ChIP-seq experiments detect the chromatin occupancy of known transcription factors in a genome-wide fashion. The comparisons of several species-specific ChIP-seq libraries done for different transcription factors have revealed a complex combinatorial and context-specific co-localization behavior for the identified binding regions. In this study we have investigated human derived ChIP-seq data to identify common cis-regulatory principles for the human transcription factor c-Fos. We found that in four different cell lines, c-Fos targeted proximal and distal genomic intervals show prevalences for either AP-1 motifs or CCAAT boxes as known binding motifs for the transcription factor NF-Y, and thereby act in a mutually exclusive manner. For proximal regions of co-localized c-Fos and NF-YB binding, we gathered evidence that a characteristic configuration of repeating CCAAT motifs may be responsible for attracting c-Fos, probably provided by a nearby AP-1 bound enhancer. Our results suggest a novel regulatory function of NF-Y in gene-proximal regions. Specific CCAAT dimer repeats bound by the transcription factor NF-Y define this novel cis-regulatory module. Based on this behavior we propose a new enhancer promoter interaction model based on AP-1 motif defined enhancers which interact with CCAAT-box characterized promoter regions. Transcription factors (TFs) are proteins that control gene expression through a variety of mechanisms such as enhancing the efficiency of the basal transcription complex to assemble or re-model chromatin. Most of them act by recognizing cis-regulatory elements or TF binding sites (TFBS) in gene proximal (promoter) or distal (enhancer) regions in a sequence-specific way. Each regulatory region is defined by an array of such TFBSs. The cooperative binding of multiple TFs to these closely located TFBSs determines the transcription activity of their target genes , 2. PoteThe ChIP-seq technology is widely used to systematically identify gene regulatory regions interacting with a known TF. ChIP-seq experiments combine chromatin immunoprecipitation with high-throughput sequencing to reveal TF-bound regions in a genome-wide fashion . The EncThe missing capability of ChIP-seq experiments to distinguish between direct and indirect TF binding is a notable fact which explains why the interpretation of ChIP-seq-derived regulatory regions is still a challenging task. For example, the nuclear glucocorticoid receptor (GR) and the activator protein 1 (AP-1) have been shown to interact with each other in two different modes. GR can interact with AP-1 in a DNA-dependent mode using two adjacent composite regulatory elements for the TFs GR and AP-1. Alternatively, the GR can interact with AP-1 at non-composite elements through protein-protein interaction (tethering). These regions contain an AP-1 binding motif (TFBS), but no corresponding GR binding motif .Complex and dynamic co-localization patterns were described for a set of TFs related to ChIP-seq experiments done in one cell type under changing conditions or across different cell types. As an example, it was shown that proximal and distal c-Fos precipitated ChIP-seq regions are characterized by different sets of co-localized TFs . For theIn the light of these findings, we made an attempt to revisit the existing c-Fos and NF-YB ChIP-seq data done in the ENCODE framework with regard to predominant sequence motifs. In this study, we present a systematic analysis of ChIP-seq data for the transcription factor c-Fos in the cell lines HUVEC, HeLa S3, K562, and GM12878. We developed a workflow based on Receiver Operator Characteristic (ROC) curves to identify important TFBS motifs for each proximal and distal ChIP-seq data sets separately. Using cell-type specific non-overlapping DNase-seq data sets as a negative control, we were able to identify the main regulators for each binding regions. We found that in four different cell lines, c-Fos precipitated proximal (promoter) and distal (enhancer related) genomic intervals show clear prevalences for either AP-1 motifs or CCAAT boxes as known binding motifs for the transcription factor NF-Y, which occur in a mutually exclusive manner. Based on this behavior we propose a new enhancer promoter interaction model based on AP-1 motif defined enhancers which interact with CCAAT-box characterized promoter regions. We show that this type of interaction is specific for genes associated with a certain group of biological processes of Gene Ontology.de novo the most prevalent sequence motif in each ChIP-seq data set  proximal and distal regions differ in their prevalence of either AP-1 or NF-Y binding motifs, and (b) this feature is also different among the four cell lines. In human umbilical vein endothelial cells (HUVEC), both proximal and distal c-Fos-bound regions are enriched for potential AP-1 sites. Both types of ChIP-seq intervals  from GM12878 (a human lymphoblastoid cell line) harbor CCAAT boxes as the most characteristic trait see also  Figs. ThSince we have observed that a large number of c-Fos-targeted genomic intervals, in particular proximal intervals, exhibit NF-Y binding motifs rather than the expected AP-1 motifs, we checked whether they have already been evidenced as bound by the transcription factor NF-Y. For three out of four cell lines investigated here, ChIP-seq data sets for the subunit NF-YB were available in the ENCODE repository . It was shown that NF-YB precipitated ChIP-seq regions define NF-Y binding sites . We therWe found that most of the proximal c-Fos-targeted regions were also bound by NF-YB . All of them exhibited a CCAAT box as prevalent motif (data not shown). Among those intervals that interact with c-Fos(only), i.e. not with NF-YB, only a subset harbors a high-scoring AP-1 motif, that could be identified by TRANSFAC matrix V$JUNDM2_04. For sake of conciseness, we denote in the following genomic intervals that are targeted by c-Fos(only) and do have an AP-1 motif above the optimized threshold with c-Fos. The regions that lack such a motif are labeled with c-Fos. The portion of c-Fos intervals varies largely between the three cell lines . Motif discovery using MEME confirmed the predominant role of AP-1 consensus motifs in these c-Fos sequences . In addiWhen we analyzed the cell-type specific co-localization pattern of c-Fos and NF-YB targeted regions for distal intervals, the picture clearly differed from that of the proximal regions. Only 8% of c-Fos targeted distal regions overlapped with NF-YB regions in HeLa S3. This portion was larger for K562 (34.1%), and the largest co-localization pattern was observed for the GM12878 cell line (86.6%). When we assessed the amount of high-scoring AP-1 motifs in distal regions we found much higher proportions of c-Fos than in the proximal regions . Motif discovery using MEME verified the dominant role of AP-1 motifs in this group (data not shown). In contrast to the proximal intervals we found no enrichment of CCAAT box motifs in c-Fos regions. Instead an alternative AP-1 motif was found to be enriched in HeLa S3 and K562 intervals .In this context we analyzed the co-localization pattern related to enhancer and promoter regions for the transcription factor c-Jun. The ENCODE project offers three different c-Jun ChIP-seq experiments that are overlapping with cell lines used in this study: (i) HUVEC, (ii) HeLa S3, and (iii) K562. For the enhancer related genomic intervals that are characterized by at least one AP-1 motif we found 52% , 68% , and 95%  which co-localize with c-Jun precipitated genomic intervals for these three cell lines. We conclude that these regions are mainly regulated by AP-1 and that the AP-1 transcription factor is assembled through the c-Fos/c-Jun heterodimer complex. Interestingly, we found no equivalent co-localization pattern for the corresponding promoter sets. Only 38% , 10% , and 15%  of promoter related c-Fos precipitated ChIP-seq intervals are overlapping with c-Jun intervals for the HUVEC, HeLa S3, and K562 cell lines. Summarizing these observations we suppose that c-Fos is the main interaction partner for our proposed enhancer/promoter model. As a member of the enhancer bound AP-1 heterodimer it is interacting with the transcription factor NF-Y (directly or indirectly) that is bound to the CCAAT box or CCAAT box repeats in their corresponding promoter regions.Our data analysis thus demonstrates that proximal c-Fos precipitated ChIP-seq intervals that are not co-localized with