Previous genome-wide analysis has shown that only a small percentage of CREB target genes are induced in response to fasting-associated signaling pathways. The precise molecular mechanisms by which CREB specifically targets these genes in response to alternating hormonal cues remain to be elucidatedWe performed chromatin immunoprecipitation coupled to high-throughput sequencing of CREB in livers from both fasted and re-fed mice. In order to quantitatively compare the extent of CREB-DNA interactions genome-wide between these two physiological conditions we developed a novel, robust analysis method, termed the ‘single sample independence’ (SSI) test that greatly reduced the number of false-positive peaks. We found that CREB remains constitutively bound to its target genes in the liver regardless of the metabolic state. Integration of the CREB cistrome with expression microarrays of fasted and re-fed mouse livers and ChIP-seq data for additional transcription factors revealed that the gene expression switches between the two metabolic states are associated with co-localization of additional transcription factors at CREB sites.Our results support a model in which CREB is constitutively bound to thousands of target genes, and combinatorial interactions between DNA-binding factors are necessary to achieve the specific transcriptional response of the liver to fasting. Furthermore, our genome-wide analysis identifies thousands of novel CREB target genes in liver, and suggests a previously unknown role for CREB in regulating ER stress genes in response to nutrient influx. Increin vivo. In vitrequences , providiequences . HoweverIn the liver, CREB plays a central role in the maintenance of glucose homeostasis, and dysregulation of the CREB-dependent gluconeogenic gene program is a contributing factor in a number of metabolic diseases including type 2 diabetes -12. A drTo address the question of whether CREB DNA binding dynamics play a role in fasting-induced gene expression, we performed chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-seq) and gene expression analysis by microarray on mouse livers in both fasted (high glucagon/insulin ratio) and re-fed conditions (low glucagon/insulin ratio). Controlled fasting and re-feeding has been shown to be a robust model of cAMP-dependent CREB activity in the mammalian liver ,16, and in vitro[In vivo studies have observed both dynamic [in vivo.Two models have been proposed as to how CREB contributes to gene activation in response to cAMP stimuli. Early studies found CRE “half-sites”, composed of only five of the eight nucleotides of the consensus CRE, were bound more tightly by CREB phosphorylated on S133 than by unphosphorylated CREB in vitro, suggest dynamic  and cons dynamic ,18, but  dynamic ,14. We tG6pc[Pck1[Ppargc1a[In order to quantitatively test genome-wide binding of CREB in both the fasted (cAMP/PKA-active) and re-fed (cAMP/PKA-inactive) states, we performed a controlled feeding experiment Figure A in whicG6pc, Pck1[20G6pc[Pck1, and Ppa[Ppargc1a in the l[Ppargc1a. Liver cThe large number of biological replicates included in our ChIP-seq study allowed us to apply a novel peak-calling and filtering strategy that removes non-reproducible peaks, while maintaining detection sensitivity across a wide range of enrichment strengths. Under our strategy, termed the “Single-Sample Independence (SSI) test”, sequence reads from all five fasted or re-fed replicates were first pooled together and used in peak-calling to identify all candidate CREB binding events. This was followed by a filtering step in which each peak was retained only if a similar peak was called after excluding any individual replicate from the pool of five replicates  were not reproducible, while peaks above this cutoff had a high rate of reproducibility , Hspa1a, and Creld2, in the fasted state relative to the re-fed state, in agreement with previous findings that nutrient influx during re-feeding induces mild ER stress [Given that our CREB ChIP-seq data indicated very few significant changes in target occupancy in response to the fasting-induced cAMP/PKA signal, we next used expression microarrays to identify which CREB targets are induced during fasting. We directly compared gene expression patterns between mouse livers in the fasted and re-fed conditions, and observed significant changes in 942 genes, including the aforementioned cAMP-inducible targets R stress ,34.We next compared our expression microarray results to the high-confidence CREB binding sites determined by our ChIP-seq analysis. We found that, in general, both genes that are induced or repressed in the fasted state are enriched for nearby CREB binding Figure A,B. GiveTo investigate the mechanism of specificity of the cAMP-response, we tested for the enrichment of various genomic features within the three subsets of CREB sites associated with fasting-induced, repressed, or non-responsive genes defined above. We found only minor differences in the occurrence of CRE motifs and intronic versus promoter positioning of sites Figure A,B. ThusPrevious results on a small set of known targets had suggested that only promoters containing a TATA-box are inducible by a CRE site . We clasBased on the results above, we hypothesized that additional sequence-specific transcription factors may contribute to the specificity of the fasting response at a subset of CREB sites. Previous work, focused on several well-studied promoters, had shown synergistic effects of CRE sequences with other transcription factor binding sites ,20,36,37The binding strength of CREB itself showed no association with the differential expression of the corresponding target gene in the hepatic feeding to fasting switch Figure . The sitde novo motif analysis of CREB sites, directly comparing those sites associated with fasting-induced and -repressed genes to the non-responsive sites, and also computed the group-wise enrichment of the additional de novo motifs identified from the entire CREB cistrome  on our microarray. Similarly, there was no significant difference in binding for our ChIP-qPCR experiments for cAMP/fasting-inducible CREB targets , a repressive protein resulting from an alternate transcript of the CREB-related gene echanism , and ourechanism , as suggs Figure G.Another possibility is that genes with higher expression in re-fed livers are “feeding-induced”, rather than “fasting-repressed”. The increased expression of ER stress genes in re-fed livers supports this notion, as nutrient influx has been shown to increase ER stress signals in liver and other tissues ,34. PrevOverall, our results demonstrate that CREB binding in the mammalian liver is constitutive with respect to metabolic state and widespread throughout the genome. The mechanisms contributing to fasting-inducible expression changes at CREB target genes required for glucose homeostasis are more complex than previously appreciated. The majority of CREB target genes are not induced by fasting and previously proposed mechanisms for specifying this response — e.g., site-specific dynamic occupancy  and inteAll mice used in this study were 8–12 week-old male C57BL/6 J mice. All experiments were conducted under a protocol approved by the IACUC of the University of Pennsylvania.Blood was sampled from the tail vein of fasted or re-fed mice, and glucose levels were measured with a OneTouch Ultra Glucometer (Lifescan Inc.).http://www.med.upenn.edu/kaestnerlab/reagents.shtml.Total RNA was extracted from livers collected from fasted and re-fed mice using the RNeasy Kit (Qiagen), then assayed for quantity and quality with the Agilent 2100 Bioanalyzer (Agilent Technologies). RNA was reverse transcribed using oligo (dT) and Superscript II reverse transcriptase (Invitrogen). The resulting cDNA samples were used as template for qPCR experiments performed with SYBR GreenER qPCR Supermix (Invitrogen) and the SYBR Green program on the Mx3000 Multiplex Quantitative PCR System (Stratagene). Reactions were performed in triplicate and normalized relative to the ROX reference dye. Median cycle threshold values were used for analyses. In each group, one sample had consistently higher threshold values for all reactions indicating poor RNA isolation quality, and was therefore excluded from analysis. Expression levels were normalized to those of Hypoxanthine guanine phosphoribosyl transferase (HPRT) as the internal control. Primer information is available at Western blot analyses were performed as previously described  using an200 ng of total RNA from individual each fasted and re-fed mouse livers (n = 4 per group) were amplified and labeled with Cy3 or Cy5 using Low Input Quick Amp Labeling Kit, two-color  with a dye swap experimental design. Labeled samples were purified using the RNeasy Kit (Qiagen) and hybridized overnight to the Agilent 4X44 Whole Mouse Genome Array. After hybridization the arrays were washed and scanned with the Agilent DNA Microarray Scanner G2565B. Median intensities of each array element were captured with Agilent Feature Extraction v10.5.1.1 and normalized by the print tip loess method in LIMMA  at 10% FLiver chromatin from fasted and re-fed mice was prepared as previously described . ImmunopReads for each individual ChIP-seq library were mapped to the UCSC mm8 reference genome using Illumina’s Eland pipeline. Redundant reads were discarded within each replicate. For each condition , non-redundant reads from all five biological replicates were pooled into a single read set, and initial peak-calling was performed with HOMER v3.0 (5% FDR) , using aTo determine the extent of differential CREB binding between the fasted and re-fed conditions genome-wide, we first merged the fasted and re-fed SSI HOMER peak calls with average height > 0.35 RPM to a common set of 7,547 high-confidence binding regions. At each region, the peak height was computed individually for each replicate by extending reads to the average fragment length of 108 bp and computing the maximum value of the resulting stack height profile within each binding region. Peak heights were normalized to RPM for each replicate, and the normalized values were averaged to compute a single value for each condition. The raw number of tags from each replicate overlapping each high-confidence peak was tabulated and used for statistical analysis by EdgeR  with defDe novo motif analysis was performed using HOMER v3.0 [De novo motifs were filtered to significantly enriched motifs matching ≥ 10% of target sequences. Positional motif enrichment plots were computed using the HOMER histogram function with 10 bp resolution. We used the HOMER motif-scanning function with the known TATA motif from JASPAR [Initial identification of consensus CRE sequences in each binding region was performed by scanning the 100 bp sequence around each site for the octamer TGACGTCA with at most one mismatch, and the matching sequences were classified as “Full CRE” sites. The remaining regions were scanned for a perfect match to either pentamer half-site CRE (TGACG or CGTCA), and matching sequences were classified as “Half CRE” sites. The remaining regions without a match to either CRE sequence were classified as “Non-CRE” sites. MER v3.0  on the 1MER v3.0  to maintm JASPAR ,58 to clm JASPAR ,59,60.Binding regions were classified by their association with known gene architecture by comparing the exact center position of each region to the mm8 RefGene track downloaded from UCSC Genome Browser . Region ATF6: Activating transcription factor 6; cAMP: Cyclic adenosine monophosphate; CEBPB: CCAAT/enhancer-binding protein beta; ChIP: Chromatin immunoprecipitation; ChIP-chip: ChIP coupled to genomic microarrays; ChIP-seq: ChIP coupled to high-throughput sequencing; CRE: cAMP response element; CREB: cAMP response element binding; CREBBP: CREB binding protein; CRTC2: CREB-regulated transcription co-activator 2; EP300: E1A binding protein p300; ER: Endoplasmic reticulum; FOXA2: Forkhead box protein A2; GR: Glucocorticoid receptor; HPRT: Hypoxanthine guanine phosphoribosyl transferase; ICER: Inducible cAMP early repressor; PPARA: Peroxisome proliferator activated receptor alpha; PKA: Protein kinase A; RPM: Reads Per Million; S133: Serine 133; SACO: Serial analysis of chromatin occupancy; SSI: Single sample independence; TSS: Transcription start siteThe authors declare no competing interests.LJE, JL, and KHK conceived and planned the overall project. LJE performed all computational analyses. JL designed and carried out the CREB ChIP-seq experiment. LJE, SL, and DB designed and carried out CREB binding site validation and liver microarray experiments. DJS and MAL designed and carried out CEBPB and GR ChIP-seq experiments. All authors read and approved the final manuscript.Supplementary tables and figures.Click here for fileSummary tables of genes bound by CREB and regulated in fasting/re-feeding microarray experiment.Click here for fileSummary table of all high-confidence CREB peaks, including peak height in each replicate, nearest TSS, and enrichment levels of additional transcription factors.Click here for file


