ChIP-Seq of ERα and RNA polymerase II defines genes differentially responding to ligands
2009; Springer Nature; Volume: 28; Issue: 10 Linguagem: Inglês
10.1038/emboj.2009.88
ISSN1460-2075
AutoresWillem-Jan Welboren, Marc A. van Driel, Eva M. Janssen‐Megens, Simon J. van Heeringen, Fred C.G.J. Sweep, Paul N. Span, Hendrik G. Stunnenberg,
Tópico(s)RNA Research and Splicing
ResumoArticle4 April 2009free access ChIP-Seq of ERα and RNA polymerase II defines genes differentially responding to ligands Willem-Jan Welboren Willem-Jan Welboren Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Marc A van Driel Marc A van Driel Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The NetherlandsPresent address: Netherlands Bioinformatics Centre, Nijmegen, The Netherlands Search for more papers by this author Eva M Janssen-Megens Eva M Janssen-Megens Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Simon J van Heeringen Simon J van Heeringen Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Fred CGJ Sweep Fred CGJ Sweep Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands Search for more papers by this author Paul N Span Paul N Span Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands Search for more papers by this author Hendrik G Stunnenberg Corresponding Author Hendrik G Stunnenberg Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Willem-Jan Welboren Willem-Jan Welboren Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Marc A van Driel Marc A van Driel Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The NetherlandsPresent address: Netherlands Bioinformatics Centre, Nijmegen, The Netherlands Search for more papers by this author Eva M Janssen-Megens Eva M Janssen-Megens Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Simon J van Heeringen Simon J van Heeringen Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Fred CGJ Sweep Fred CGJ Sweep Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands Search for more papers by this author Paul N Span Paul N Span Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands Search for more papers by this author Hendrik G Stunnenberg Corresponding Author Hendrik G Stunnenberg Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands Search for more papers by this author Author Information Willem-Jan Welboren1, Marc A van Driel1, Eva M Janssen-Megens1, Simon J van Heeringen1, Fred CGJ Sweep2, Paul N Span2 and Hendrik G Stunnenberg 1 1Department of Molecular Biology, Faculty of Science, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands 2Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands *Corresponding author. Department of Molecular Biology, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Geert Grooteplein 26 Zuid, Nijmegen 6525GA, The Netherlands. Tel.: +31 24 36 10524; Fax: +31 24 36 10520; E-mail: [email protected] The EMBO Journal (2009)28:1418-1428https://doi.org/10.1038/emboj.2009.88 PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info We used ChIP-Seq to map ERα-binding sites and to profile changes in RNA polymerase II (RNAPII) occupancy in MCF-7 cells in response to estradiol (E2), tamoxifen or fulvestrant. We identify 10 205 high confidence ERα-binding sites in response to E2 of which 68% contain an estrogen response element (ERE) and only 7% contain a FOXA1 motif. Remarkably, 596 genes change significantly in RNAPII occupancy (59% up and 41% down) already after 1 h of E2 exposure. Although promoter proximal enrichment of RNAPII (PPEP) occurs frequently in MCF-7 cells (17%), it is only observed on a minority of E2-regulated genes (4%). Tamoxifen and fulvestrant partially reduce ERα DNA binding and prevent RNAPII loading on the promoter and coding body on E2-upregulated genes. Both ligands act differently on E2-downregulated genes: tamoxifen acts as an agonist thus downregulating these genes, whereas fulvestrant antagonizes E2-induced repression and often increases RNAPII occupancy. Furthermore, our data identify genes preferentially regulated by tamoxifen but not by E2 or fulvestrant. Thus (partial) antagonist loaded ERα acts mechanistically different on E2-activated and E2-repressed genes. Introduction Estradiol (E2) is a key regulator in the growth and differentiation of many target tissues and is involved in the development and progression of breast cancer (Anderson, 2002). Its genomic activity is to a large extent mediated by the estrogen receptor α (ERα; NR3A1), a member of the nuclear receptor super family. ERα regulates expression of target genes classically by binding directly to its cognate sequence, the estrogen response element (ERE). ERα binds to its cognate-binding sites as homodimer, recruits co-factors