NF-Y related binding events contain CCAAT motifs and at the same time were lacking AP-1 motifs. This observation was found in all three cell-types for proximal ChIP-seq intervals.To get a more robust criterion for the co-occurrence probability of these two regulatory elements, we checked the appearance of high-scoring potential AP-1 and NF-Y binding sites in the proximal and distal regions bound by c-Fos in either of the four cell lines. We recorded the presence of AP-1 or NF-Y binding motifs using TRANSFAC/Match , 22 and As can be seen in R = −0.9571; Focusing on those c-Fos-bound ChIP-seq interval sets that exhibit either motif, we observed in the sequence sets shown in We monitored the ROC curves for both motifs in the union set of all proximal intervals where c-Fos and NF-YB co-localize in at least one of the three cell lines  compared to non-overlapping DHS sites as background set (control set). In Based on the observed result we conclude a mutually exclusive behavior for c-Fos-targeted regions if they are containing high-affinity AP-1 or NF-Y motifs. Enhancer regions active in HeLa S3 or in K562 cells were characterized by AP-1 motifs, promoters of these two cells were enriched for CCAAT box motifs. The GM12878 promoters are shaped by CCAAT boxes as well, but due to the low number of c-Fos-bound enhancers in these cells no statistical statement can be made upon their motif composition.As was observed from the MEME analyses, c-Fos-targeted proximal regions tend to exhibit two distinguishable variants of CCAAT boxes , Inter, and NF-YB(only) has been studied in more detail. The We conclude that c-Fos-targeted promoters that do not exhibit an AP-1 motif but are characterized by direct CCAAT box repeats, preferable at a distance of 31bp, define a novel sequence-specific regulatory module bound by the transcription factor NF-Y.P = 3.31703e − 281).It has been discussed earlier, that enhancer-bound proteins may be cross-linked by the ChIP procedure also to promoters targeted by these enhancers . We therThe ENCODE project investigated a genome-wide annotation of chromatin state for different cell lines . Based oFor all three data sets (i-iii) we observe a large overlap (89–93%) to chromatin modifications that are observed for active promoter regions. This result verifies our proximal data sets as promoter regions and support the relevance of the double CCAAT box as a main feature in this data sets.To verify our distal genomic intervals as potential enhancers we determine the overlap of the distal genomic intervals to chromatin modifications related to active enhancers. The AP-1 motifs that are characterizing distal genomic intervals show a large overlap with active enhancer regions defined by the ChromHMM data sets.Two-thirds of all enhancer/promoter interactions in the GM12878 cell line are directed to the nearest active promoter . Based oBoth transcription factors c-Fos as well as NF-Y are known to interact with the co-activator p300 by binding either to the C-terminal or a central region of the p300 molecule, respectively , 26. SinIn order to detect potential functional correlates of the c-Fos(CCAAT) promoters, in particular those that harbor a direct CCAAT repeat, we mapped all proximal regions into three classes: c-Fos(only), Inter, or NF-YB(only) see . From thFor the c-Fos(only) set, we did not find any enrichment of a GO-defined biological process  after p-The explicit enrichment of chromatin and nucleosome assembly process categories in proximal regions of nearby genes, where (a) c-Fos- and NF-YB-co-localize, (b) the direct CCAAT tandem arrangement is present, and (c) co-activator p300 co-localizes may indicates that direct CCAAT boxes have a distinct regulatory influence on these processes. These repeats are the dominating feature in this group and contain no high-scoring AP-1 motifs. We hypothesize that these dimers define an appropriate interface for a transcription factor complex which comprises c-Fos, NF-YB and, probably, the co-activator p300.http://www.factorbook.org/mediawiki/index.php/C-Fos). Also, Fleming et al. reported co-localization of NF-Y and c-Fos at CCAAT, typically at loci lacking an AP-1 motif [T(c/g)a. A particular instance with a potential AP-1 half site 5’ to the CCAAT box was suggested as well [During our analysis of the different c-Fos related ChIP-seq data sets, we made a couple of noteworthy observations. The first was that many c-Fos-targeted promoters exhibit an AP-1 motif, as to be expected, but that an even higher number is rather characterized by a CCAAT box; since these promoters are also found in an NF-YB data set, their CCAAT boxes serve obviously as NF-Y binding sites. This finding confirmed earlier observations on the same data sets, which have already been described in factorbook  as being-1 motif . One exp-1 motif . Co-immu-1 motif . However-1 motif . The rea-1 motif  have not as well . However as well .Moreover, our second observation was that CCAAT boxes and AP-1 motifs even appear in a mutually exclusive way. If a high-scoring AP-1 binding site is found in a c-Fos ChIP-seq region, no NF-Y binding motif is detectable and vice versa by motif matching (TRANSFAC/MATCH) or motif discovery (MEME) approaches. We conclude that c-Fos-targeting of promoters that are characterized by CCAAT boxes even depends on the absence of a genuine AP-1 binding binding site in the same promoter. We suppose an interfering mechanism of such an AP-1 binding motif which prohibits formation of a proper enhanceosome.While we could exclude the presence of obscure AP-1 motifs or other accompanying binding sites to explain the c-Fos-targeting to c-Fos(CCAAT) promoters, we checked whether any particular arrangement of the CCAAT boxes could provide an explanation. We were able to identify recurring patterns of two tandem copies of CCAAT boxes specifically in the c-Fos-targeted promoters, with a pronounced distance distribution profile. The main peak is at a distance of 31 base pairs between the two CCAAT boxes, followed by decreasing maxima of around 41, 52 and 63 bp. The difference of 10-11bp between these peaks indicates a conserved orientation of the two CCAAT boxes on the same side of the DNA double helix. It has been shown by structural analysis of NF-Y/DNA co-crystals that the NF-Y heterotrimer induces a strong bending of the DNA by about 80 degree between the second A and the T of the CCAAT box . Since tIn contrast to the promoters related intervals, most of the enhancer intervals that are targeted by c-Fos in the cell lines HeLa S3 and K562 exhibit a clear AP-1 motif. This prompted the speculation that it might have been the enhancers that contribute to the c-Fos-binding to the respective promoters, detected by ChIP after cross-linking of protein complexes that were bound to both enhancers and promoters as discussed by Mercer and Mattick . This waThe functional categorization of genes with c-Fos-targeted promoters revealed as most prominent GO classes those that relate to chromatin remodeling processes. One of the most prominent functions of the FOS proto-oncogene is to promote cell proliferation, but it also plays a role in other processes like cell differentiation mediating some signal responses. On the other side, NF-Y has been suggested to be a master regulator of cell cycle progression, recruiting p300 to cell cycle regulatory genes . As mentIn a study from Lok et al.  we foundIn human colorectal cancer cells it was shown that the transcription factor SOX9 binds to some cell cycle regulatory genes as a cofactor of NF-Y through the CCAAT motif . This exThe intersection of FOS and NF-Y ChIP-seq regions were reported for the cell line K562 , 18. DolAs discussed in the paper from Mercer and Mattick  we belieIn this study we propose a novel regulatory function of the transcription factor NF-Y in gene-proximal regions co-localized with the transcription factor c-Fos. These NF-Y binding sites are found in a specific CCAAT dimer configuration around a distance value of 31 bp, accompanied by a series of progressively decreasing maxima at every 10-11 bp in addition. More generally, our study shows how versatile direct and indirect transcription factor occupancy in ChIP-seq regions may be. A regulatory region is bound by a number of TFs and only a subset of these factor can be found on the sequence level. This novel regulatory module introduce an additional level of complexity: the explicit missing of a transcription factor binding sites. We demonstrate