction) Anova analysis with a Hprt gene was used as a constitutively expressed internal control to normalize the mRNA levels of target genes.The expression of individual mRNAs was measured by quantitative PCR (qPCR) amplification of cDNA transcripts generated by reverse transcriptase (RT). Briefly, RNA samples (n = 6) used for transcriptional profiling were pooled and 3 µg of pooled RNA was converted to cDNA using Moloney murine leukemia virus (Invitrogen) in a 20 µl reaction according to the manufacturer's recommended experimental protocol. PCR amplification was performed using Quantitech SYBR Green PCR kit (Qiagen), and all samples were measured in duplicate. Each reaction contained 2 µl of cDNA template, 1 µl of the target-specific primer pair (each primer at 5 µM), 9.5 µl of RNase-free water and 12.5 µl of Quantitech SYBR Green PCR master mix. PCR amplification included an initial denaturation step (10 min at 95°C) followed by 50 cycles of amplification , and was performed using the 7500 Real Time PCR system (Applied Biosystems). PCR primers were designed to generate amplicons ranging from 100 to 150 bp. The 2-terminal portion of Ii) are all detected by the In-1 mAb BMDMs were obtained from wt (B6) and IRF8 mutant (BXH2) mice, either prior to or following stimulation (4 and 24 hrs) with IFNγ (400 U/ml) and CpG DNA . Whole cell extracts (75 µg per lane) were subjected to 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS–PAGE), followed by electroblotting and overnight incubation with the monoclonal anti-Cd74 (Ii) antibody (clone In-1 purchased from BD Pharmingen) (used at 1∶200). Immune complexes were revealed with a horseradish peroxidase-conjugated goat anti-rat antibody (used at 1∶3000) and visualized by enhanced chemiluminescence . Intact p41 and p31 Ii, as well as SLIP Ii fragment , and further purified using the QIAquick PCR purification kit (Qiagen).ChIP assays were performed on J774 macrophages stimulated with IFNγ/CpG for 3 hours, according to a method previously described Sample preparation for hybridization to promoter arrays was carried out as recommended in Agilent Mammalian ChIP-on-chip protocol, with minor modifications. Briefly, the ChIP DNA was amplified by ligation-mediated PCR (LM-PCR) following DNA blunting and linker ligation. The LM-PCR samples were purified on QIAquick purification columns and submitted to 18 additional rounds of amplification in the presence of aminoallyl-dUTP . The LM-PCR samples containing aminoallyl-dUTP were purified (QIAquick PCR purification columns) and labeled with Cy3 and Cy5 dies. The DNA amount was calculated by using the OD at 260 and 320, and the Cy3 and Cy5 incorporation was also determined.Samples were hybridized to Agilent 244K mouse extended promoter arrays containing ∼17,000 of the best-defined mouse transcripts as defined by RefSeq spanning the regions from −5.5 kb upstream to +2.5 kb downstream of the transcription start site. The procedure was done according to the Agilent mammalian ChIP on chip protocol version 9.2. Following the hybridization at 65°C for 40 hrs, the arrays were washed and scanned using a GenePix 4000B scanner and data was extracted from the images using Agilent Feature Extraction software as described in the mammalian ChIP on chip protocol . Data from ChIP-chips were normalized and averaged using ChIP Analytics 1.3 software. Data was processed in ChIP Analytics using the intra-array Lowess normalization, Whitehead Error Model v1.0 and Whitehead Per-Array Neighbourhood Model v1.0 for peak detection and evaluation. The default parameters were used to identify significant binding events .de novo binding motif analyses with 3 different algorithms: MEME de novo binding motif were generated with WebLogo We retrieved from the UCSC genome browser 500 bp sequences centered on each 319 IRF8 ChIP-chip and performed We used the DAVID  website to calculate GO and KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment in our different ChIP-chip and expression datasets  Figure S1de novo motif finding with three different algorithms: MEME, MDscan and AlignACE De novo transcription factor binding motif analyses on IRF8 ChIP-chip binding sites. (A) 500 bp of sequence flanking the 319 IRF8 binding peaks were queried for (TIF)Click here for additional data file.Figure S2Validation of members of the Gbp (p65) and Irgm (p47) families at protein level. BMDMs total proteins were obtained from wt (B6) and IRF8 mutant (BXH2) mice either prior to (unstimulated control) or following stimulation with IFNγ/CpG (4 hrs and 24 hrs post-stimulation), separated in 10% SDS-PAGE (35 µg of lysate/lane) and probed with specific antibodies. β-actin was used as a constitutively expressed internal control to normalize the protein levels.