and activates or represses transcription in response to E2 (Shang et al, 2000). Alternatively, nonclassical regulation involves protein–protein interactions with other DNA-binding proteins such as Sp1, AP-1 and NF-κB. Identification of the ERα target gene network regulated by agonist and/or antagonist treatment is essential to understand the role of ERα in normal physiological processes and in cancer. Several gene expression profiling studies in MCF-7 cells identified E2-responsive genes in the range of 100–1500 (Charpentier et al, 2000; Coser et al, 2003; Frasor et al, 2003; Rae et al, 2005; Carroll et al, 2006; Kininis et al, 2007; Kwon et al, 2007; Lin et al, 2007; Stender et al, 2007), whereas large scale ERα ChIP profiling showed that ERα interacts with many thousands genomic regions (Carroll et al, 2006; Kininis et al, 2007; Lin et al, 2007). This discordance is in part due to the fact that mRNA levels do not necessarily reflect gene activity because it is subject to degradation and regulation, and that likely not all ERα-binding sites are active under all conditions. Genome-wide profiling of RNA polymerase II (RNAPII) occupancy, however, does provide a much more direct readout and, thus, could yield insights beyond what is typically obtained by mRNA expression profiling. Recent studies have shown that the promoters of a large number of genes are preloaded with RNAPII with minimal occupancy over the coding body, a phenomenon referred to as pausing or promoter proximal enrichment of RNAPII (PPEP). Collectively, these studies suggest that control of elongation rather than or in addition to transcription initiation has an important function in the activation of these genes, particular for genes rapidly responding to the developmental and cell signalling cues (Muse et al, 2007; Zeitlinger et al, 2007; Core et al, 2008). Selective estrogen receptor modulators (SERMs) are (partial) E2 antagonists used for the treatment and prevention of breast cancer. One of the most widely used is tamoxifen, which has mixed agonistic/antagonistic properties and tissue-specific effects. Tamoxifen resistance develops ultimately in advanced breast cancer and is of major clinical significance (Ali and Coombes, 2002). SERMs induce an alternative conformation of the ERα ligand-binding domain that results in the recruitment of different co-factors and repression of transcription instead of activation. Fulvestrant (ICI 182 780) is a full antagonist that increases protein turnover and results in the degradation of ERα. Fulvestrant is used for the treatment of advanced breast cancer and tamoxifen-resistant tumours (Howell, 2006). The effect of SERMs on ERα binding and subsequent RNAPII recruitment has not been studied at a genome-wide level. In this study, we used massive parallel sequencing of immunoprecipitated DNA fragments to identify ERα-interaction sites and RNAPII occupancy in response to E2 or the (partial) antagonists tamoxifen and fulvestrant. Combining ERα-binding site and RNAPII occupancy allowed us to measure the consequence of E2 treatment on RNAPII occupancy, that is ongoing transcription. RNAPII analyses also allowed us to assess whether PPEP is a general phenomenon in rapid E2 response. We identified a large number of ERα-interaction sites and a much smaller number of direct target genes, and show that tamoxifen and fulvestrant alter but not abolish ERα binding, and have differential effects on E2-upregulated and E2-downregulated genes. E2-mediated activation is antagonized by both compounds, whereas at E2-downregulated genes, tamoxifen shows agonistic behaviour in contrast to fulvestrant, which antagonizes E2-mediated repression. Results Identification of ER-interaction sites ChIP followed by deep sequencing was performed using the MCF-7 breast cancer cell line, which was hormone starved for 48 h and subsequently mock-treated (minus ligand) or stimulated for 1 h with 10 nM E2. The numbers of sequenced and mapped tags are shown in Supplementary Table SI. Classical ERα target genes, for example TFF1 and GREB1, showed vast enrichment of tags over a narrow range in their promoter and enhancer regions in the E2 dataset as compared with minus ligand (Figure 1A). Overlapping tags were joined into peaks and the number of tags per peak (peak scores) was counted. The frequency distribution of peak scores shows a wide range in the E2 dataset going up to nearly a 1000 tags/peak (Supplementary Figure S1). In the absence of ligand, the majority of peaks are found in the bins with lower peak scores; two high peak score bins are observed. Because substantial ERα binding is not expected in the absence of ligand, we