that this level can be used to differentiate between direct or cis-regulatory influence in comparison to trans-regulatory (protein-protein interaction) effects.All data sets used in this study were taken from the ENCODE project  and perfWe classified the corresponding ENCODE ChIP- or DNase-seq data into distal or proximal regions depending on their genomic annotations: if an experimentally identified genomic interval was overlapping the minus 1000 bp region (-1kb) upstream of a RefSeq annotated transcription start site (TSS), including the first exon, we defined this interval as a proximal region. Each interval, which did not overlap the corresponding -1 kb upstream region or its related transcription unit was defined as a distal region. For the RefSeq data we used the UCSC genome browser provided download (05/14/2014). Both the ENCODE ChIP-/DNase-seq data and the RefSeq annotation used here were based on GRCh37 (hg19) reference genome annotation.We used the TRANSFAC library version 2013.3) together with the MATCH algorithm (Version 9.0) to analyze the different high-throughput data sets. We made use of all vertebrate matrices in this profile, which were altogether 2176 PWWs. For all matrices in this library we chose a matrix similarity score (MSS) threshold of 0.5. The core similarity score (CSS) threshold was set to 0 (for details see references 13.3 toge).We developed a workflow to analyze experimentally determined regulatory sequence sets with PWMs stored in the TRANSFAC database. For each ChIP-seq data set under study, we removed all overlapping intervals from the DNase-seq data set of the same cell line and used the remaining genomic intervals as specific control set. We received four distinct cell type specific data sets: Two ChIP-seq data sets for c-Fos and NF-YB, resp., and two DNase-seq data sets as control for the c-Fos or the NF-YB set. We counted each ChIP-seq interval as a true positive (TP), when it contained at least one PWM match above the set threshold, otherwise it was classified as a false negative (FN). Likewise each DNase-seq region with at least one PWM match above the chosen threshold was counted as a false positive (FP), otherwise as a true negative (TN). For each of the PWMs we monitored TP, TN, FP and FN at gradually decreasing thresholds from the highest score (1.0) to 0.5. To determine the performance of a PWM, we made use of the classical receiver operator characteristic (ROC) curves by plotting the true positive rate  were not separately considered.For the distance analysis between putative enhancer regions  and their proximal or putative promoter regions, we also calculated an edge-to-edge distance. For each promoter region we determined all available upstream enhancer regions with the same chromosomal annotation. For all possible upstream regions we calculated the distance by subtracting the enhancer end position from the start position of the corresponding promoter region. Correspondingly, we subtracted all start positions of all downstream located enhancers from the same chromosome from the end position of the closest promoter element. From all the distances we determined the closest enhancer, either up- or downstream, for each promoter region. The distance is calculated from the first C of the first CCAAT to the first C of the second CCAAT box.Proximal unified ChIP-seq intervals were submitted to the GREAT web service . We choshttp://www.hgdownload.cse.ucsc.edu/goldenPath/hg19/database/rmsk.txt.gz). We filter this file for all Long Terminal Repeat (LTRs) elements which resulted in 717,656 different LTR regions.The repeating elements identified by RepeatMasker  are downhttp://hgdownload.cse.ucsc.edu/goldenPath/hg19/database/wgEncodeRegTfbsClusteredV3.txt.gz). Totally this file contains 138,836 p300 interfering regions.We identified p300 interfering regions using the ENCODE Transcription Factor Binding Track cluster Table Browser tool collection .S1 Figc-Fos ChIP-seq data sets obtained from HUVEC (black curves), HeLa S3 (green), K562 (red) and GM12878 cells (blue) were analyzed with the TRANSFAC matrix V$JUNDM2_04 (M02876), using non-overlapping sets of DNase I hypersensitive sites from the same cell lines as control. Top inset: Logo plot representing the AP-1 motif detected by matrix V$JUNDM2_04 (top); bottom inset: Plot of Matthews correlation coefficient (MCC) against the applied threshold of the matrix similarity score (MSS) calculated by the Match program. The vertical line together with the yellow circle point to the MSS threshold used for detecting potential AP-1 sites in the further analyses. (A) Results for distal, (B) for proximal regions.(TIF)Click here for additional data file.S2 Figc-Fos ChIP-seq data sets obtained from HUVEC (black curves), HeLa S3 (green), K562 (red) and GM12878 cells (blue) were analyzed with the TRANSFAC matrix V$NFY_01 (M00287), using non-overlapping sets of DNase I hypersensitive sites from the same cell lines as control. Top inset: Logo plot representing the NF-Y binding motif detected by matrix V$NFY_01 (top); bottom inset: Plot of Matthews correlation coefficient (MCC) against the applied threshold of the matrix similarity score (MSS) calculated by the Match program. The vertical line together with the yellow circle point to the MSS threshold used for detecting potential AP-1 sites in the further analyses. (A) Results for distal, (B) for proximal regions.(TIF)Click here for additional data file.S3 FigTop five enriched motif for three different proximal (P1-P3) and distal (E1-E3) sample sets are shown. The used sample size was set to 657 Click here for additional data file.S4 FigTop five enriched motif for proximal (P) and distal (E1-E3) sample sets are shown. The used sample size was set to 657 Click here for additional data file.S5 FigTop five enriched motif for proximal (P1-P3) and distal (E1-E3) sample sets are shown. The used sample size was set to 657 Click here for additional data file.S6 FigTop five enriched motif for proximal (P1-P3) and distal (E) sample sets are shown. The used sample size was set to 657 Click here for additional data file.S7 FigMotif discovery using MEME confirmed the predominant role of AP-1 consensus motifs in these c-Fos sequences.(TIF)Click here for additional data file.S8 FigProximal regions interacting with both c-Fos and NF-YB show significant shorter distance relations to c-Fos(only) bound distal regions (left) compared to NF-YB(only) bound distal regions (right).(TIF)Click here for additional data file.S1 TableShown are the number of genomic intervals bound by c-Fos or NF-YB in the indicated cell lines, retrieved from the corresponding data sets of the ENCODE repository. For the HUVEC cell lines no NF-YB ChIP-seq data is available (NA).(TIF)Click here for additional data file.S2 TableThe top 20 significantly enriched gene ontology biological process categories for proximal c-Fos and NF-YB co-localizing ChIP-seq regions are shown. 1724 proximal genomic intervals were analyzed (see (TIF)Click here for additional data file.S3 TableThe top 20 significantly enriched gene ontology biological process categories for c-Fos and NF-YB co-localizing ChIP-seq regions which contain at least one CCAAT dimer repeat were used as input set. 869 genomic intervals were analyzed (see (TIF)Click here for additional data file.S4 TableThe top 20 significantly enriched gene ontology biological process categories for c-Fos and NF-YB co-localizing ChIP-seq regions which contain at least one CCAAT dimer repeat and are overlapping with ENCODE derived p300 ChIP-seq intervals were used as input set. 471 genomic intervals were analyzed (see (TIF)Click here for additional data file.S1 File(BED)Click here for additional data file.S2 File(BED)Click here for additional data file.S3 File(BED)Click here for additional data file.S4 File(BED)Click here for additional data file.S5 File(BED)Click here for additional data file.S6 File(BED)Click here for additional data file.S7 File(BED)Click here for additional data file.S8 File(BED)Click here for additional data file.