Transcription factors CREB, C/EBPβ and Jun regulate genes involved in keratinocyte proliferation and differentiation. We questioned if specific combinations of CREB, C/EBPβ and c-Jun bound to promoters correlate with RNA polymerase II binding, mRNA transcript levels and methylation of promoters in proliferating and differentiating keratinocytes.Induction of mRNA and RNA polymerase II by differentiation is highest when promoters are bound by C/EBP β alone, C/EBPβ together with c-Jun, or by CREB, C/EBPβ and c-Jun, although in this case CREB binds with low affinity. In contrast, RNA polymerase II binding and mRNA levels change the least upon differentiation when promoters are bound by CREB either alone or in combination with C/EBPβ or c-Jun. Notably, promoters bound by CREB have relatively high levels of RNA polymerase II binding irrespective of differentiation. Inhibition of C/EBPβ or c-Jun preferentially represses mRNA when gene promoters are bound by corresponding transcription factors and not CREB. Methylated promoters have relatively low CREB binding and, accordingly, those which are bound by C/EBPβ are induced by differentiation irrespective of CREB. Composite “Half and Half” consensus motifs and co localizing consensus DNA binding motifs are overrepresented in promoters bound by the combination of corresponding transcription factors.Correlational and functional data describes combinatorial mechanisms regulating the activation of promoters. Colocalization of C/EBPβ and c-Jun on promoters without strong CREB binding determines high probability of activation upon keratinocyte differentiation. During differentiation, keratinocytes exit the cell cycle and start producing differentiation-specific proteins used in the formation of the outer skin layer. Both the c-Jun/AP-1 family of transcription factors The mechanism that allows for the selective regulation of genes involved in diverse cell functions such as proliferation and differentiation using the same transcription factors is still unknown. Differential expression of AP-1 family members c-Jun/JunB, Fra2/cFos and C/EBPs family members C/EBPα and C/EBPβ contribute to the modulation of gene activities upon differentiation CREB is another transcription factor important for keratinocyte proliferation Gene activation and repression mediated by the binding of a transcription factor can also be driven by cooperative interactions with other sequence specific transcription factors Our previous work has demonstrated that DNA methylation is important for activation of some tissue specific genes involved in keratinocyte differentiation We hypothesized that CREB, c-Jun and C/EBPβ are functioning differently when they bind to promoters in different combinations. Because CREB is important for cell survival, we hypothesized that C/EBPβ and c-Jun regulate genes involved in cell survival and proliferation if they co-localize with CREB and regulate genes involved in differentiation when they do not. We test this hypothesis by analyzing how genome-wide promoter binding of transcription factors CREB, C/EBPβ and c-Jun in different combinations correlate with either the activation or repression of promoters and their target genes upon keratinocyte differentiation.In order to determine factors correlating with activation of promoters as measured by RNA polymerase II (RNAP) binding, we determined localization of three transcription factors – CREB, C/EBPβ and c-Jun, as well as RNAP, in proliferating and differentiated keratinocytes using chromatin immunoprecipitation followed by microarray hybridization. Despite close to 100% immunoprecipitation efficiency, c-Jun had lower DNA binding levels than the other proteins .Upon keratinocyte differentiation, RNAP binding increased at 797 promoters and decreased at 841 promoters . Out of We next analyzed if promoters bound by different combinations of transcription factors are preferentially repressed or induced upon differentiation. CREB, C/EBPβ and cJun bind distinct set of promoters in differentiated keratinocytes . Among tWe found the same absolute values of RNAP induction between groups ; howeverTranscription factors are known to recruit histone acetyltransferases that change chromatin accessibility and transcriptional activation. Therefore, we next investigated whether H3K9 acetylation preferentially altered upon differentiation for promoters bound by specific combinations of transcription factors. As expected, H3K9 acetylation correlates with RNAP binding in differentiated  and undiC/EBPβ binding to promoters is induced upon keratinocyte differentiation and RNAP binding is preferentially induced to promoters bound by C/EBPβ and cJun. In order to determine genes that are dependent upon C/EBPβ or cJun function we expressed dominant negatives A-C/EBP and A-Fos using a tetracycline driven expression system Because CREB is rarely bound to promoters induced by differentiation, we hypothesized that CREB binding affinity might be lower in promoters bound by CREB C/EBPβ and cJun and induced by differentiation. Comparison of transcription factor binding distributions in all promoters and promoters bound by CREB, C/EBPβ and cJun in differentiated keratinocytes revealed lower levels of CREB binding in promoters bound by all three of these transcription factors and induced by differentiation . We arbiColocalization of C/EBPβ and cJun with CREB makes promoters refractory to induction with calcium and to repression by dominant negatives. CREB is known to bind nearly the same set of promoters in different cells Indeed, scatter plots of transcription factors and RNAP DNA binding  showed tIt was shown that DNA methylation is important for activation of some tissue specific genes involved in keratinocytes differentiation Similar to what is observed for all promoters, unmethylated promoters containing C/EBPβ and c-Jun are mostly induced by differentiation while those that are also bound by CREB are not . The fraCCCACCATGCTTTGGTCA containing half C/EBP (TTTG) and half c-Jun (GTCA) binding site. And, for promoters bound by all three proteins we found c-Jun and CREB binding sites.The presence of specific DNA sequences which bind transcription factors is the major mechanism of transcription factor recruitment to the promoters. We hypothesized that specific combinations of DNA binding motifs recruit corresponding combinations of CREB, c-Jun and C/EBPβ. To identify these combinations we calculated motifs overrepresented in sets of promoters bound by transcription factors alone and in different combinations. First, we used all promoters as a background and report the top two enriched motifs in GACAAGTTAGGTCA) was the same when promoters bound by C/EBP or c-Jun were used as a background. The same motif was identified for c-Jun and C/EBPβ bound promoters relatively to c-Jun. Motifs enriched in CREB –c-Jun bound promoters relative to c-Jun or CREB represent known binding motifs for corresponding transcription factors. The same calculations performed for combination of three transcription factors identified consensus motifs for c-Jun and CREB and TCCCANNNCCTC for C/EBPβ.CREB, c-Jun and C/EBPβ can bind promoters via separate binding sites; compete for the same DNA binding motifs or bind DNA as heterodimers. In improve identification of motifs that can recruit two transcription factors, we used as a background promoters bound by one transcription factor  and calculated motifs enriched in promoters bound by combination of two transcription factors. This analysis identified composite motif containing half C/EBP and half CRE site and C/EBP consensus site for promoters bound by C/EBPβ and CREB relative to CREB. Inversely, when promoters bound by C/EBPβ were used as a background for the same test site we identified CREB binding site and CTACANNTCCC sequence. Likewise, the same calculation performed for the promoters bound by c-Jun and C/EBPβ identified TRE site relative to the C/EBPβ set. Interestingly second identified motif  bound to promoters together with C/EBPβ and c-Jun will determine if specific gene is ultimately induced, repressed or do not change upon differentiation. Many other transcription factor are involved in keratinocytes differentiation Notably, analysis of combinatorial recruitment of CREB, c Jun and C/EBPα generated similar results .Presence of specific DNA sequences in the promoter determines recruitment of corresponding transcription factors for regulation of gene expression. CREB, c-Jun and C/EBPβ can compete for the same binding sites or bind simultaneously at different sequences. c-Jun, C/EBPβ and CREB bind to TGACTCA, TTGCGCAA and TGACGTCA consensus sequences respectively. CREB and c-Jun can bind the same TGACGTCA CCCACCATGCTTTTGGTCA is identified in promoters bound by C/EBPβ and c-Jun. Similar composite C/EBPβ - c-Jun motif GACAAGTT(T/A)GGTCA is enriched in promoters bound by C/EBPβ and c-Jun relatively either to c-Jun or C/EBPβ bound promoters. This suggests that it is the C/EBPβ/c-Jun protein complex that binds to this motif, similar to what is described in papers To understand how sequences of promoters determine preferential recruitment of CREB, c-Jun and C/EBPβ in different combinations, we identified DNA motifs overrepresented in promoters bound by one, two or all three of these transcription factors relative to all promoters or relative to promoters bound by one or two transcription factors. As expected, we found that consensus binding sites are overrepresented in promoters bound by single transcription factor or in groups where corresponding transcription factors co-localize with other transcription factors. As expected, when promoters bound by a particular transcription factor were used as a background, subsets of promoters bound both by this and another transcription factor where enriched in the other transcription factor’s consensus sequence. The composite motif between CREB and C/EBPβ binding motif identified in our analysis was similar to the one reported in This paper uncovered combinatorial rules of transcription factor recruitment that determine activation of gene expression upon differentiation.All mouse experiments were approved by the Animal Ethics Committee at the National Institutes of Health, under the approved protocol number LM-076. Newborn mice were handled and humanely sacrificed by carboxyl dioxide followed by secondary physical method in accordance with the National Institutes of Health Institutional Guidelines .2). After 24 hours, cultures were washed twice with PBS and switched to medium with 0.05 mM calcium . At the same time doxycyclin added to the media of A-C/EBP or A-Fos cultures was removed to induce expression of A-C/EBP or A-Fos. 24 hours later, cultures were switched to the same medium with 0.4 mM calcium  for two days to induce differentiation or maintained in parallel as undifferentiated keratinocytes in the low calcium medium. For demethylation experiments, 5-azacytidine (5-aza) was added 6 hr after seeding to the culture medium to a final concentration of 1 µM. Cell culture medium was replaced every day.Keratinocytes were cultured as describe in http://farnham.genomecenter.ucdavis.edu/protocol.html). Primary cultured cells were chemically cross-linked by adding 0.6% formaldehyde (Sigma) directly to the medium. Cells were allowed to cross-link for 10 minutes with gentle swirling at room temperature. The cross-linking reaction was stopped by adding 125 mM glycine and dishes were swirled for 5 minutes at room temperature. Cells were washed twice with ice-cold PBS and harvested in ice-cold PBS containing protease  and phosphatase inhibitors . Cells were pelleted by centrifugation at 4°C for 5 minutes at 300 g. Cells where incubates in cell lysis buffer (5 mM PIPES pH 8.0 85 mM KCL 0.5% NP40 1 mM NF 1 mM NaVa Roche protease inhibitors cocktail) and resuspended in nuclear lysis buffer  and sonicated to average size of 500 bp. After centrifugation supernatant was diluted 3 times by dilution buffer . 