visually inspected these genomic regions and observed local high tag densities over large areas reminiscent of copy number variation (CNV). Indeed, the outlier regions coincide with CNV as determined by arrayCGH data (Shadeo and Lam, 2006) and includes the amplified in breast cancer-1 gene (AIB1 or NCOA3) on chromosome 20. Regions with high CNV obviously compromise peak calling and were, therefore, corrected for prior to peak calling. Using an FDR of <1 × 10−4, we identified 10 205 ERα-interaction sites. ChIP-qPCR on three independent biological replicas validates the binding of ERα to randomly selected sites (20/20) (Supplementary Figure S2). The majority of the binding sites (41%) are located in introns and only a small percentage (7%) in promoter regions (Figure 1B), in good agreement with published data (Carroll et al, 2006; Lin et al, 2007). Figure 1.Overview of ERα-interaction sites. (A) ERα-binding sites at the TFF1 and GREB1 loci. The maximum number of overlapping tags, that is peak height is shown. Clear ERα peaks are detected in the promoter and enhancer region of the TFF1 and GREB1 gene on E2 treatment, whereas residual binding is observed in the absence of ligand. ERα binding is strongly decreased although not completely abolished on treatment with tamoxifen or fulvestrant compared with E2. (B) Genomic location of ERα-interaction sites. The majority of sites (41%) are located within an intron or distal from a gene (23%); 7% is located in promoter regions. (C) Comparison of large-scale ChIP profiling data. Venn diagram of the overlap of ERα-binding sites as identified in this study or reported by Lin et al and Lupien et al. 3305 and 1089 of the ChIP-Seq interaction sites are overlapping with the Lupien et al and Lin et al analysis (57 and 88%, respectively). (D) Venn diagram of the overlap between ERα-binding sites induced on E2, tamoxifen and fulvestrant treatment. The E2 and tamoxifen profile overlap to a large extent, but also contain preferential binding sites. Fulvestrant-liganded ERα interacts with a small number of sites that largely overlap with those found on E2 or tamoxifen induction. Download figure Download PowerPoint Next, we compared our 10 205 ERα-interaction sites with genome-wide profiles determined in MCF-7 cells using either a micro-array platform or ChIP-PET identifying 5782 sites and 1234 sites, respectively (Figure 1C) (Lin et al, 2007; Lupien et al, 2008). Our ChIP-Seq and the ChIP-chip datasets show a substantial overlap (57%). Including the less deeply sequenced ChIP-PET dataset, which showed a 88% overlap with the ChIP-Seq targets, we obtained 615 ERα-binding sites that are identified with all three platforms. Sites shared between all three datasets are likely to encompass high affinity sites. Indeed, our ERα-binding sites common to all three datasets had a higher average peak height (84) as compared with sites present only in our dataset (average 34). The good enrichment obtained with our ERα monoclonal antibody combined with the high accuracy, sensitivity and sequence depth achieved with the Illumina genome analyzer allowed for the identification of more transient and likely indirect interaction sites in addition to high affinity and direct DNA-binding sites. However, small variations in cells and culture conditions, that is biological variation and sample handling likely also account for some of the differences. In conclusion, our ERα-binding site analysis reveals a very large number of sites encompassing direct as well as indirect interactions sites. (Partial) antagonists affect ER binding The effect of tamoxifen and fulvestrant is hitherto only studied on a small number of genes. The prevailing view is that SERMs do facilitate DNA binding of ERα (Shang et al, 2000). We performed ChIP-Seq of ERα in MCF-7 cells treated with either tamoxifen or fulvestrant to assess whether this holds true on a genome-wide scale. A total of 8854 tamoxifen and 4284 fulvestrant-induced ERα sites are detected and representative examples of ERα binding to the TFF1 and GREB1 loci are shown (Figure 1A). Globally, the E2 and tamoxifen profiles overlap to a large extent (54%), whereas a smaller proportion of the binding sites are shared between E2 and the fulvestrant profile (33%) (Figure 1D). These data corroborate and extend the notion that ERα is able to bind to its regulatory regions in vivo when loaded with these (partial) antagonists. We note that binding is reduced or even abolished at some sites (Supplementary Figure S3). The altered DNA binding of ERα in response to fulvestrant is not due to receptor degradation (Pink and Jordan, 1996), because we did not observe a reduction