Further investigation indicated that 186 SNVs (15 promoters) are predicted to alter transcription factor binding. In addition, 62 SNVs created, removed or altered the placement of a CpG dinucleotide in 13 of the proximal promoters, 53 of which overlapped putative transcription factor binding sites. These 53 SNVs are also our top candidates for future studies aimed at examining the effects of alcohol on epigenetic gene regulation.Maternal alcohol consumption inflicts a multitude of phenotypic consequences that range from undetectable changes to severe dysmorphology. Using tightly controlled murine studies that deliver precise amounts of alcohol at discrete developmental stages, our group and other labs demonstrated in prior studies that the C57BL/6 and DBA/2 inbred mouse strains display differential susceptibility to the teratogenic effects of alcohol. Since the phenotypic diversity extends beyond the amount, dosage and timing of alcohol exposure, it is likely that an individual's genetic background contributes to the phenotypic spectrum. To identify the genomic signatures associated with these observed differences in alcohol-induced dysmorphology, we conducted a microarray-based transcriptome study that also interrogated the genomic signatures between these two lines based on genetic background and alcohol exposure. This approach is called a gene x environment (GxE) analysis; one example of a GxE interaction would be a gene whose expression level increases in C57BL/6, but decreases in DBA/2 embryos, following alcohol exposure. We identified 35 candidate genes exhibiting GxE interactions. To identify  Women who drink during pregnancy place their unborn children at risk of acquiring clinical features of fetal alcohol syndrome (FAS) or fetal alcohol spectrum disorder (FASD). FASD encompasses all patients displaying some of the clinical features of fetal alcohol exposure and is much more prevalent than FAS. These syndromes comprise an array of phenotypes that include: cognitive deficits, intrauterine and post-natal growth retardation, memory deficits, poor motor skills, facial dysmorphology and social/behavioral problems. On one end of the spectrum , children present with mild to moderate mental deficits that are difficult to diagnose by appearance, while those on the other end  exhibit a readily identifiable facial dysmorphology coupled with a complement of severe neuropsychological sequelae and neurobehavioral deficits Abel, .ADH1B, can lead to varying teratogenic outcomes in different ethnic groups  approach to identify transcripts that were affected by both genetic background  and alcohol exposure  to identify genes that are candidates for the morphological diversity between the these two inbred strains following exposure of equimolar ratios of alcohol in cultured embryos. Since the GxE approach identifies differentially expressed genes that are candidates for mediating the interaction, we then sought to uncover underlying single nucleotide variants (SNVs) in cis-regulatory elements within the proximal promoters of these candidate genes. SNVs within the promoters are excellent candidates for regulating expression of the nearby altered genes, as regulatory SNVs can alter the location and function of enhancers and promoters , these studies would identify underlying genetic differences between C57BL/6 and DBA/2 that contribute to the observed differential vulnerability to the teratogenic effects of alcohol. Furthermore, we proposed that polymorphisms between C57BL/6 and DBA/2 in regulatory elements and other factors that influence RNA expression are responsible for much of these morphological differences. We used a two-pronged approach that takes advantage of the strain-specific genomic signatures and gene expression profiles to identify candidate http://jaxmice.jax.org/strain/000664.html) and DBA/2J (http://jaxmice.jax.org/strain/000671.html) lines created at The Jackson Laboratories . The C57BL/6NJ (http://jaxmice.jax.org/strain/005304.html) sub-line consists of embryos that were frozen at the NIH in 1997 and sent back to the Jackson Laboratory in 2005. The Jackson Laboratory thawed this line, expanded it and froze it down immediately. New stock animals are continually thawed to maintain the genetic integrity of the C57BL/6NJ sub-line. CC Little started inbreeding DBA/2 mice in 1909, and DBA/2J animals have been maintained continuously at The Jackson Laboratories. A sub-line (DBA/2N) was sent to the NIH in 1951 (at generation F34). Harlan later acquired this line, designated DBA/2NHsd .The Harlan strains used in the microarray study (C57BL/6NHsd and DBA/2NHsd), as well as the lines used to identify the potential regulatory SNVs (C57BL/6NJ and DBA/2J), descended from the original C57BL/6J  and are in accordance with the guidelines of the Institutional Animal Care and Use Committee of the National Institute on Drug Abuse, National Institutes of Health, and the Guide for the Care and Use of Laboratory Animals  were incubated in 20 mL of medium, consisting of 70% immediately centrifuged heat-inactivated rat serum and 30% phosphate buffered saline supplemented with 20 units/ml penicillin and 20 units/ml streptomycin . Culture bottles were gassed for 2 h with 5% O2, 5% CO2 and 90% N2 in a rotating culture system . After a 1–2 h acclimation period, a 6 h treatment was initiated by incubating embryos in fresh medium with or without 88 mM ethanol in isotonic buffer. After the 6-h alcohol treatment, all embryos were transferred to alcohol-free culture media for 15–16 h, for a total of 24 h in culture. The 6 h exposure allows a precise delineation of the developmental time period in which various teratogenic effects can be induced, which facilitates a rigorous examination of the temporal windows of vulnerability  8.25 (when culture initiated), +1 day in culture ; E8.25 + 1 is analogous to an embryo examined at E9.0. We observed several morphological changes in the embryos, which are analogous to those observed at the later time points , further dissection of parts of the head or brain would not yield enough tissue for microarray studies. The head of each embryo was dissected above the otic vesicle, immediately immersed in 0.7 ml TRIzol  and homogenized to extract total RNA for RT-PCR and microarray studies. Total RNA was isolated from 36 individual embryos  as previously described  for each treatment were extracted using the Affymetrix Microarray Suite 5.0 (MAS5) algorithm. Data for both experiments have been deposited in GEO/NCBI and have been assigned series accession number GSE9545 and sample numbers GSM241642 through GSM241660. To minimize false positive results, only genes detected  on at least half of all individual arrays in at least one experimental condition were retained for further analysis. This avoids data that primarily represent noise  for both C57BL/6NJ (http://www.ebi.ac.uk/ena/data/view/ERS076384&display=html) and DBA/2J (http://www.ebi.ac.uk/ena/data/view/ERS075663&display=html) onto release 66 of the M. musculus genome from Ensemble (http://www.ensembl.org) using CLC Genomics Workbench V4.7 (http://www.clcbio.com). We then called SNVs using the quality based variant detection tool with the neighborhood radius set to 5, maximum gap and mismatch count set to 2, minimum neighborhood quality of PHRED 15, and minimum central quality of PHRED 20. Variants in non-specific regions were ignored. Across all reads, a minimum variant frequency greater than 10% was required.We remapped the recently established genomic sequence available at the European Nucleotide Archive , genetic background (C57BL/6NHsd or DBA/2NHsd) and alcohol exposure (88 mm EtOH or vehicle) in six groups as indicated in the experimental design above. Five embryos from each category were used for microarray studies. Since there were no control animals with the neural tube open morphology, all NTO studies used the control-NTC animals for comparison.http://media.affymetrix.com/support/technical/technotes/plier_technote.pdf). The PLIER method produces a more accurate probe set signal by employing feature responses to interpret intensity data, dynamic weighting by empirical feature performance, and handling error appropriately across low and high target abundance. The results from the PLIER analysis were variance stabilized using log2 transformation and analyzed by gene for significant differences using a 2 factor analysis of variance adjusted for multiple testing with a false discover rate of 5%  method. According to the Affymetrix manual   for the genomic analyses. To define potential SNVs driving the differential phenotype following alcohol exposure, we cataloged all SNVs between C57BL/6NJ and DBA/2J located within 5 kb upstream of the transcriptional start site(s) of each candidate gene. To define a SNV, we calculated the difference in allele frequency for the same allele between C57BL/6NJ and DBA/2J, and concentrated on