(TIF)Click here for additional data file.Table S1Genes differentially regulated at basal level in wt versus IRF8 mutant macrophages .(XLS)Click here for additional data file.Table S2Genes differentially regulated in wt versus IRF8 mutant macrophages at basal level, and modulated by IFNγ/CpG stimulation .(XLS)Click here for additional data file.Table S3Genes differentially modulated by IRF8 in wt versus IRF8 mutant BMDMs in response to IFNγ/CpG exposure .(XLS)Click here for additional data file.Table S4List of IRF8 ChIP-chip binding sites.(XLS)Click here for additional data file.Table S5Known transcription factor binding motifs enrichment analysis.(XLS)Click here for additional data file.Table S6Gene Ontology and KEGG pathways enrichment analysis.(XLS)Click here for additional data file.Table S7M. tuberculosis-infected B6 mice for 30 days.Intersection between IRF8 ChIP-chip binding sites and differentially regulated genes in IFNγ/CpG treated F2 mice or (XLS)Click here for additional data file.Table S8Intersection between IRF8 target lists from Ref. (XLS)Click here for additional data file.


The HIF1- and HIF2-mediated transcriptional responses play critical roles in solid tumor progression. Despite significant similarities, including their binding to promoters of both HIF1 and HIF2 target genes, HIF1 and HIF2 proteins activate unique subsets of target genes under hypoxia. The mechanism for HIF target gene specificity has remained unclear. Using siRNA or inhibitor, we previously reported that STAT3 or USF2 is specifically required for activation of endogenous HIF1 or HIF2 target genes. In this study, using reporter gene assays and chromatin immuno-precipitation, we find that STAT3 or USF2 exhibits specific binding to the promoters of HIF1 or HIF2 target genes respectively even when over-expressed. Functionally, HIF1α interacts with STAT3 to activate HIF1 target gene promoters in a HIF1α HLH/PAS and N-TAD dependent manner while HIF2α interacts with USF2 to activate HIF2 target gene promoters in a HIF2α N-TAD dependent manner. Physically, HIF1α HLH and PAS domains are required for its interaction with STAT3 while both N- and C-TADs of HIF2α are involved in physical interaction with USF2. Importantly, addition of functional USF2 binding sites into a HIF1 target gene promoter increases the basal activity of the promoter as well as its response to HIF2+USF2 activation while replacing HIF binding site with HBS from a HIF2 target gene does not change the specificity of the reporter gene. Importantly, RNA Pol II on HIF1 or HIF2 target genes is primarily associated with HIF1α or HIF2α in a STAT3 or USF2 dependent manner. Thus, we demonstrate here for the first time that HIF target gene specificity is achieved by HIF transcription partners that are required for HIF target gene activation, exhibit specific binding to the promoters of HIF1 or HIF2 target genes and selectively interact with HIF1α or HIF2α protein. Solid tumors are often hypoxic due to chaotic vascularization of the tumors and increased oxygen consumption of proliferating tumor cells and infiltrating inflammatory cells. Low oxygen concentration stabilizes the alpha subunits of hypoxia inducible factors (HIF1α or HIF2α). HIF1α and HIF2α translocate to nuclei where they associate with a constitutively expressed beta subunit called ARNT (Aryl Hydrocarbon Receptor Nuclear Translocator) or HIF1ß –6. Thus,The HIF1α and HIF2α subunits are considerably similar in the arrangement of their protein domains. The N-terminal half of HIF1α or HIF2α contains a basic DNA-binding domain and the ARNT interacting HLH/PAS domain while the C-terminal half of HIF1α or HIF2α contains an N-terminal transactivation domain (N-TAD), an inhibitory