300 l of sonicated chromatin preparation with protein concentration 1–2 µg/µl  was incubated overnight with antibodies. ChIP was performed using antibodies against RNA pol II (RNAP)  that recognizes the unphosphorylated form of RNAP, CREB (2 µg/ml of the each antibody from Santa Cruz (sc-186) and Upstate (06–863)), H3K9 acetyl from Upstate 06–942, c-Jun from Santa Cruz  and C/EBPβ from Santa Cruz . A fraction of lysate was left untreated to serve as an input control. Immunocomplexes were captured using protein G agarose beads (Invitrogen) blocked with 1 g/l yeast tRNA and BSA (Sigma) and washed twice with the buffer containing 2 mM EDTA, 100 mM Tris-Cl pH 8.0 and 0.18% Sarkosyl, and four times with the Chip wash buffer  and two times with TE. After incubating with RNAse A and Proteinase K, DNA was eluted using QIAquick PCR Purification Kit. From 1–2×106 primary keratinocytes for RNAP, CREB, and C/EBPβ, 0.5–2 ng of DNA were typically immunoprecipitated. DNA quantification was performed using Picogreen DNA quantification kit . PCR was performed using RedMix Tag polymerase (Sigma).ChIP experiments were performed following the protocol from Farnham’s group (http://research.stowers-institute.org/gertonlab/protocols/RandomPCRamplification.pdf. Only one round of amplification was used. After amplification 5–6 µg of ChIP or control DNA was purified using PCR Purification Kit (Qiagen), isopropanol precipitated, and vacuum dried for 5 minutes. DNA was dissolved in 3 µl water, mixed with Component A and Hybridization buffer (Nimblegen) according to manufacturer’s instructions. Amplified ChIP DNA was hybridized overnight to Nimblegen MM5 min Mouse promoter microarrays containing 400,000 oligos interrogating 26,264 promoters in MAUI hybridization station (BioMicro Systems) and washed according to manufacturer instruction. Arrays were dried by centrifugation and scanned using Axon 4000 B scanner. Images were processed with NimbleScan (Nimblegen) using default settings.Primers conjugated with Cy3 or Cy5  were used for the amplification of the input or immunoprecipitated DNA using round A/B/C random amplification protocol: Nimblegen MM5 min promoter arrays contain probes for 26,264 promoter regions spanning approximately −1000 bp…+500 bp relative to the transcription start site. We limited our data analysis to 20,328 promoters. We excluded promoters that are located on the X or Y chromosomes, 3,940 promoters were further eliminated that either had unsequenced DNA segments larger than 150 bp or which contained large regions of DNA sequence (≥150 bp) which were identical to regions in 10 or more of other promoters. Binding of given transcription factor was defined as an average enrichment of ChIP DNA over input DNA for the whole −1000…+500 promoter region. Binding from individual replicates were averaged. Promoters were defined as bound by several transcription factors if binding of these factors were higher than specific thresholds. Values of thresholds for calculation of transcription factor DNA binding in Ln2: CREB - 0.4, C/EBPβ-0.4, C/EBPα-0.36 c-Jun-0.36, RNAP-0.4. RNAP induction or repression upon differentiation: RNAP Diff>0.4 and RNAP Diff- RNAP Undiff>0.3. H3K9 acetylation induction or repression upon differentiation: H3K9Ac Diff>0.4 and H3K9Ac Diff- H3K9Ac Undiff>0.36.MeDIP experiments were described in Rishi mRNA expression profiling with Affymetrix microarrays (Mouse genome 430 2.0 array) was performed by NCI microarray core facility (Frederick). We compared the mRNA expression levels of genes determined using mRNA expression arrays to the binding of proteins to the promoters regions of those genes, determined by ChIP-chip data collected using Nimblegen promoter chips. Using GenBank Accessions, Gene Symbols, UniGene Clusters and UniGene IDs the mRNA expression data was mapped to the same promoter set as the ChIP-chip data. Genes in the expression data which shared a common identifier with promoters in the ChIP-chip data were assigned to their matching promoters in the ChIP-chip set. When multiple data points from the mRNA expression data were all mapped to the same promoter in the ChIP-chip data, the average of these points was assigned to that promoter. 17,930 of the 20,328 promoters used in our ChIP-chip analysis were successfully assigned mRNA expression values. Threshold for mRNA changes upon differentiation – more than 1.4 or 0.5 in Ln2 scale.http://lgsun.grc.nia.nih.gov/CisFinder/DNA Motif analysis was performed using CisFinder Excel “Chitest” function was used to calculate significance of observed values from expected ones based on the total number of events. Excel two tailed “Ttest” function was used to determine whether two samples are likely to have come from the same two underlying populations that have the same mean.GSE48383.Figure S1Promoters induced by differentiation are overrepresented in the group of C/EBPβ bound and promoters with increase of C/EBPβ binding upon differentiation. A. Scatterplotts of transcription factors and RNAP before and after differentiation show that binding do not change for majority of promoters with the highest scatter for RNAP and overall increase of C/EBPβ binding. B. Scatterplotts of changes in RNAP v.s. transcription factors upon differentiation show that promoters induced by differentiation are overrepresented in group of promoters with induced C/EBPβ binding. C. Scatterplotts of changes in RNAP upon differentiation v.s. binding of transcription factors in differentiated keratinocytes show that promoters induced by differentiation are overrepresented in group of promoters bound by C/EBPβ. D. Efficiency of c-Jun immunoprecipitation was about 100%: 5% of input cell lyzat and 20% of c-Jun Chip material was resolved by SDS-PAGE transferred to membrane and probed with c-Jun antibody.(TIF)Click here for additional data file.Figure S2Colocalization of c-Jun and C/EBPβ with CREB determine levels of mRNA induction upon differentiation. A. Inductionof RNAP binding  in differentiated compared to undifferentiated keratinocytes for promoters where RNAP is induced by differentiation and bound by different combination of transcription factors. B. Increase of mRNA levels  in differentiated compared to undifferentiated keratinocytes for genes whose mRNA is induced by differentiation and promoters are bound by different combination of transcription factors. Numbers represent t-test values. Dotted lines represent thresholds for induction.(TIF)Click here for additional data file.Figure S3H3K9 acetylation is preferentially induced by differentiation when promoters are bound by combination of C/EBPβ and c-Jun. A. Scatterplot of RNAP binding versus H3K9 acetylation in differentiated keratinocytes. B. Changes of RNAP binding upon differentiation correlates with changes in H3K9 acetylation. C. Fraction of promoters bound by different combinations of transcription factors in differentiated keratinocytes where H3K9 acetylation is reduced (white bars) or induced upon differentiation (black bars). * - numbers are different from expected (p<0.05). D. Induction of H3K9 acetylation  for promoters where H3K9 acetylation is induced and bound by different combinations of transcription factors in differentiated keratinocytes. Numbers represent t-test values. Dotted line represents threshold for induction.(TIF)Click here for additional data file.Figure S4Examples of binding patterns of RNAP, CREB, C/EBPβ and c-Jun across promoter regions of selected promoters that are induced or not induced by differentiation. Claudin4 promoter induced by differentiation, not bound by CREB and bound by C/EBPβ and c-Jun, Small proline rich protein 1A promoter induced by differentiation, not bound by CREB  and bound by C/EBPβ and c-Jun, DNAse1-like3 induced by differentiation and bound by C/EBPβ, c-Jun with low CREB binding, Rsp19 - ribosomal protein 19 promoter not induced by differentiation, bound by C/EBPβ and c-Jun with strong CREB binding. Arrows on top are directions of transcription started from transcriptional start site.(TIF)Click here for additional data file.Figure S5Colocalization of C/EBPβ and c-Jun with CREB is associated with high probability of RNAP binding in undifferentiated keratinocytes. RNAP binding percentiles  for promoters bound by different combinations of transcription factors in undifferentiated keratinocytes.(TIF)Click here for additional data file.Figure S6CREB binding is relatively low when promoters are methylated while C/EBPβ biding to methylated or unmethylated promoters is the same. Promoters bound by different combination of transcription factors are shown.(TIF)Click here for additional data file.Figure S7Genes with promoters bound by C/EBPβ and c-Jun are preferentially repressed by 5-azacytozine. Percent of genes which mRNA is repressed (white bars) or induced (black bars) by DNA demethylation agent 5-azacytidine in groups of promoters bound by different combinations of transcription factors in differentiated keratinocytes. * - significant difference p<0.05.(TIF)Click here for additional data file.Figure S8Combinatorial recruitment of CREB, C/EBPα and c-Jun determines activation of promoters in keratinocyte differentiation. A. Scatterplot of C/EBPα binding v.s. C/EBPβ binding show that C/EBOa was detected on a subset of promoters bound by C/EBPβ. B. RNAP binding percentiles  in promoters bound by different combinations of CREB, C/EBPα and c-Jun. C. Fraction of promoters bound by different combination of transcription factors in differentiated keratinocytes where RNAP binding is repressed (white bars) or induced by differentiation (black bars). D. Fraction of genes with mRNA levels induced or repressed by differentiation more than 1.4 times in groups of promoters bound by different combinations of transcription factors. * - values are different from expected (p<0.05). ). E. Fraction of genes repressed by A-C/EBP differentiated keratinocytes in groups of promoters bound by different combinations of transcription factors. F. Fraction of genes repressed by A-Fos in differentiated keratinocytes in groups of promoters bound by different combinations of transcription factors * - numbers are different from expected (p<0.001).(TIF)Click here for additional data file.Table S1Numbers and fractions of promoters bound by different combinations of transcription factors and induced or repressed by differentiation. Reference groups used to calculate fractions in different groups are also presented. Above row 64 is the data for C/EBPβ, CREB and c-Jun and below row 67 is the data for C/EBPα, CREB and c-Jun.(XLS)Click here for additional data file.