alleles driven to opposite fixation. SNVs were defined as alleles that were fixed at ≥0.90 . To identify putative transcription factor binding sites, we retrieved 20 bp of flanking sequence  from the NCBI37/mm9 mouse genome assembly, and put the sequence into PROMO  (0.0324) × 35,561 = 75. We observed about 12 times that number.We first compared gene expression profiles between all C57BL/6NHsd and all DBA/2NHsd cultured embryos without taking alcohol exposure into consideration. We combined all C57BL/6NHsd embryos with an NTC morphology, which included those exposed and not exposed to alcohol, and compared them to the DBA/2NHsd embryos with a NTC phenotype, including those exposed and not exposed to alcohol. We repeated this study with embryos displaying NTO. However, in this analysis, the controls had a NTC phenotype, as none of the control animals displayed an NTO morphology. This analysis was used to determine the subset of genes that are differentially expressed between the two lines. Using a false discovery rate (FDR) of 5% , Chrnb1 ; neural transcription factors and homeobox genes, e.g., Nkx1-2 , Igf1 (insulin-like growth factor 1), Gbx2 (gastrulation brain homeobox 2), Sox21 (SRY (sex determining region Y)-box 21); epigenetic components, e.g., Hist1h2ab , Setd7 (SET domain containing lysine methyltransferase 7); heat shock proteins, e.g., Dnajc13, Dnajc21 DnaJ (Hsp40) homolog, subfamily C, member 13 and 21; genes involved in apoptosis, e.g., Bnip3l (BCL2/adenovirus E1B interacting protein 3-like), Gadd45gip1 , E2f5 (E2F transcription factor 5); and structural proteins, Bean1 , Tuba3a , Optc (opticin).Many genes in this cohort are key to the development of the nervous system including: channel proteins and receptors, e.g., www.ingenuity.com) of this set of 904 genes found in both the NTC and NTO experiments indicates that the most significant pathways are: inflammatory response; cell death and survival; energy production; lipid metabolism; embryonic development; and cancer, hematological disease. We picked three networks as examples. The genes delineating these networks are listed in Table Furthermore, Ingenuity Pathway Analysis  interaction). We compared the ethanol-treated animals with a NTC subtype from each genotype to their respective NTC controls. However, since none of the control animals had an NTO phenotype, NTC embryos from the same strain were used as a control, as follows: the Control-NTC vs. Alcohol-NTC group and the Control-NTO vs. Alcohol-NTO group. Accepting an FDR of 5%, we identified 35 candidates that demonstrate a GxE interaction; 22 were in the NTC subtype and 13 were in the NTO subtype Figures . IPA stuEya2 [eyes absent 2 homolog (drosophila)] expression changes from an average of 7.26 ± 0.045 in control C57BL/6NHsd embryos to 7.52 ± 0.004 in ethanol-treated embryos. Conversely, control DBA/2NHsd embryos show an expression value of 7.63 ± 0.007, which drops to 7.40 ± 0.04 following incubation in alcohol  showed strong GxE interactions  showed weak GxE interactions  showed strong GxE interactions and two (Pkm2 and Vipr1) showed weak GxE interactions  to a strain that is more distantly related . A hallmark of biased expression would be a consistent observation of decreased signal from the DBA/2NHsd animals in transcripts harboring SNVs in the probe-sets. In Figure s Figure , and Pkms Figure , are expEya2, Csmd3, Mcat, Tac2, Vps51, Apold1, Leo1, Psme4, Vipr1, Fam174b, Megab18, Pdxp, Rpl36a, Tspan2, Zfp157, and Snord38a  between C57BL/6 and DBA/2 using a genomics approach. However, the strains used for the microarray study (C57BL/6NHsd and DBA/2NHsd) were raised at Harlan and have not been added to the mouse sequence database. The closest matches in the mouse database are C57BL/6NJ  between C57BL/6NJ and DBA/2NJ within the three promoters  binding sites. For example, there are no predicted TF binding sites at SNVs 1, 4, 7, 10, 13, 14, and 16 in the C57BL/6NJ allele, while SNVs 4, 7, 10, 13, and 16 are predicted to contain one or more TF binding sites in the DBA/2J allele. Given the potential for these SNVs to function not only in a genetic manner, but also epigenetically through alterations in DNA methylation, we report that 5 of the 21 SNVs within the three promoters of Eya2 change a CpG dinucleotide. Four of these  lead to the loss of a CpG dinucleotide in the DBA/2J background. Examination of putative TF binding sites in these four SNVs shows that there are fewer potential TF binding sites in the C57BL/6NJ allele compared to the DBA/2J allele. Eya2 shows increased expression in C57BL/6NHsd embryos following alcohol treatment, while the DBA/2NHsd animals exhibit a decrease in expression following alcohol exposure. This would be consistent with increased TF binding in C57BL/6NHsd embryos compared to DBA/2NHsd cultures, and provides a putative mechanism for the GxE interactions.Sixteen of the twenty-one SNVs identified in the three promoters of Apold1 (Apolipoprotein L domain containing 1), Leo1 (Paf1/RNA Polymerase II Complex Component), Psme4 (Proteasome Activator Subunit 4) and Snord38a   Table . Apold1 de novo creation of a CpG site and 2 (3%) changed the position of a CpG site . In addition, the vast majority of SNVs that alter a CpG site [53/62 (85%)] are associated with potential additions, losses and/or substitutions in TF binding sites, indicating that both genetic (SNVs) and epigenetic (CpG methylation) could be implicated in the GxE interactions.A summary of the putative regulatory implications of these 241 SNVs is found in Table http://phenome.jax.org/db/q?rtn=strains/search&compare2=1). We discovered that there are 119590 SNVs between C57BL/6NHsd and C57BL/6NJ, which given a genome of ~ 2.7 × 109 bp, corresponds to a mutation frequency of 4.4 × 10−5 mutations/bp, or one SNV in every ~22,500 bp. In this study, we analyzed 5000 bp from 18 promoters of 16 genes, including three promoters for Eya2. This totals 90,000 bp of sequence. Given a mutation frequency of 4.4 × 10−5, we would expect to find four SNVs that could be attributed to background alterations between C57BL/6NHsd and C57BL/6NJ in our sample. Although we need to estimate the background mutation frequency between DBA/2NHsd (expression studies) and DBA/2NJ , the DBA/2NHsd line has not been sequenced nor has it been included in any of the available SNP chip repositories. Therefore, we assumed a similar mutation frequency between the two DBA/2 lines . Taking these numbers as an estimate, we would expect to find eight total SNVs (four for the C57BL/6 lines and four for the DBA/2 lines) that could be due within sub-line mutations. However, we found 241 SNVs between C57BL/6NJ and DBA/2J in this study, which corresponds to a mutation frequency of 2.7 × 10−3 mutations/bp, indicating that likelihood of seeing a GxE interaction due to false positives (~0.033) falls within a 0.05 confidence interval.To better understand the genetic variability between the C57BL/6 sub-strains used for gene expression studies (C57BL/6NHsd) and SNV analysis (C57BL/6NJ), we used the SNV Data from the Broad Institute (Broad2) to identify SNVs between C57BL/6NHsd and C57BL/6NJ in the “Compare Two or More Strains” option from the Mouse Phenome Database  Are differentially expressed in response to alcohol treatment during neurulation; and (2) Demonstrate a genetic interaction between two strains of mice (C57BL/6 and DBA/2) that respond very differently to prenatal alcohol exposure. While C57BL/6 animals are highly sensitive to the teratogenic effects of alcohol, DBA/2 animals are remarkably resistant, as shown by studies using gavage feeding , as they can mediate neural progenitor cell fate determination and neural tube patterning. The potassium channel (Kcnmb1) and cholinergic receptor (Chnb1) genes can mediate timely signal transduction during neural differentiation, while Hist1h2ab and Setd7 have the potential to differentially affect the epigenetic response of the developing brain cells to environmental assaults, including alcohol. The apoptosis, cell cycle and heat shock proteins act to influence cell number, and could contribute to neural tube deficits between the two lines.These comparative expression studies reveal a cohort of ~1400 genes that are preferentially expressed in either the C57BL/6NHsd or DBA/2NHsd strains during the beginning stages of neurulation. These genes may represent a first tier contribution to either protect (DBA/2NHsd) or increase (C57BL/6NHsd) the vulnerability of the embryo