domain (IH), followed by a C-terminal transactivation domain (C-TAD) –11. MostPAI1 and EPO [PGK1 and CA9, albeit weakly [PGK1 [Despite the similarities between HIF1α and HIF2α in protein domain structure, primary protein sequence, dimerization partner and regulation of protein stability by oxygen concentration, HIF1 and HIF2 activate transcription of different sets of hypoxia responsive genes both in cultured cells or in animals where both HIF1α and HIF2α are expressed –21. Inte and EPO ,13,22. At weakly ,22. Furtly [PGK1 ,13. Addily [PGK1 ,22. Morely [PGK1 ,22.Activation of hypoxia responsive genes, like transcription of other eukaryotic genes requires multiple transcription factors which recruit chromatin remodeling complexes, histone modifying enzymes and basal transcriptional machinery to form stable “enhanceosome” complexes . The imp2 for 16 hr (or otherwise noted). RCC4 or Hep3B cells stably knockdown of STAT3 or USF2 were described previously [HEK293T, RCC4 and RCC4T (ATCC) cells were grown in high-glucose DMEM (Hyclone) with 10% FBS. Hep3B cells (ATCC) were cultured in MEM/EBSS (Hyclone) containing 10% FBS. For hypoxic treatment, 25 mM HEPES was added to growth media and cells were incubated at 21% or 1.2% Oeviously ,29.tag at C-terminus) was described previously [PGK1/Luc and PAI1/Luc reporters have been described ,29. The eviously . The USFeviously ,15.A. Reporter assay. All promoter reporter assays were conducted using Fugene 6 Transfection Reagent (Roche) to transfect DNA into HEK293T cells. Typically, ~50% confluent HEK293T cells in one well of the 6-well plates were transfected with 200 ng reporter DNA and 200 ng β-galactosidase. In addition, 200 ng HIFα (or HIF1α/HIF2α hybrid plasmid), USF2, or STAT3C expression vector, or 200 ng each of HIFα+USF or STAT3C were co-transfected to activate the reporter genes. 36 hours after transfection, cells were collected into 400 µl 1x Reporter Lysis Buffer (Promega) and assayed for β-gal activity and luciferase activity using a luminometer. Promoter activation by HIFα, USF, or STAT3 or combination of HIFα/USF2 or STAT3 was corrected for β-gal transfection efficiency and presented as fold of induction relative to promoter activities from an empty control vector. Results were the average of at least three experiments. B. Transfection of Hep3B to assess endogenous target gene activation. 60% confluent Hep3B cells in 6 cm dishes were transfected with 3 µg of HIFαTM or USF2, or STAT3C DNA or 1.5 µg each of HIFαTM+USF2 (or STAT3C) using Lipofectamine and Lipofectamine Plus Reagent (Invitrogen). RNA was collected from cells 48 hrs post-transfection to analyze the HIF target gene expression. Results were the average of at least three experiments.RNA was isolated from cells using the Qiagen RNeasy-Plus kit utilizing DNase to digest possible contaminated genomic DNA. RNA was reverse-transcribed using the ISCRIPT Advanced Reverse Transcription Kit (BioRad). Levels of mRNA were quantified by SYBR Green qPCR using the CFX384 Real-Time System (BioRad). All primer sets designed to detect target gene mRNA or used in ChIP were validated for their product specificity and amplification efficiency using melt curve analysis, qPCR product sequencing, and standard dilution analysis. Amplification efficiencies of primer sets were between 90 and 110%. qPCR results for mRNA were normalized using both 18S rRNA and beta-actin mRNA. qPCR for ChIP DNA was performed using primers located near validated HRE positions of genes or in intron4 of the PAI1 gene as a negative control. Results were the average of a minimum of three independent experiments performed in triplicate. Primer sequences for mRNA and DNA ChIP can be found in For STAT3 and USF2 interaction with HIFα protein in over-expression setting, HEK293T cells were transfected with HA-tagged constitutively active full-length (FL) STAT3C or HA-tagged wild type USF2 alone, or STAT3C-HA (or USF2-HA) with Flagged constitutively active full-length or deletion mutants of HIF1αTM or HIF2αTM. Lysates from transfected 293T cells were immunoprecipitated with anti-Flag M2 beads (Sigma) to pull-down Flag-tagged HIF1α or HIF2α protein, in which HA-tagged STAT3 or USF2 was detected. For endogenous STAT3 and USF2 