S. cerevisiae is of great interest to basic and applied bioenergy research. By expressing three different fungal pathways in two S. cerevisiae hosts respectively, we found that the xylose utilization efficiency by recombinant S. cerevisiae depends not only on the choice of xylose pathway but also on the choice of host, exhibiting an obvious host or context dependence. To investigate molecular mechanisms of this context dependence, we applied RNA-seq analysis in this study for a systematic characterization of the xylose utilization via different pathways in different S. cerevisiae hosts.Xylose-based ethanol production by recombinant Based on the RNA-seq analysis, the transcripts that were regulated during xylose utilization have been identified. Three transcription factors involved in regulation of amino acid metabolism, responses to oxidative stresses, and degradation of aggregated proteins, respectively, were found to participate in xylose metabolism regulation regardless of which pathway was expressed and which host the xylose pathway was expressed in. Nine transcription factors, involved in homeostasis, regulation of amino acid metabolism, and stress responses, were identified as the key modules responsible for the host-specific responses to the same xylose pathway. In addition, the transcriptional regulations of xylose utilization in different yeast hosts were compared to two reference regulation patterns, which indicated that diverse regulation strategies were adopted by different hosts for improved xylose utilization.S. cerevisiae. Both the conserved regulatory modules for xylose metabolism and the key modules responsible for host dependence were identified. As indicated by the functions of the conserved transcription factors involved in xylose metabolism regulation, the xylose utilization in recombinant S. cerevisiae may be affected by both carbohydrate metabolism regulation and stress responses. Based on the comparison of transcriptional regulation patterns, the metabolic optimizations of xylose utilization in different hosts went toward different directions, which may explain the host dependence observed in this study. The knowledge revealed by this study could provide valuable insights towards the improvement of metabolic engineering strategies for cellulosic ethanol production.This study provides the first transcriptomic study of the host dependence of xylose utilization in  S. cerevisiae to utilize xylose for ethanol production is of great interest to the biofuel industry because it can reduce the cost of feedstock for bioethanol production and substantially minimize the emission of greenhouse gases [S. cerevisiae[Engineering se gases ,2. To acerevisiae-5, folloerevisiae,7 and everevisiae.S. cerevisiae hosts, namely CTY and INVSc1, to efficiently utilize xylose for bioethanol production by using the COMPACTER approach [S. cerevisiae depends not only on the pathway but also the host.Previously, we engineered two approach . In brieS. cerevisiae strains to xylose metabolism. Basically, three different xylose pathways  were functionally expressed in two hosts of S. cerevisiae , which generated six recombinant strains in total. Specifically, we aimed to find the answers to two questions about the xylose metabolism in S. cerevisiae: 1) what are the conserved modules that are involved in xylose metabolism regulations; and 2) what are the key modules that lead to the host dependence. By systematically grouping the differentially expressed genes by the transcription factors (TFs) and comparing the profiles of TFs in the CTY and INVSc1 hosts respectively . Two optimized pathways were selected respectively in either CTY  or INVSc1  based on their improved performance compared to the wild-type pathway (WT). In general, in the CTY host, the strain with the optimized pathway  enhanced the xylose uptake rate by nearly three fold  from the INVSc1 host to the CTY host, the resultant CTY-INVp strain has a 25% decrease in the xylose uptake rate and nearly 100% decrease in ethanol production compared to those of INV-INVp. Similarly, a 28% decrease in xylose uptake rate and a 16% decrease in ethanol yield were found in another pathway-switched strain, INV-CTYp, compared to those of CTY-CTYp. In general, despite of the similar genomic background between the two To systematically characterize the transcriptional responses of the CTY and INV hosts to different xylose pathways, the RNA-seq analysis with over 442 million sequence reads in total was finished for 18 samples, which includes six recombinant strains  with three biological replicates respectively. To identify the transcripts that have significantly different expression levels between the control group and the experimental group, the Cuffdiff program was used with the default parameter setting. The advantage of using Cuffdiff’s count-based differential expression analysis is that the error introduced by the isologues of the genes can be well corrected, which provides more accurate and in-depth analysis of the transcriptional behaviors . HoweverIn the CTY host, 17 and 16 transcripts were identified to have different expression levels in CTY-CTYp and CTY-INVp, respectively, as compared to those from CTY-WT Figures . A furthIn the INVSc1 host, only 1 transcript in INV-CTYp and 2 transcripts in INV-INVp were identified to be differentially expressed compared to those of INV-WT  that govern the way of controlling the flow of genetic information from DNA to mRNA [S. cerevisiae, in this study, we only considered the TF-gene regulations supported by published data. For each TF analysis, we generated a TF profile by choosing the top 20 candidates based on the number of genes they regulated. Then, we compared the TF profiles between different xylose utilization conditions in the host of either CTY or INVSc1, from which we selected the common TFs as the key modules in xylose metabolism regulation. A total of 15 TFs were found to be the key regulatory modules in the CTY host while 5 TFs were found in the INVSc1 host. Specifically, three TFs, Gcn4p, Rpn4p, and Yap1p, stood out as the regulatory modules that were always involved in the xylose metabolism regulation regardless of which xylose pathway was used and in which host the xylose pathway was expressed.The exhibition of complex genetic responses of  to mRNA . To uncoS. cerevisiae, one of the key functions of Rpn4p may be degrading the mis-folded heterologous proteins. In S. cerevisiae, the oxidative stress is primarily controlled by Yap1p. Since the fungal xylose pathway expressed in S. cerevisiae was cofactor imbalanced, NADH was produced when xylitol was converted to xylulose. The oxidative stress caused by NADH overproduction may trigger the transcriptional regulation of Yap1p [S. cerevisiae was indicated to involve both carbohydrate metabolism regulation and stress responses. However, in order to decode the more detailed regulatory patterns of the TFs involved in xylose metabolism, tremendous genotype-phenotype correlation experiments needs to be accomplished in future.As indicated by GO analysis, the cellular amino acids process (GO:0006520) was found to be tightly regulated in both the CTY and INVSc1 hosts, which may explain the pivotal role Gcn4p played in xylose metabolism, since it is well known as a transcriptional activator of amino acids biosynthesis . The Rpnof Yap1p -19. AccoS. cerevisiae respectively. Interestingly, the conserved TFs in xylose metabolism, Gcn4p, Rpn4p, and Yap1p, were also found among the key modules responsible for the host dependence, suggesting that the same regulatory modules may play different roles in the transcriptional regulation of carbon metabolism in different hosts of S. cerevisiae.The transcriptional behaviors of host dependence were characterized by comparing the global gene expression levels in the CTY and INVSc1 hosts in response to the same xylose pathway Figure . When thS. cerevisiae may be affected by both carbohydrate metabolism regulation and stress response. To deconvolute such two effects on xylose metabolism regulation, we solicited two transcriptional datasets from the GEO database as the reference datasets for xylose-related carbohydrate metabolism regulation  and stress responses , respectively. The top 250 genes which are differentially expressed in the reference datasets were extracted, followed by the TF analysis to generate the reference TF profiles. In order to make a direct comparison, both the reference TF profiles generated from GEO database and the sample TF profiles generated from this study were normalized, based on which the Euclidean distances were calculated  were selected as the conserved regulative modules for xylose metabolism. To further validate their indispensable role in regulating the xylose utilization regardless of which pathway was expressed and which host the xylose pathway was expressed in, we solicited two additional datasets from the published transcriptional studies. The first dataset included the differentially expressed genes in a recombinant n source . The TF ce issue ,23. HoweS. cerevisiae depends not only on the choice of the heterologous pathway but also the choice of the host. To perform a systematic investigation of the so-called host dependence, we applied RNA-seq analysis in this study to characterize the transcriptional behaviors of six strains, created by expressing three xylose pathways in two hosts. We identified three transcription factors as the conservative modules that regulated the xylose metabolism regardless of which xylose pathway was used and which host the xylose pathway was expressed in. Another nine transcription factors were found as the key regulatory modules playing pivotal roles in the host dependence. Based on the transcription factor analysis, xylose utilization in recombinant S. cerevisiae may involve both carbohydrate metabolism regulation and stress responses. The diverse regulatory strategies and the different directions of pathway optimization in the context of various S. cerevisiae hosts are hypothesized to cause the host-specific responses to xylose utilizations. In sum, the work presented in this study can be viewed as a stepping stone towards a more comprehensive understanding of the regulatory machinery of the cellulosic sugar metabolism in recombinant S. cerevisiae, and provide valuable insights towards improved engineering strategies for cellulosic ethanol production.The xylose utilization in recombinant S. cerevisiae strain INVSc1 (MATa his3Δ1 leu2 trp1-289 ura3-52 MATα his3Δ1 leu2 trp1-289 ura3-52) was purchased from Invitrogen . Still Spirits (Classic) Turbo Distiller’s Yeast (CTY) was purchased from Homebrew Heaven . Three xylose pathways, namely WT (the wild-type pathway without optimization of promoter strengths), CTYp (the xylose pathway with optimization of promoter strengths in the CTY host), and INVp (the xylose pathway with optimization of promoter strengths in the INV host), were constructed previously using the COMPACTER approach [S. cerevisiae strains, seed cultures were grown in YPAD media  at 30°C overnight. The seed cultures were then inoculated  into the YPAX medium with 4% xylose as the carbon source. All of the yeast strains were cultivated at 30°C and 100 rpm for oxygen limited conditions, with initial cell concentration at ~0.08 g DCW/L. Three biological replicates were made when culturing each of the six recombinant strains.The parent approach . The plaSamples were taken at the log phase of the six recombinant strains (~24 h). The cell pellets (~10 mg) were frozen by liquid nitrogen. Total RNA was extracted by FastRNA Spin kit for yeast  according to the manufacturer’s instructions. The RNA quality and quantity were determined using Agilent 2100 Bioanalyzer . The RNA integrity number (RIN) of all RNA samples used for sequencing was more than 9.0. The RNA samples were then sent to The Biotechnology Center at University of Illinois at Urbana-Champaign for library preparation and sequencing.RNA-seq libraries were constructed and sequenced at 7the W. M. Keck Center at the University of Illinois at Urbana-Champaign. Eighteen libraries were constructed using the TruSeq RNA Sample Preparation Kit . Briefly, mRNA was selected from total RNA with oligo dT beads and chemically fragmented. First-strand cDNA was synthesized with random hexamer primers and SuperScript II (Life Technologies). Double stranded DNAs were blunt-ended, 3′-end A-tailed and ligated to indexed adaptors. The adaptor-ligated double-stranded cDNA were amplified by PCR for 10 cycles with the Kapa HiFi polymerase  to reduce the likelihood of multiple identical reads due to preferential amplification. The final libraries were quantitated with Qubit  and the average size was determined on an Agilent bioanalyzer DNA7500 DNA chip  and diluted to 10 nM. The 10 nM dilution was quantitated by qPCR on an ABI 7900 Real-time PCR system (Life Technologies).The libraries were pooled in equimolar concentration and loaded onto 8-lane flowcells for cluster formation and sequenced on an Illumina HiSeq2000. The libraries were sequenced from both ends of the DNA molecules to a total read length of 100 nt from each end. The output from the lane with 18 libraries was 442,365,348 reads.http://usegalaxy.org). Briefly, the files were groomed to make sure the quality-scores line in the files use Sanger-scaled quality values with ASCII offset 33. The RNA-seq paired-end reads were mapped into transcripts using TopHat by setting the reference genome as S. cerevisiae . The transcripts were assembled and the FPKM (fragments per kilobase of exon per million fragments mapped) were estimated using Cufflinks with the default parameter settings, followed by transcripts merge using Cuffmerge. The assembled transcripts between control group and experimental group were compared using Cuffdiff, with cutoff p-value set as 0.05. The transcripts, of which the FPKM were identified as significantly different between the control group and experimental group, were picked and searched in the genome browser of BioCyc database to identify the specific genes included in the transcripts. The transcripts cluster analysis was achieved by using ‘clustergram’ of MATLAB . The gene ontology analysis was performed by using generic GO term mapper developed by Princeton University (http://go.princeton.edu/cgi-bin/GOTermMapper).The sequence files in FASTQ format were analyzed using the Galaxy software (http://www.yeastract.com/) [TF and TFnorm are the un-normalized and normalized transcription factor profiles, respectively. To get the reference and normalized transcriptional factor profiles for xylose metabolism and stress responses, two additional transcriptional datasets (ID: GSE27325 and GSE3812) were obtained from Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/). The top 250 differentially expressed genes were extracted and passed through the similar flowchart as described above to generate the reference normalized TF profile for xylose metabolism and stress responses, respectively. The Euclidean distance of the sample normalized TF profiles to the reference normalized TF profiles was then calculated as TFi,s and TFi,r are the ith element in the sample normalized TF profile and reference normalized TF profile, respectively, and n is the number of elements in the normalized TF profile.To generate the regulation matrix, the YEASTRACT database (ct.com/)  was soliXR: Xylose Reductase (XR); XDH: Xylitol Dehydrogenase (XDH); XKS: Xylulose Kinase; COMPACTER: Customized Optimization of Metabolic Pathways By Combinatorial Transcriptional Engineering; TFs: Transcription Factors; FPKM: Fragments Per Kilobase of Exon Per Million Fragments Mapped; GO: Gene Ontology; qPCR: quantitative Polymerase Chain Reaction; GEO: Gene Rxpression Omnibus; YPAD: Yeast Extract Peptone Dextrose; YPAX: Yeast Extract Peptone Xylose; DCW: Dry Cell Weight; CW: CTY-WT ; CI: CTY-INVp ; CC: CTY-CTYp ; IW: INV-WT ; II: INV-INVp ; IC: INV-CTYp .The authors declare that they have no competing interests.XF carried out all the experiments, analyzed the data and drafted the manuscript. XF and HZ read, revised and approved the final manuscript.Figure S1. Correlation between the cut-off valueand the number of transcripts identified as differentially expressed. Figure S2. Cluster analysis of transcriptional responses of INVSc1 host to xylose metabolism. Figure S3. FPKM of XR, XDH, and XKS in different recombinant S. cerevisiae strains. Figure S4. TF profiles of xylose metabolism regulations as reported in Microbial Cell Factories 2008, 7:18. Figure S5. TF profiles of xylose metabolism regulations using xylose isomerase pathway.Description of transcriptional factors involved in context dependence. Click here for file


ID1 gene, a target of ZNF382, but that binding is greatly reduced in the presence of MAGE I proteins. MAGE I expression relieved KAP1 mediated ID1 repression, causing increased expression of ID1 mRNA and ID1 chromatin relaxation characterized by loss of H3me3K9. MAGE I binding to KAP1 also induced ZNF382 poly-ubiquitination and degradation, consistent with loss of ZNF382 leading to decreased KAP1 binding to ID1. In contrast, MAGE I expression caused increased KAP1 binding to Ki67, another KAP1 target gene, with increased H3me3K9 and decreased Ki67 mRNA expression. Since KZNFs are required to direct KAP1 to specific genes, these results show that MAGE I proteins can differentially regulate members of the KZNF family and KAP1 mediated gene repression.Class I MAGE proteins (MAGE I) are normally expressed only in developing germ cells but are aberrantly expressed in many cancers. They have been shown to promote tumor survival, aggressive growth, and chemoresistance but the underlying mechanisms and MAGE I functions have not been fully elucidated. KRAB domain zinc finger transcription factors (KZNFs) are the largest group of vertebrate transcription factors and regulate neoplastic transformation, tumor suppression, cellular proliferation, and apoptosis. KZNFs bind the KAP1 protein and direct KAP1 to specific DNA sequences where it suppresses gene expression by inducing localized heterochromatin characterized by histone 3 lysine 9 trimethylation (H3me3K9). Discovery that MAGE I proteins also bind to KAP1 prompted us to investigate whether MAGE I can affect KZNF and KAP1 mediated gene regulation. We found that expression of MAGE I proteins, MAGE-A3 or MAGE-C2, relieved repression of a reporter gene by ZNF382, a KZNF with tumor suppressor activity. ChIP of MAGE I (-) HEK293T cells showed KAP1 and H3me3K9 are normally bound to the  We and others have found that MAGE I proteins bind to the RBCC region of KAP1(1). suppression of p53 by increasing KAP1 ubiquitin E3 ligase activity and p53 ubiquitination (2). global induction and maintenance of transcriptionally inactive heterochromatin characterized by Histone 3 tri-methyl lysine 9 (H3me3K9), and (3). suppression of specific genes by localized induction of transcriptionally inactive heterchromatin, targeted by KRAB domain containing zinc finger transcription factors (KZNFs).MAGE I expression in malignancies has been correlated with aggressive clinical course, the acquisition of resistance to chemotherapy, and poor clinical outcome ID1ID1 oncogene, a ZNF382 target, causing chromatin relaxation with decreased H3me3K9 and increased ID1 mRNA expression. MAGE I binding to KAP1 also induces ZNF382 poly-ubiquitination and degradation, suggesting the most likely mechanism is degradation of ZNF382, leading to release of KAP1 from the ZNF382 target site. In contrast, MAGE I expression increased KAP1 binding to the Ki67 gene, causing increased H3me3K9 and decreased Ki67 mRNA expression. Together, these data indicate that MAGE I proteins can increase expression of some genes while suppressing expression of others. Since KZNFs are required to direct KAP1 to specific sites, this work shows that MAGE I proteins can either positively or negatively regulate KZNF target gene expression, and establish the ability of MAGE I proteins to regulate members of the large and complex KZNF family.The KZNFs are the largest group of transcription factors known in vertebrates, and are involved in cell differentiation, proliferation, apoptosis, tumor suppression, and neoplastic transformation This work focuses on MAGE-A3 and MAGE-C2 as representatives of two major Class I MAGE families that they are often expressed in human cancers. We will refer to them collectively as “MAGE I”.MAGE I have a large terminal exon that usually encodes the entire protein and contains the MAGE homology domain (MHD), a conserved region of ∼170 amino acids that comprises about 70% of each MAGE protein and that recently has been implicated as the binding site for KAP1 L152A,L153A and MAGE-A3L120A,L121A, which have decreased ability to bind KAP1 ZNF382, also known as KS1, is a KZNF that was recently shown to be a tumor suppressor ID1ID1 gene ID1 gene in MAGE I (-) HEK293T cells and is associated with H3me3K9, indicating KAP1 induced chromatin compaction (ID1 mRNA production is low in this state (ID1 gene (p<0.05), decreases chromatin compaction as measured by H3me3K9 (p<0.05), and increases ID1 mRNA expression (p<0.01)  . NeitherID1 gene .Ki67 gene appropriate for ChIP analysis Ki67 because Ki67 is believed to play a role in proliferation and regulation of the cell cycle Ki67 (Ki67 mRNA (p<0.01) and protein expression were decreased by MAGE I  the reason for the opposite effects does not appear likely to reside in the MAGE I proteins and is more likely a function of the particular KZNF. KZNFs