to the effects of alcohol exposure. Because this set of transcripts does not take alcohol exposure into consideration , it represents the cohort of transcripts that differ between these two strains in two independent experiments. Genes of particular interest are the neural transcription factor and homeobox genes  and open neural tube (NTO) embryonic subtypes were analyzed independently, with an FDR of 5% as the cut off. These differentially expressed genes potentially network to alter inflammatory response, cell death and survival, energy production, embryonic development and hematopoiesis between the two inbred lines. This cohort of differentially expressed transcripts likely results from combinations of factors including genetic background, innate programming, reactivation of transposable elements and epigenetic inheritance and responses. Since this study was conducted on embryonic cultures, it eliminates maternal elements  that would have normally acted during this critical developmental window. However, since we analyzed whole brains, we were not able to assess tissue-specificity or cell-specific differences in gene expression, and it is plausible that we missed rare transcripts with large effects or primary cell-specific transcripts that are driving the genetic differences in the sensitivity of these two inbred strains to alcohol exposure. Therefore, it is likely that our results are an under-representation of the total number of genes that are differentially expressed between these two lines.Eya2)       . With an FDR of 5%, we identified 35 genes that exhibited GxE interactions, as measured by an inverse correlation in gene expression (based on genotype) in response to alcohol. Examination of potential mechanisms for GxE interactions indicates that 16 genes have SNVs in their proximal promoters. Several of these 16 candidates are strongly associated with brain and cranial development, including preplacedal ectoderm differentiation , for a total of 241 SNVs within 90,000 bp of promoter sequence. The majority of SNVs  altered the genomic DNA in a way that led to the predicted addition or subtraction or a potential transcription factor binding site, indicating that these underlying genetic differences could play significant roles in the differential phenotypes we detected in this study. In addition, ~25% (62/241) of the SNVs have the potential to affect DNA methylation by either creating or eliminating a CpG dinucleotide. Since DNA methylation is affected by alcohol exposure  Ramsay,  and epig Ramsay, , the undin utero alcohol exposure. Exploration of the genetic and environmental factors led us to a cohort of 35 genes subject to GxE interactions; these genes represent the best candidates for driving the downstream morphological changes observed following alcohol exposure. Examination of potential regulatory SNVs associated with these 35 candidates indicates that the differences between the C57BL/6 and DBA/2 inbred strains could be due to a variety of factors, including binding of cis-acting elements , expression of trans-acting factors, epigenetic events, evolutionary consequences and combinations of these different factors.By using a multi-pronged approach in two separate experiments , we captured over 900 genes that have the potential to contribute to the cascade that leads to differential dysmorphology in embyros from the two genetically contrasting lines. These first tier genes are good candidates for further understanding the phenotypic variability associated with These experiments lay the groundwork for future studies aimed at testing the causality of these different SNVs. Although a seemingly daunting task, with emerging genome modification tools, such as zinc finger, TALEN and CRISPR modification systems (Gaj et al., The Guest Associate Editor Stephen Bruce Mason declares that, despite being affiliated to the same Institution as authors Feng C. Zhou and Chiao-Ling Lo, the review process was handled objectively. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Abf1-regulated genes in the budding yeast Saccharomyces cerevisiae are undiminished even after Abf1 has dissociated from its regulatory sites. Here we provide additional support for this effect and investigate its molecular basis. We show that the effect is observed in a distinct abf1 ts mutant from that used in earlier studies, demonstrating that it is robust, and use chromatin immunoprecipitation to show that Abf1 association is decreased similarly from memory effect and transcriptionally responsive genes at the restrictive temperature. We also demonstrate that the association of TATA-binding protein and Pol II decreases after the loss of Abf1 binding for transcriptionally responsive genes but not for memory effect genes. Examination of genome-wide nucleosome occupancy data reveals that although transcriptionally responsive genes exhibit increased nucleosome occupancy in abf1 ts yeast, the promoter regions of memory effect targets show no change in abf1 ts mutants, maintaining an open chromatin conformation even after Abf1 eviction. This contrasting behavior reflects different inherent propensity for nucleosome formation between the two classes, driven by the presence of A/T-rich sequences upstream of the Abf1 site in memory effect gene promoters. These sequence-based differences show conservation in closely related fungi and also correlate with different gene expression noise, suggesting a physiological basis for greater access to “memory effect” promoter regions. Thus, our results establish a conserved mechanism underlying a transcriptional memory effect whereby sequences surrounding Abf1 binding sequences affect local nucleosome occupancy following loss of Abf1 binding. Furthermore, these findings demonstrate that sequence-based differences in the propensity for nucleosome occupancy can influence the transcriptional response of genes to an altered regulatory signal.Previous studies have described a transcriptional “memory effect,” whereby transcript levels of many  Abf1 is an essential, abundant general regulatory factor found in Saccharomyces cerevisiae and conserved in other fungi , diluted to OD600= 0.3−0.5 and allowed to grow for 2 hr at the permissive temperature (25°). Culture density was measured to ensure doubling, and cultures were shifted to the restrictive temperature (37°) by adding prewarmed media and incubated at 37° for 60 min. All other cultures were grown to mid-log phase (OD600 = 0.6-1.2), diluted to OD600= 0.3-0.5 and allowed to grow for 2 hr at 30°.Yeast strains are listed in ing site . Yeast cAbf1 , αTBP , and αRpb3 . Bar-coded libraries for ChIP-seq were prepared as recently described  and log2 values were generated for each ratio. The mean and variance of log2 ratios were calculated across the genome and normalized to N for every base pair to yield Z-scores. Peaks were identified using MACS (P < 10−3)  and the two classes of targets are for the most part well demarcated. Memory effect targets showed little change in expression in both the abf1-1 ts and abf1-101 ts strains, whereas the transcriptionally responsive targets showed on average a twofold decrease in expression in both backgrounds. We further validated the differing behavior of memory effect and transcriptionally responsive genes by comparing transcript levels for two genes belonging to each category in wild type and abf1-101 ts yeast after 1 hr at 37°  or no (RPN8) decrease in mRNA level in abf1-101 ts yeast  behaved similarly; however, we show below that RPL3 transcription does not depend on its Abf1 binding site. Transcript levels of IPP1 decreased about threefold in the abf1-101 ts strain in this experiment, and ARO3 transcript levels decreased approximately 1.6-fold. Although these decreases are somewhat less than seen in the experiment of rpb1-1 yeast). These results indicate that the continued expression of these Abf1 targets is not due to transcript stability.The distinct behavior of memory effect and transcriptionally responsive genes could be caused by differential transcript stability. To examine this possibility, we compared mRNA half-lives, as measured in a recent study in which a thiourea labeling protocol was used in a pulse-chase experiment  binding to memory effect and transcriptionally responsive genes using the CERES web tool . Furthermore, the average number of non-Abf1 TF binding sites within 500 bp of the starting ATG was very similar for the two classes, with memory effect genes averaging 