of the protein levels during the 1h treatment applied in these experiments (data not shown). We conclude that ERα binding is affected, but not abolished when liganded with SERMs. Motif analysis Next, we interrogated the sequence of the binding sites for overrepresentation of DNA motifs using the MDmodule program (Liu et al, 2002). The full ERE—palindromic arrangement of half sites with a 3bp spacer—turned out to be the by far most prevalent motif (Figure 2A). Using the weight matrix generated by MDmodule and an ERscan algorithm similar to that used earlier (Smeenk et al, 2008), we find that 68% of the ERα-interaction sites contain one or more ERE (motif score cut-off of 5, FPR of 15%). A clear positive correlation can be observed between peak height and the mean of the motif scores indicating that the ERα indeed binds most strongly to sites encompassing a consensus motif (Figure 2B). Next, we screened the ERα-interaction site sequences for the presence of other motifs. In line with published data (Carroll et al, 2006), we find significant enrichment of the Sp1, C/EBP and FOXA1 (HNF3α) motifs in addition to the ERE (Supplementary Table SII). Although the FOXA1 motif is statistically enriched in our dataset (P-value <0.0001; 400 bp window), the total number of potential FOXA1 sites in our data is low (748/10 205 or 7%). We separately examined the 3251 sites that do not encompass an ERE for the enrichment of transcription factor motifs. Among others, we find the FOXA1 motif in 308 peaks (9%). Given the apparent discordance between the Lupien and co-workers and our data, we also performed a peak calling using MACS to exclude any bias based on the peak detection algorithm (Zhang et al, 2008). MACS detects 7713 peaks, that is a 75% overlap with the 10 205 sites called by FindPeaks. Motif analysis showed that the FOXA1 motif is present in 6.6% of peaks called by MACS. To further rule out that this discordance is due to the use of different weight matrices and algorithms, we directly determined the overlap (400 bp window) between our ERα-interaction sites and the 12 904 reported FOXA1-binding sites and found an overlap of 15 and 13.6% with binding sites determined by FindPeaks and MACS, respectively. Taken together, our analysis reveals the statistical enrichment of a number of sequence motifs including the FOXA1 motif, but only a minor co-occurrence of ERα and FOXA1-interaction sites was detected. Figure 2.ERE motif and correlation with peak height. (A) The weight matrix of the highly overrepresented ERE motif. (B) Correlation of peak height with ERα motif score. The mean ERE motif score was determined using ERscan. ERα-interaction sites were binned according to peak height; random genomic regions were used as background. A clear positive correlation is obtained between the height of an ERα peak and the motif score. The mean of the motif scores in the three bins is significantly different as assessed by the Mann–Whitney test, with a P-value of <0.01, indicated by a double asterisk (C) Percentage of interaction sites containing an ERE. The different binding site profiles were searched for the presence of an ERE using ERscan. The ‘E2 preferential’ group contains the highest percentage of ERE motifs as compared with the tamoxifen and fulvestrant preferential groups. Download figure Download PowerPoint On treatment of MCF-7 cells with tamoxifen and fulvestrant, we observe many ‘SERM-specific’ ERα-interaction sites (Figure 1D). The selective binding of the receptor in the presence of different ligands may be dictated by the sequence composition of the cis-acting element. Therefore, we assessed the presence of the ERE and other known transcription factor motifs in the different categories of compound-specific interaction sites as well as of sites common to all three compounds. We find that 74% of the ‘E2-specific’ interaction sites contain an ERE, whereas 36 and 39% of the tamoxifen- and fulvestrant-specific sites contain an ERE (Figure 2C). Besides the ERE, no differentially enriched transcription factor motifs could be detected. In addition, we assessed the evolutionary conservation of the ERα-binding sites. The shared as well as the compound-specific groups are significantly more conserved compared with random regions (P-value <0.01) as shown in Supplementary Figure S4. This indicates that binding sites present in MCF-7 cells are conserved between species and play a general role in the regulation by ERα. Ligand triggers rapid changes in RNAPII occupancy Our and earlier genome-wide analyses have provided a wealth of ERα-binding sites. However, assigning the target genes has remained problematic because a