bind KAP1 by their KRAB domains, which are heterogeneous and may contain members of one or both of several KRAB A and KRAB B motifs ID1, or to increased binding and co-localization with MAGE I seen with Ki67. Except for sites of DNA damage, where KAP1 binds DNA in a sequence independent fashion, KAP1 normally requires binding to KZNFs to guide it to specific genes. KAP1 binds to ∼7,000 sites in the human genome Ki67. While the results with Ki67 seem to indicate an anti- proliferative affect of MAGE I proteins, it is important to consider the role of MAGE I in the DNA damage response, which requires a temporary pause in the cell cycle for DNA repair. Interestingly, when looked at over the course of 72 h we saw an initial drop in Ki67 expression followed by slow partial recovery, compatible with a temporary cell cycle halt (data not shown). While it remains to be determined how MAGE I regulation of Ki67 may affect overall cell proliferation or DNA damage repair, when these data are combined with our studies of ZNF382 they show unequivocally that MAGE I proteins may have differential effects (repression or de-repression) on different KAP1 KZNF targets.It is important to note that the effects of MAGE-A3 and MAGE-C2 are thus far always similar for a given gene and do not appear to be random, indicating a true biologic effect. Since both MAGE-A3 and MAGE-C2 have similar effects on each of the genes studied . CHO-5xGal4-UAS-TK-Luc-2p cells were cultured in F12 with 10% fetal bovine serum and 100 ug/ml hygromycin antibiotic RNA from cells was isolated using a total RNA isolation mini kit (Qiagen). Total RNA was treated with 2 units of DNase I (New England Biolabs). Reverse transcription and qRT-PCR were performed using an Advantage RT-for-PCR kit (Clontech) and SYBR Green Core PCR reagents (SABiosciences), according to manufacturer's recommendations. Quantification of qRT-PCR was done using an ABI Prism 7000 machine and ABI Prism 7000 SDS software (Applied Biosystem). Sequences of primers used for qRT-PCR are presented in To obtain the whole-cell lysate for western blot analysis, cells were lysed using denaturing RIPA buffer containing phosphate buffer saline (pH 7.4), 0.5% sodium deoxycholate, 0.1% SDS, 1% (v/v) NP-40, 100 mM sodium orthovanadate, and proteinase inhibitor cocktail (Sigma).2-terminal region 1–50 amino acids of KAP1), anti-KAP1 monoclonal 20C1 , anti-FLAG monoclonal M2 (Sigma) and anti-human H3me3K9 , and anti-human Ki67 .For human target validation studies and immunoprecipitation we used: anti–MAGE-C2 , anti-human KAP1 . ZNF382 with His tag at the 3′ end was also used in this vector. GGC CGA GTT AGT GGA GTT CGC AGC ACT CAA ATA CGA AGC AGA GGA GC) and 50 reverse (GCT CCT CTG CTT CGT ATT TGA GTG CTG CGA ACT CCA CTA ACT CGG CCA CC) were used to allow substitutions L152A and L153A in the MHD region of MAGE-C2. MAGE-A3- L120A, L121A was introduced using the primers 50 forward (GGT GGC CGA GTT GGT TCA TTT TGC AGC ACT CAA GTA TCG AGC CAG GGA GC) and 50 reverse (GCT CCC TGG CTC GAT ACT TGA GTG CTG CAA AAT GAA CCA ACT CGG CCA CC). PCR conditions included one cycle at 94°C for five minutes and 30 cycles of: 94°C for 30 sec, 60°C for 30 sec and 72°C for 30 sec, followed by one cycle of 72°C for seven minutes. PCR products were run on an agarose gel to confirm the presence of a product of correct molecular weight. Sequencing was performed to confirm the mutagenesis.Site-directed mutagenesis was done by overlap extension PCR (Invitrogen). MAGE-C2 mutation: L152A, L153 A. The primers including 50 forward , essentially according to the instructions of the manufacturer, with SEAP secreted reporter protein. The modified bait expression plasmid contains an SV40 promoter driving expression of a hybrid of full length (FL) or MHD MAGE-A3 or C2 and a DNA-binding domain (DBD). The modified prey expression plasmid uses the SV40 promoter driving a hybrid protein of an activation domain (AD) and FL or RBCC region KAP1. Binding of the bait and prey plasmids cis-activates E1b which in turn transactivates a reporter plasmid containing a secreted alkaline phosphatase (SEAP) cDNA. Phosphatase produced by the transactivated SEAP plasmid is measured by enzyme-based detection using the chemiluminescent substrate CSPD.(ΔCT of input − ΔCT of IP'ed DNA).ChIP assays were performed according to the protocol of the kit manufacturer (SABiosciences). Equal amounts of specific and nonspecific control IgG were used. Both input DNA and immunoprecipitated DNA were purified with SABiosciences DNA mini kit. All samples were analyzed by qRT-PCR and were carried out in triplicate with primers specific for these regions using SYBR Green Supermix (SABiosciences). The fold enrichment of target sequence was determined using the following formula: fold enrichment  = 2To test how MAGE I affects ZNF382, CHO cells with a ZNF382 luciferase reporter 5xGal4-UAS-TK-Luc-2p were evaluated after transfected with ZNF382 with or without MAGE-A3 or C2 or mutants. Luciferase assay was done as previously described 8 µg of wild-type or mutant MAGE-C2 or mutant expression plasmids, or empty vector control, were introduced into HEK293T cells at 70% confluency using the CaPO4 method (Clotech). 8 µg FLAG-ZNF382-His tag, 4 µg KAP1, 4 µg of pcDNA 3.1+ vector harboring HA tagged ubiquitin were co-transfected. After 20 h, the cells were treated with 25 µM of MG132  for 5 h, lysed in RIPA buffer, and subjected to immunoprecipitation. A 500 µg aliquot of total protein from the transfected HEK293T cells in 250 µl lysis solution was mixed with 10 µl of the anti-His affinity matrix  pre-blocked with 2% bovine serum albumin (BSA), and incubated overnight with gentle rotation at 4°C. The affinity matrix was washed with HIPA buffer three times, collected by centrifugation, and the precipitated proteins were denatured in sample buffer containing 0.1 M dithiothreitol (DTT), subjected to 7% SDS-PAGE and transferred to a PVDF membrane. The transferred proteins were then incubated with anti-His , or anti-HA  antibodies. Anti-mouse IgG, HRP-linked secondary antibodies  were used for the western blotting procedure.


Facilitates Chromatin Transactions) complex performs essential functions in eukaryotic cells through the reorganization of nucleosomes. During transcription, FACT reorganizes nucleosomes to allow passage of RNA Polymerase II and then assists in restoring these nucleosomes after RNA Polymerase II has passed. We have previously shown, consistent with this function, that Spt16 facilitates repression of the SER3Saccharomyces cerevisiae  gene by maintaining nucleosome occupancy over the promoter of this gene as a consequence of intergenic transcription of SRG1 noncoding DNA. In this study, we report the results of a genetic screen to identify mutations in SPT16 that derepress SER3. Twenty-five spt16 mutant alleles were found to derepress SER3 without causing significant reductions in either SRG1 RNA levels or Spt16 protein levels. Additional phenotypic assays indicate that these mutants have general transcription defects related to altered chromatin structure. Our analyses of a subset of these spt16 mutants reveal defects in SRG1 transcription-coupled nucleosome occupancy over the SER3 promoter. We provide evidence that these mutants broadly impair transcription-coupled nucleosome occupancy at highly transcribed genes but not at lowly transcribed genes. Finally, we show that one consequence shared by these mutations is the reduced binding of mutant Spt16 proteins across SRG1 and other highly transcribed genes. Taken together, our results highlight an important role for Spt16 in orchestrating transcription-coupled nucleosome assembly at highly transcribed regions of the genome, possibly by facilitating the association of Spt16 during this process.The highly conserved FACT ( In eukaryotes, genomic DNA is packaged with proteins to form chromatin, a repeating array of nucleosomes that contain 147 bp of DNA wrapped around an octamer of histone proteins (Facilitates Chromatin Transactions) is a prominent member of the histone chaperone family with reported functions in multiple nuclear processes including DNA replication, DNA repair, transcription initiation, and transcription elongation [reviewed in in vitro  domain that is thought to be involved in dimerization with Spt16, a middle (M) domain that contains a double pleckstrin homology motif, and an acidic C-terminal (C) domain , dimerization (D), middle (M), and C-terminal (C) domains  are isogenic to a GAL2+ derivative of S288c  in lyp1Δ::SER3prURA3-  , synthetic complete (SC), omission (SC−), 5-fluoroorotic acid (5-FOA), and galactose media have been previously described  and from +1430 to +3521 (region C), were amplified from pAO01 plasmid (gift from A. Duina) using GoTaq polymerase (Invitrogen) and standard PCR conditions. Amplified DNA was cotransformed into YJ1089 with pAO01 plasmid that had been digested with either Eag1 and SnaB1 (region B) or SnaB1 and XbaI (region C). Transformants containing gap-repaired plasmids were selected on SC medium lacking leucine and then replica-plated onto medium containing 5-FOA to select for cells that lost the URA3-marked plasmid carrying a wild-type copy of SPT16 (pSPT16-URA3). The resulting colonies were then replica-plated to SC medium lacking histidine and leucine that was supplemented with 5 mM 3-AT. Candidate plasmids were recovered from strains resistant to 5 mM 3-AT, retransformed into YJ1089, and retested for their ability to confer 3-AT resistance. The region of SPT16 that was subjected to PCR mutagenesis was first subcloned into a new copy of pAO01 before retransformation. For each plasmid that retested for 3-AT resistance, both strands of the entire SPT16 gene were sequenced and compared with the wild-type gene.Using a previously described strategy , SER3 (+111 to +1342), and SCR1 (−163 to +284) were generated by random-primed labeling of PCR fragments amplified from genomic DNA. RNA levels were quantified using a PhosphorImager (FLA-5000) and ImageJ software.Cells were grown to approximately 2 × 10escribed . Radiola7 cells/ml using trichloroacetic acid as previously described , anti-Pob3 , anti-G6PDH . After incubation with HRP-conjugated IgG secondary antibody , the immunoreactive proteins were visualized by enhanced chemiluminescence detection (PerkinElmer) using a Kodak image station 440CF. Spt16 and Pob3 protein levels were calculated by measuring their signal intensities in these Western blots using Kodak ID 3.6 software and normalizing these values to those obtained for the G6PDH control.Whole cell extracts (WCE) were prepared from cells grown in YPD at 30° to approximately 3 × 108 cells/ml, cultures were serially diluted 10-fold. Three microliters of each dilution was spotted onto indicated media and incubated