1.5 TF binding sites/promoter and transcriptionally responsive genes averaging 1.24 TF binding sites/promoter. It therefore seems unlikely that other TFs make an important contribution to the distinction between memory effect and transcriptionally responsive promoters.Many yeast promoters bind multiple transcription factors. This could lead to redundancy in transcriptional activation, such that putative “memory effect” genes do not depend on Abf1 dependence would be to mutate promoter binding sites and examine the effect on transcript levels. Previous work has demonstrated the need for the Abf1 binding site at the promoter region of selected memory effect targets. Mutation of Abf1 binding sites at the RPL3, QCR8, RPS28A, HIS7, and ADE5,7 promoters in plasmid-borne reporter constructs resulted in strongly decreased expression, whereas chromosomal mutations at the Abf1 binding site in the promoter of the memory effect gene TOM6 resulted in a decrease in TOM6 expression  using a criterion of motif conservation within two standard deviations of the motif average, whereas 29 of 69 transcriptionally responsive promoters with unique Abf1 binding sites showed equivalent conservation. Abf1 sites in memory effect genes therefore do not appear to be less functionally important, based on evolutionary conservation, than those sites in transcriptionally responsive genes. Taken together, data from previous site mutation experiments and those shown here, together with information on evolutionary conservation, indicate that the memory effect is not likely explained by Abf1 being unimportant for transcriptional activity at these promoters.As an additional test for the functional importance of Abf1 targets is that loss of Abf1 binding occurs differentially in these two classes in abf1 ts yeast. Abf1 binding motifs in the promoters of these two classes were indistinguishable, making this seem less likely , and the decrease in Abf1 enrichment at memory effect targets such as RPN8 and CNB1 confirms that transcript levels remain high in spite of Abf1 dissociating from its binding site at genes (at least some) that depend on their Abf1 binding site for normal levels of transcription  and RNA Polymerase II (Rpb3 subunit), was examined by ChIP-Seq in wild type and abf1ts yeast after 1 hr at 37°. As expected, TBP association was observed at promoters of both memory effect and transcriptionally responsive promoters  of Abf1-regulated targets decreased in abf1-101 ts yeast, while virtually no change was seen at memory effect genes . These results suggest that open chromatin structure that persists in the promoter regions of the Abf1 memory effect genes after dissociation of Abf1 may allow the general transcription machinery continued access to the transcription start site, resulting in persistent expression.Chromatin structure of promoter regions can affect transcriptional activity, as a more open chromatin structure can allow increased access to activators and general TFs, thus facilitating transcription . To testpe yeast  .We next asked what might cause the maintenance of low nucleosome occupancy observed at memory effect genes in Abf1 binding site of memory effect and transcriptionally responsive promoters; this could result in a greater tendency for one class than the other  to be occupied by a nucleosome after loss of Abf1 binding. Previous work from the Widom and Segal labs measured nucleosome occupancy obtained upon packaging yeast genomic DNA into nucleosomes in vitro, and then developed an algorithm based on the results to predict relative nucleosome-forming propensity based on DNA sequence , which are relatively unfavorable for nucleosome formation and can affect transcription of the associated gene, and which also have been shown to cooperate with Abf1 in transcriptional activation  . These results strongly suggest that the differential response of memory effect and transcriptionally responsive promoters to loss of Abf1 binding is due at least in part to memory effect promoters showing a reduced propensity, based on DNA sequence, to form a closed chromatin structure upon loss of Abf1 binding in abf1 ts yeast.We then asked whether the propensity to form nucleosomes might differ in the vicinity of the ng sites . Memory gure S2) . This efAbf1 target genes are nonphysiological, in that they are observed using abf1 ts yeast. Therefore, to determine whether the observed differences in promoter type are physiologically significant, we examined DNA sequences of promoters of genes homologous to these two classes for nucleosome-forming propensity in four additional yeast species, S. paradoxus, S. mikatae, S. kudriavzevii, and S. bayanus. Similar to the results observed in S. cerevisiae, three of the four yeast species have increased levels of dA/dT upstream of the Abf1 binding site in the promoters of memory effect genes as compared to the promoters of transcriptionally responsive genes  which is higher than other depleted proximal nucleosome promoters  at the promoters of Abf1 memory effect targets could contribute to modest retention of Abf1 in the ts mutant at these loci. With weaker competition between Abf1 and the histone proteins, Abf1 is not evicted as efficiently.Although our ChIP-seq results showed that ts yeast , there iAbf1 function cannot progress through G1 into S phase (Abf1 target genes by swapping sequences upstream of the Abf1 binding site did not succeed in clearly changing transcriptional response to loss of Abf1 binding in abf1 ts yeast. Thus, although sequence-directed differences in propensity for nucleosome occupancy appear important for distinguishing transcriptionally responsive from memory effect genes, other factors, including sequences downstream of Abf1 binding sites, may also contribute to this effect. An alternative and likely more efficient means to dissecting the sequences that distinguish transcriptionally responsive and memory effect promoters would be to measure this effect using engineered abf1 ts mutant strains of Saccharomyces species closely related to S. cerevisiae, as this would simultaneously monitor the effect of sequence changes in hundreds of promoters (The details of how the chromatin-mediated mechanism that we have uncovered here contributes to the memory effect seen at select Abf1-dependent genes remain unclear. It is difficult to ascertain the temporal limits of the memory effect, as yeast cells deficient in


CYP19 gene encodes aromatase, which converts androgens to estrogens. CYP19 mRNA variants are transcribed mainly from three promoters. Quantitative RT-PCR was used to measure the relative amounts of each of the three transcripts and determine the on/off state of the promoters. While some of the promoters were silent, CYP19 mRNA production differed among the other promoters, whose estimated transcription levels were 0.001% to 0.1% of that of the TUBB control gene. To investigate the structural aspects of chromatin that were responsible for this wide range of activity of the CYP19 promoters, we used a fractionation protocol, designated SEVENS, which sequentially separates densely packed nucleosomes from dispersed nucleosomes. The fractional distribution of each inactive promoter showed a similar pattern to that of the repressed reference loci; the inactive regions were distributed toward lower fractions, in which closed chromatin comprising packed nucleosomes was enriched. In contrast, active CYP19 promoters were raised toward upper fractions, including dispersed nucleosomes in open chromatin. Importantly, these active promoters were moderately enriched in the upper fractions as compared to active reference loci, such as the TUBB promoter; the proportion of open chromatin appeared to be positively correlated to the promoter strength. These results, together with ectopic transcription accompanied by an increase in the proportion of open chromatin in cells treated with an H3K27me inhibitor, indicate that CYP19 mRNA could be transcribed from a promoter in which chromatin is shifted toward an open state in the equilibrium between closed and open chromatin.The human  Transcription is often defined as the first regulatable step in gene expression, and in this step a specific gene (or set of genes) is targeted within the genome. In this process, transcription factors (TFs) must bind to regulatory sequences of target genes ,2, and eCDKN1A (p21) promoter [DNA in cells is packed into chromatin, and the primary components of chromatin are nucleosomes