interaction with HIFα, STAT3 (or USF2) protein was precipitated by anti-STAT3 (or anti-USF2) antibodies and protein A/protein G beads. The co-precipitated HIF1α or HIF2α protein was detected using anti-HIFα antibodies.CA9, PGK1, PAI1, EPO or VEGF promoter around the reported HREs or in intron 4 of PAI1 for negative control. ChIP/ReChIP: ChIP was performed as above, binding complexes from the first IP were eluted from the sepharose beads using re-ChIP buffer. The eluted protein/DNA complexes were diluted in RIPA buffer and re-subjected to ChIP using a different antibody [ChIP assays were performed as described . The genantibody .Typically whole cell lysates were used for western blot analysis. Protein concentration was determined by BCA protein assay kit  and the same amount of protein was loaded in western blot. Western blot analysis was performed using standard protocols with the following primary antibodies: anti-HIF1α , anti-HIF2α , anti-STAT3  , anti-USF2 , anti-Flag , anti-HA  and anti-beta actin .Two-tail t-test were performed for this paper with “*” indicating p<0.05 and “**” indicating p<0.01. All the controls for the t-tests were indicated in the figures.CA9 and PGK1) and two HIF2 target genes (PAI1 and EPO) for potential binding sites of STAT3 {TT(N) 4-6AA} [CANNTG) [CA9 promoter, a HIF1 target gene, and the EPO promoter, a HIF2 target gene. However, the PAI1 promoter, a HIF2 target gene, contained more USF2 binding sites than the promoter of the HIF1 target gene PGK1 , indicating STAT3 was not able to strongly activate its target gene promoters alone under this setting. 293T cells exhibited active endogenous STAT3 (data not shown), co-transfected STAT3C also only weakly activated these STAT3 target promoters when 293T cells were treated with the STAT3 inhibitor S3I-201 which was expected to inhibit endogenous, but not STAT3C activity (data not shown). These results indicated that endogenous active STAT3 activity is not responsible for the weak activity of transfected STAT3C in regulating these reporters in 293T cells. Importantly, USF2 strongly activated HIF2 target gene reporters    although there is a relatively low amount of active endogenous STAT3 in Hep3B cells [EPO, PAI1, OCT4 and PLAC8  from qPCR  from the PAI1 promoter into the CA9/Luc reporter near the -13 HBS . HoweverCA9 and PAI1 and the role of USF2 binding sites for HIF2’s ability to activate a target gene, we deleted the -1096/-506 region from CA9/Luc and made a -506/+25 CA9/Luc reporter that contained only two potential STAT3 binding sites  on the HIF target promoters, which may initiate transcription independent of HIF transcription partners (e.g STAT3 and USF2) that are normally required in a physiological setting.We then confirmed a functional interaction of HIF2α with USF2 on HIF2 target genes, and STAT3 with HIF1 on HIF1 target genes in experimental conditions where HIF, STAT3 and USF2 are over-expressed  and 2. HThe specific functional interaction observed in our over-expression system established a foundation for us to determine which protein domains of HIF1α and HIF2α are involved in their functional interaction with STAT3 and USF2. We demonstrate here for the first time that the N-TADs of HIF1α and HIF2α are required for functional cooperation with their respective co-transcriptional activator proteins in the activation of HIF1 or HIF2 target genes, supporting the previously reported results that the N-TADs of HIFα are important in determining HIF target gene specificity ,22. In cCA9, is only associated with HIF1 protein [PAI1) in reporter gene assays. We show that replacement of the CA9 HBS by the PAI1 HBS does not change the response of this reporter to HIF or USF2 activation  Schematic presentation of the CA9 promoters of -506/+25 and -171/+25 with potential STAT3, USF2 and HIF binding sites indicated. B) Fold of induction of CA9/Luc reporters activated by the indicated plasmids. CA9 -171/+25 was not activated by STAT3C and not cooperatively activated by HIF1αTM+STAT3C.(TIFF)Click here for additional data file.Table S1The primers used in q-PCR to detect mRNA or genomic DNA in ChIP.All these primers were tested for specificity and amplification efficiencies.(TIFF)Click here for additional data file.