at 30° for the indicated number of days.Cells were grown at 30° overnight to saturation then washed twice with water. Starting at 1 × 107 cells/ml in YPD and subjected to a nucleosome-scanning assay, as previously described  was calculated as a ratio between MNase-digested and MNase-undigested samples and then normalized to the amount of MNase-protected control template (GAL1 NB) that is located within a well-positioned nucleosome in the GAL1 promoter , or 2.5 μl anti-Rpb3 antisera  followed by the addition of IgG-Sepharose beads  for 2 hr at 4°. Dilutions of input DNA and immunoprecipitated DNA were analyzed by qPCR reactions. Primer sets that amplify the following regions were used for qPCR: SER3-41 ; SER3-25 ; SER3-22 ; SER3-7 (+195 to +295); PYK1 ; PMA1 ; ADH1 (+845 to +943); CYC1 (+122 to +217); TUB2 ; and GAL1 . Histone H3, Spt16, and Rpb3 ChIP signals for each gene were normalized to a No ORF control template, which is located within a region of chromosome V that lacks open reading frames  and the indicated primers .Saccharomyces cerevisiae whereby transcription of SRG1 ncDNA assembles nucleosomes over the promoter of the adjacent SER3 gene to maintain SER3 repression , which is dispensable for SER3 repression . These PCR fragments were cotransformed with a gapped LEU2-marked plasmid that contained homology to the PCR fragments into an spt16Δ his3Δ strain containing an integrated SER3prHIS3- reporter (SPT16 from a URA3-marked plasmid (YJ1089). Following gap-repair and loss of the URA3-marked plasmid expressing SPT16, we screened for spt16 mutants that derepress the SER3prHIS3- reporter by their ability to confer growth in the presence of 3-AT, a competitive inhibitor of the HIS3 gene product , double (11), or triple (2) amino acid substitutions. For the 12 single amino acid substitution mutants, the location of the altered amino acids varies: 3 are located at the very 3′ end of the Spt16-NTD, 3 are found in Spt16-D, and the remaining 6 are found in Spt16-M, including 3 residues that are within 13 amino acids of each other  and was found to genetically interact with mutations in other transcription elongation factors.With this screen, we initially identified 522 mutants that permit growth on medium containing 5 mM 3-AT. Forty ch other . Interesspt16 mutants that we isolated confers a growth defect at elevated temperatures (39°) or in the presence of HU .To further characterize these mutants, we tested the strains for temperature sensitivities and growth defects on YPD medium supplemented with cyclohexamide (CHX), hydroxyurea (HU), mycophenolic acid (MPA), and caffeine. Surprisingly, we found that not one of the ce of HU , phenoty16-G132D , row 2 a8I/P859S , row 3  to milder  that are similar to what we had previously observed for spt16-G132D . Compared with strains containing wild-type control plasmids, protection from MNase digestion was reduced across the SRG1-transcribed region in all the spt16 mutants examined to degrees approximately equal to or exceeding that of spt16-G132D , compared with the other mutants that had increases in MNase sensitivity that were more evenly distributed across the SRG1 transcription unit , which is caused by defects in chromatin and aberrant transcription initiation  phenotype of a histone mutant, H3 L61W, a phenotype that has been previously described for a distinct class of mutations located within the Spt16 M-domain (spt16Δ cells containing the H3 L61W mutant as the sole source of histone H3 (YADP50) and plasmid-borne copies of wild-type or mutant versions of SPT16 were monitored for growth on YPD at 15° (spt16-E735G control (kindly provided by A. Duina), none of our identified spt16 mutants suppressed the cold sensitivity of H3 L61W. Therefore, the spt16 mutants we isolated as being defective for SER3 repression represent a distinct class of mutants from those that suppress the cs phenotype of the H3 L61W mutant and may define functionally distinct regions of the Spt16-D and Spt16-M domains.Finally, we tested the D at 15° . When coSpt16 fail to be recruited normally to transcribed regions, which may account for their multiple phenotypes related to defects in transcription-coupled nucleosome occupancy. Therefore, we performed ChIP experiments to assess the binding of selected Spt16 mutant proteins across the SRG1 transcription unit  in Rpb3 binding across SRG1. However, by normalizing the binding of this mutant version of Spt16 to Rpb3 binding, it is clear that this minor decrease in Rpb3 binding alone cannot account for the reduced binding of this mutant version of Spt16 across SRG1 , PYK1 (95 mRNA/hr), and ADH1 (125 mRNA/hr) , TUB2 (12 mRNA/hr), and CYC1 (10 mRNA/hr)  was detected at these highly transcribed genes, comparable to what we observed at SRG1. In contrast to what we observed at highly transcribed genes, occupancy of the mutant Spt16 proteins and Rpb3 at three lowly transcribed genes, GAL1, TUB2, and CYC1, were largely unaffected. Importantly, we show that when these mutants are grown in galactose-containing medium to induce high levels of GAL1 expression, we detected reduced occupancy of both H3 and the mutant Spt16 proteins to the GAL1 coding sequence similar to what we observed for SRG1 and other highly transcribed genes . Thus, we have identified mutant spt16 alleles that cause reduced occupancy of both the mutant version of Spt16 encoded by these alleles and histones specifically over highly transcribed regions of the genome. Taken together, our studies suggest that the integrity of the Spt16-D and Spt16-M domains is generally required to maintain nucleosome occupancy at highly transcribed genes, possibly by facilitating Spt16 recruitment to those genes.We next examined the occupancy of these mutant derivatives of st genes . Consist regions . InteresSpt16 is an essential, highly conserved component of the FACT elongation complex with a dual role in transcription elongation—the disassembly of nucleosomes to allow the passage of RNA Pol II and their reassembly in the wake of RNA Pol II [reviewed in Spt16-D and Spt16-M domains are required to support the histone chaperone activities of Spt16 during transcription elongation. We utilized a previously characterized system in which this activity of Spt16 is required for SRG1 transcription–dependent repression of the SER3S. cerevisiae  gene , the spt16 mutants that we identified in this work are distinct from those that have been previously identified by other genetic approaches . Therefore, I626T and one or both of T651A and H741Y substitutions appear to suppress the negative effects of the E857K substitution.Interestingly, the Spt16-D and Spt16-M domains revealed a strong correlation between defective transcription-dependent nucleosome assembly and reduced association of these mutant versions of Spt16 at highly transcribed regions of the yeast genome. Several possible models could account for these observations. First, these mutant versions of Spt16 may interfere with the normal recruitment of FACT to transcribed DNA. In this model, the reduced recruitment of FACT would be the cause of the defect in transcription-coupled nucleosome assembly. Although several studies have determined that FACT physically associates with DNA that is being transcribed (Spt16 association with transcribed DNA, including the Chd1 chromatin-remodeling factor, the Paf1 elongation complex, RNA Pol II, and histone proteins (Spt16-D and Spt16-M domains that interfere with transcription-coupled nucleosome assembly do so by altering FACT interactions with one or more of these factors. Second, the reduction in Spt16 association with transcribed regions may be a consequence of the reduced nucleosome occupancy due to a defect in transcription-coupled nucleosome assembly. In this model, the amino acid substitutions in the Spt16-D and Spt16-M domains would not alter initial Spt16 recruitment to transcribed DNA or its ability to associate with nucleosomal DNA but, rather, interfere with its nucleosome remodeling activity that leads to disassembly and/or reassembly of nucleosomes during transcription. Additional molecular and biochemical experiments to investigate the affect of these mutants on FACT interactions with other proteins and the nucleosome remodeling activity of Spt16 will be necessary to distinguish between these models.Our analysis of the single amino acid substitutions in the Spt16-D and Spt16-M domains may directly mediate protein-protein interactions or FACT nucleosome remodeling activity is intriguing, we cannot rule out a more indirect role for these domains. For example, it is possible that the three mutations in the Spt16-D domain may simply disrupt the Spt16-Pob3 interface (Spt16-Pob3 dimer interface to be subtle, specifically affecting the activity of FACT in transcription-dependent nucleosome assembly rather than in a more general histone chaperone role. Large perturbations in the Spt6-Pob3 interaction would most likely lead to more broad defects in cell growth and DNA replication/repair, which were not detected in these mutants by our phenotypic assays.Although the possibility that the nterface . Howeverspt16 mutants that specifically impairs transcription-coupled nucleosome occupancy across highly transcribed regions of the S. cerevisiae genome and results in reduced association of the mutant Spt16 proteins to these regions. These mutants are likely to be useful molecular tools to further elucidate the dynamic function of Spt16 in maintaining chromatin architecture during transcription.In summary, we have identified a novel class of