that comprise eight histone proteins. Because this structure usually becomes an obstacle for events that occur on the DNA, the removal of nucleosomes from a promoter region must precede transcription –6. In fapromoter . Other Tpromoter . This typromoter . Converspromoter . In addipromoter ,19. Thespromoter . This fiCYP19 gene encodes aromatase, an enzyme that converts androgens to estrogens, and is expressed exclusively in a set of steroidogenic tissues [CYP19 mRNA initiates at multiple promoters that each result in a distinct mRNA consisting of a distinct noncoding first exon and common coding downstream exons. Reportedly, the promoter usage differs among cell types that express this gene [CYP19 transcripts increases along with the development of breast cancer, indicating that the transcription level could be controlled by the promoter usage [CYP19 promoters in three human cell lines in which the CYP19 gene is transcribed or not transcribed.The human  tissues . Transcrhis gene ,23. Moreer usage . Here, tCYP19 gene, the cells were harvested following culture for 3 days with 10 μM of 3-deazaneplanocin A .HepG2, JEG-3, and HeLa cells were cultured in Minimum Essential Medium with alpha modification supplemented with 10% calf serum and antibiotics. KGN cells were cultured in Dulbecco's Modified Eagle Medium: Nutrient Mixture F-12 supplemented with 10% fetal bovine serum and antibiotics. To study the contribution of H3K27me3 to transcription of the RNeasy micro spin columns (Qiagen) were used to prepare total RNA from cells. Superscript III Reverse Transcriptase and random primers (Life Technologies) were used to synthesize cDNA from total RNA; the cDNA was then purified and concentrated on a MinElute spin column (Qiagen) following treatment with RNase A plus RNase H and extraction with phenol/chloroform. For conventional PCR, 2 ng of cDNA template, which was quantified with a Quant-iT OliGreen Kit (Life Technologies), was used in each single reaction. Each PCR comprised 34 cycles  with a primer set capable of amplifying a region derived from two separate exons. Each amplicon was size-fractionated in a 4% agarose gel to determine whether it was of the correct size. For quantitative PCR, each cDNA sample diluted from 0.0004 to 10 ng was used for a single reaction. To make a standard curve for comparison between PCR signals amplified with a different primer set, serially diluted human genomic DNA  was utilized as described previously . Primer CYP19 product), #SM2222PS, Acris; mouse IgG2a isotype control, #M076-3, MBL. Alexa Fluor 488-conjugated anti-mouse IgG Fab fragment (Life Technologies) was used for the secondary antibody.Three to 8 million cells were dispersed following treatment with PBS supplemented with 0.25% trypsin. The harvested cells were then crosslinked with 3.7% formaldehyde in PBS for 10 min at 37°C and permeabilized for 30 min on ice in nine volumes of ice-cold methanol. After being washed with PBS twice, the cells were re-suspended in PBS supplemented with 2 mg/ml BSA. Finally, the cells were incubated with primary antibody for 1 hr at room temperature and then with secondary antibody for an additional 30 min at room temperature. The stained cells were analyzed by using a FACScan flow cytometry analyzer (BD). The primary antibodies were used as follows: anti-aromatase , #SM2222PS, Acris; anti-β-actin, #A1978, Sigma; anti-pan-histone H3, #ab1791, Abcam; anti-H3K27me3, #9733, Cell Signaling; anti-EZH2, #5246, Cell Signaling.The cultured cells were suspended in western lysis buffer (55 mM Tris-HCl (pH 6.8), 0.72 M 2-mercaptoethanol, 2% SDS, 0.005% bromophenol blue, and 8% glycerol) and boiled for 5 min. After centrifugation at 14,000 xg for 5 min, each supernatant was collected as a cell lysate. An EZQ Protein Quantitation Reagent (Life Technologies) was used to measure the protein concentration of each sample. Each protein sample (5 to 10 μg) was loaded onto a SDS-PAGE mini-gel; separated proteins were then blotted onto a polyvinylidene difluoride membrane (Merck Millipore). After sequential exposures to a primary antibody, a biotinylated secondary antibody , and a streptavidin-conjugated alkaline phosphatase , each membrane was developed with Western Blue (Promega). The primary antibodies were used as follows: anti-aromatase —are located in a region extending about 100 kb upstream of the protein-coding region  transcripts , while a simple peak in the histogram was seen in the other cell lines. Because the pattern of JEG-3 cells was observed even in re-cloned JEG-3 cells (data not shown), the heterogeneity could be an intrinsic property of JEG-3 cells. Therefore, HepG2 and KGN cells were utilized to reveal chromatin structure responsible for the strength of the CYP19 promoters in further experiments.We estimated the expression of the ell line . JEG-3 cCYP19 promoters, we used our recently established SEVENS assay [To explore what aspect of chromatin structure determined the strength of the NS assay . This asTUBB (β-tubulin), ACTB (β-actin), and GAPDH  as constitutively active genes; and OR1A1 (olfactory receptor type 1A1), MYT1 (myelin transcription factor 1), and IL2RA (interleukin 2 receptor α chain) as genes that are repressed in all the cell lines used in this study. The expression profile of these genes was confirmed by RT-PCR  by using the SEVENS assay  (Hg-EUS-1 to -5 in CYP19 promoters in HepG2 cells was well reflected in the chromatin proportion (open chromatin vs. closed chromatin) as determined via the SEVENS assay.We first assessed the NS assay . The disCYP19 locus in KGN cells (abbreviated as Kg) was examined in the SEVENS assay, regions with a relatively high Up/Lo ratio were evident at Kg-EUS-1 to -7  was also analyzed in the SEVENS assay . A singllue belt . A high CYP19 locus in HepG2 cells  –12. To aG2 cells . Three rTUBB promoter, suggesting that open chromatin seen at Kg-EUS-7 seems to be due to the absence of nucleosomes. Because occupancy at the other regions did not fall down to the TUBB level, nucleosomes appeared to be removed in some of the cells. Such nucleosome removal could result in a moderate proportion of open chromatin at the EUS regions, particularly at Kg-EUS-6, in a weak but significant activity of the Ic promoter.When KGN cells were subjected to the ChIP assay, four regions with low nucleosome occupancy were evident and coincided with Kg-EUS-4 to -7 . Of thesWhen the nucleosome occupancy of HeLa cells was analyzed, one region with a relatively low level of nucleosomes was observed and coincided with Hl-EUS-1 . This seAltogether, all the regions with low nucleosome occupancy were mapped to the positions of the EUS regions. Therefore, we confirmed that the proportion of nucleosome-free chromatin was directly reflected in the proportion of open chromatin judged in the SEVENS assay. However, some EUS regions were not identified as regions with a low level of nucleosomes; for example, no particular feature in nucleosome occupancy corresponded to Hg-EUS-2 or Kg-EUS-2. These discrepancies may result from the different spatial resolution achieved in an entire sheared sample in the ChIP assays vs. that achieved with a size-fractionated sample in the SEVENS assays.CYP19 gene, we examined the distribution of H3K27me3 and H3K27ac throughout the locus by using ChIP assays with an antibody that recognizes each epigenetic mark. Because the amount of nucleosomes at each assessed position of the CYP19 locus was not equal as shown in Histone H3 tri-methylated at lysine 27 (H3K27me3) is an epigenetic mark related to gene silencing, and it also accumulates at promoters with low activity . In addiMYT1 control locus, which is a target gene of a polycomb repressive complex [We first examined the distribution of H3K27me3 in HepG2 cells  is included in parentheses.The primers for RT-PCR are designed for the exons shown in parentheses. To represent the position of the primers for SEVENS and ChIP assays, the distance from the TSS (the Ia TSS for the (PDF)Click here for additional data file.S1 FigRT-PCR analyses were performed using 100 pg of cDNA as a template, which was synthesized from total RNA purified from either of the cell lines. The PCR reactions with 100 pg of genomic DNA  were also performed as a positive control (designated as “Control”). Therefore primer sets that amplify a region encoded by a single exon of the respective genes were utilized. The primers used in this study are listed in (PDF)Click here for additional data file.