Schizosaccharomyces pombe, providing an important conceptual framework for possible modes of action of ncRNAs also in other organisms. In this review, we highlight mechanistic insights into chromatin-associated ncRNA activities gained from work with fission yeast, and we draw parallels to studies in other eukaryotes that indicate evolutionary conservation.RNA transcripts that do not code for proteins have been long known to lie at the heart of many biological processes, such as splicing and translation. Yet their full potential has only been appreciated recently and non-coding RNAs (ncRNAs) are now attracting increasing attention. Pioneering work in yeast and plant systems has revealed that non-coding RNAs can have a major influence on the deposition of histone and DNA modifications. This can introduce heritable variation into gene expression and, thus, be the basis of epigenetic phenomena. Mechanistically, such processes have been studied extensively in the fission yeast  Recent advances in technologies enabling the profiling of transcriptomes at unprecedented depth have revealed the production of RNA in eukaryotic cells from a proportion of their genomes much larger than anticipated  -related pathways act solely as guide molecules Hannon . With a Caenorhabditis elegans in 1998 -mediated process in NAs Fig.   generated upon DNA damage were proposed to affect protein synthesis after DNA damage by inhibiting rRNA biogenesis  genome RNAs that control transposable elements in the germline of animals have been linked to chromatin regulatory processes. Mutations in piRNA pathway components led to defective DNA methylation in male mouse germ cells , Dicer (Dcr1) and the RNA-dependent RNA polymerase (Rdp1), are essential for the formation of centromeric heterochromatin -containing Chp1 component. Interestingly, the Chp1 CD also possesses intrinsic nucleic acid-binding activity, a property that can further stabilize RITS association with chromatin   gene is linked to Ubx expression. As in the case of SRG1, ncRNA transcription leads to Ubx repression. Finally, extensive truncation and promoter-swap experiments in mice have shown that silencing of the imprinted Ifg2r gene also results from transcriptional overlap between protein-coding and non-coding sequences, without a contribution by the long ncRNA Airn itself (Latos et al. Similar ncRNA-transcription-dependent but ncRNA-independent regulatory processes have been described in other organisms. In Much excitement has been triggered by the notion that eukaryotic cells transcribe a much greater proportion of their genomes than anticipated, and that these seemingly non-protein coding RNAs may add yet another layer of complexity to genome regulation. Clearly, the examples highlighted in this review and others demonstrate that some ncRNAs are functionally highly relevant. However, for most of the “non-coding transcriptome” of different organisms, the extent of ncRNA involvement in regulatory circuits and the mechanisms by which they might act remain largely unexplored. Thus, a future challenge will be to systematically probe ncRNAs for physiological relevance.cis on chromatin. Given the recent advances in genome-editing technologies (Wang et al. The power of yeast has been its genetic tractability, which has allowed specific manipulations of an ncRNA and its underlying genomic sequence in order to perform loss-of-function experiments. The ability to do so is of particular importance when the ncRNA under investigation acts in Most importantly, the properties and functions of ncRNAs, whether or not their activities are associated with chromatin, are likely to be heavily dependent on their interactions with specific proteins. Therefore, we must aim at developing strategies to determine the protein partners of ncRNAs, similar to a recent proteomic study in which close to 800 proteins were identified based on their ability to bind to polyadenylated transcripts (Baltz et al.


Plasmodium falciparum is responsible for the most severe form of malaria in humans. Antigenic variation of P. falciparum erythrocyte membrane protein 1 leads to immune evasion and occurs through switches in mutually exclusive var gene transcription. The recent progress in Plasmodium epigenetics notwithstanding, the mechanisms by which singularity of var activation is achieved are unknown. Here, we employed a functional approach to dissect the role of var gene upstream regions in mutually exclusive activation. Besides identifying sequence elements involved in activation and initiation of transcription, we mapped a region downstream of the transcriptional start site that is required to maintain singular var gene choice. Activation of promoters lacking this sequence occurs no longer in competition with endogenous var genes. Within this region we pinpointed a sequence-specific DNA–protein interaction involving a cis-acting sequence motif that is conserved in the majority of var loci. These results suggest an important role for this interaction in mutually exclusive locus recognition. Our findings are furthermore consistent with a novel mechanism for the control of singular gene choice in eukaryotes. In addition to their importance in P. falciparum antigenic variation, our results may also help to explain similar processes in other systems. Borrelia spp., Neisseria spp., Giardia lamblia, Plasmodium falciparum and Trypanosoma brucei, this paradigm of clonal phenotypic variation reaches a remarkable yet poorly understood level of sophistication  on the RBC surface  in ring-stage parasites during the first half of the IDC   and demonstrated its exclusive localization to the active var locus suggesting a role for this enzyme in the transmission of epigenetic memory  that is essential for var promoter activation. Notably, we also identified a region downstream of the transcriptional start site (TSS) and demonstrate an important role for this element in mutually exclusive promoter recognition. In absence of this sequence var promoters are fully active but, unlike wild-type promoters, do not compete with endogenous var gene transcription. Within this region we identified a 47 bp motif that interacts in a sequence-specific manner with an unknown nuclear protein. Together, our results show for the first time that the complex regulation of mutually exclusive var gene transcription involves functional cis-acting modules with intrinsic and position-dependent activities. They are furthermore consistent with a novel mechanism in sustaining singular gene choice in eukaryotes.We postulated that transcriptional control of var promoter elements we employed a system suitable to analyse promoter activity in stably transfected parasites. All reporter constructs are based on the parental plasmid pBC (bsd) resistance cassette selects for stable episomes. A 2.5 kb var upsC upstream sequence (PFL1960w) controls transcription of the dual reporter encoding human dihydrofolate reductase fused to green fluorescent protein (hdhfr-gfp). A var gene intron element is located downstream of the hdhfr-gfp cassette to account for its role in var gene regulation. A telomere-associated repeat element 6 sequence (TARE6/rep20) is included for improved plasmid segregation . As shown in var promoter activity. The promoter in pBC5, lacking 491 bp of the 5′ UTR, was also fully active. In contrast, the truncation encompassing bps −1057 to −1 in pBC4 caused a significant reduction in steady-state transcript levels. Hence, this approach identified two regulatory regions, located upstream and downstream of the putative TSS, respectively, which fulfil important roles in var promoter function.To identify elements involved in promoter activation and mutual exclusion we sequentially truncated the upsC upstream sequence from either the 5′ or 3′ end B. We chokahrp) gene promoter for three reasons. First, the TSS of this gene has been mapped to 849 bp upstream of the ATG  (min). qRT-PCR analysis revealed that upsC fragments C1 (−1679 to −1200) and C2 (−1401 to −727) consistently activated Kmin to a similar extent in both the episomal and chromosomal context whereas fragment C3 had no effect. Furthermore, neither the var intron nor the rep20 element altered Kmin activity. Together, these findings corroborate the results obtained with the upsC deletion constructs and are consistent with the presence of a var UAS located between bps −1401 and −1217. The fact that this element activates transcription from a heterologous minimal promoter suggests an autonomous, context-independent function in activating RNA polII-mediated transcription.We cloned two overlapping fragments containing the putative upsC UAS upstream of KBC2Kmin) D and S1.BC2Kmin) B, was usHere, we investigated the functional region downstream of the putative TSS that is defined by plasmids pBC4 and pBC5 (−1057 to −491). Deletion of this region caused a substantial reduction in steady-state transcripts B, suggesvar promoters do not transcribe endogenous var genes and fail to express PfEMP1  in electromobility shift assays (EMSA) using parasite nuclear extracts. Whereas MEE1 and MEE3 showed no sign of specific binding (data not shown), the central 47 bp MEE2 fragment formed a DNA–protein complex that was specifically competed in a dose-dependent manner by an excess of homologous competitor only A. To chavar genes. We inspected all var upstream sequences (−600 to −1 relative to the start ATG) and identified a perfect or slightly deviated MEE2 core motif with the consensus sequence (A/T)(A/T)(A/T)GA(T/A)TA in 44 (73%) out of all 60 var genes. Strikingly, in all but four cases this motif (i) is conserved in terms of orientation and position relative to the ATG start codon, (ii) is embedded in an overall highly similar sequence context including a characteristic poly-dT stretch, and (iii) occurs in upsB-, upsC-, upsB/C- and upsB/A-type var genes (var gene (PF07_0048), in which six nucleotide positions are changed compared with MEE2 including one substitution in the core motif, competed as efficiently as the wild-type MEE2 motif (var gene (PFL0005w), in which 19 positions are altered including two in the core motif, competed albeit with lower efficiency (var upsA (PFD1235w) and a var-unrelated rif (PFB0035c) upstream region, in which an AT(A/T)GATTA core motif is present at the same relative position as in MEE2, failed to inhibit formation of the MEE2–protein complex  also binds to related motifs found in a large proportion of T. brucei, the causing agent of African sleeping sickness, mutually exclusive transcription of variant surface glycoprotein genes is carried out by an extranucleolar RNA polI-containing body  to a cis-acting sequence motif present in this region (MEE2) corroborates this hypothesis and suggests an important role for this DNA–protein interaction in mutually exclusive promoter activation. The presence of MEE2-related motifs in a large subset of var genes provides circumstantial evidence for a conserved mechanism of singular var gene choice. Although the exact function of this interaction remains to be discovered, binding of MIF to the mutual exclusion element may earmark var loci for mutually exclusive activation. Additional experiments tailored towards identifying MIF and dissecting the exact function of this interaction in var regulation are now required to test this hypothesis. In this context it is worth mentioning that the 47 bp MEE2 sequence does not contain any obvious ApiAP2 transcription factor-binding motifs  . RNA was glyoxylated for 1 h at 55°C in five volumes glyoxal reaction mixture and electrophoresis was performed using 1× BPTE-buffered 1.5% agarose gels  was performed on whole-cell lysates. Primary antibody dilutions were: mouse anti-GFP , 1:500; mouse anti-GAPDH 1-10B (kind gift of Claudia Daubenberger), 1:20 000. PfEMP1 was extracted from trophozoite-infected RBC pellets (Triton X-100-insoluble/SDS soluble fraction) as described (van Schravendijk et al., High-salt nuclear extracts and EMSAs were prepared and carried out as described (Voss