large proportion of the ERα-binding sites are located at great distances from genes. To more directly identify genes responding to E2 treatment (1 h), we performed ChIP-Seq using an antibody against RNAPII and determined the log2 ratio of E2/minus ligand. RNAPII occupancy throughout the gene body provides a direct readout of transcriptional activity and thus yields insights beyond what is typically achieved by mRNA expression profiling. Classical ERα target genes, such as TFF1 and GREB1, show a clear increase in RNAPII occupancy over their gene body already after 1 h exposure to E2 (Figure 3). At a global scale, RNAPII occupancy over 596 genes significantly changes in response to E2 stimulation (mean±1.5 × s.d.), with 349 genes showing an increase and 247 genes showing a decrease in RNAPII occupancy. Comparing our E2-regulated genes with mRNA expression profiles (Kininis et al, 2007; Lin et al, 2007) revealed an overlap of 64 and 47 genes, respectively. When including genes that change less then two-fold but are significant (P-value <0.05) in the Kininis dataset, the overlap increased to 195 genes. Note that with our ChIP-Seq of RNAPII occupancy and the short E2 treatment (1 h), we will only or predominantly identify direct and immediate/early responding target genes, whereas in gene expression profiling at 3 or 8 h after E2 addition delayed/late responding and indirect targets may also have been identified. Figure 3.RNA polymerase II occupancy at ERα target genes. The RNAPII occupancy is depicted for the TFF1 (top panel) and GREB1 locus (lower panel) in response to solvent (green) or E2 (red). Download figure Download PowerPoint Next, we examined E2-responsive genes for the presence of nearby ERα-interaction sites (within 50 kb). Of the 349 upregulated genes, 309 (89%) encompass 1226 ERα-interaction sites, that is 4 on average, whereas of the 247 downregulated genes, 116 (47%) encompass 192 ERα-interaction sites (1.5 on average). Besides that upregulated genes more frequently encompass ERα-binding sites than downregulated genes, the sites in upregulated genes more frequently contain an ERE that conforms better to the consensus ERE and displays a higher mean motif score (Supplementary Table SIII). Motif analysis shows that ERα-binding sites near up- and downregulated genes do not contain differentially enriched transcription factor motifs at statistically significant P-values. Gene Ontology (GO) analysis shows that E2-regulated genes are enriched for a diverse set of cellular processes and functions, including ovulation cycle process, female gonad development and female meiosis (Supplementary Table SIV). In conclusion, we show that 596 genes change in RNAPII occupancy over the gene body in response to E2, of which 59% are upregulated and 41% are downregulated. A higher number of ERα-bindings sites are present near upregulated genes compared with downregulated genes and sites near upregulated genes conform better to the ERE consensus sequence than those of nearby downregulated genes. Promoter proximal enrichment of RNAPII Recent genome-wide (ChIP-chip) studies have shown that a large fraction of the promoters of developmental and cell signalling genes as well as genes responding to external stimuli display PPEP or pausing of RNAPII, which is thought to facilitate rapid upregulation of transcription (Guenther et al, 2007; Muse et al, 2007; Zeitlinger et al, 2007). GRO-seq (global nuclear run-on-sequencing) revealed that up to 30% of genes display promoter proximal pausing (Core et al, 2008). Nuclear hormone receptors such as ERα are regulators of rapid response par excellence and hence, it seemed likely that pausing of RNAPII might be involved in the fast regulation of immediate early E2-responsive genes. Therefore, we determined the number of tags in the promoter and body of genes; in the minus ligand dataset (i.e. before induction) of the 8465 genes that are significantly enriched for RNAPII, 1228 (15%) display PPEP (Figure 4A). RNAPII enrichment in promoter regions was validated on 6/6 genes using the 8WG16 antibody (Supplementary Figure S5). Furthermore, we validated PPEP using a number of phospho-specific (phosphoserine 2, 5 and 7) and an N-terminal RNAPII antibody (N-term). The transition of RNAPII from the initiation to the elongating form can be monitored by phosphorylation of specific serine residues in the CTD. Serine 5 is phosphorylated at the initiating phase of transcription, whereas serine 2 is a mark of productive RNAPII and occurs more in the 3′ end of a gene. Serine 7 phosphorylation is a mark for elongating RNAPII (Phatnani and Greenleaf, 2006; Chapman et al, 2007). The RNAPII phosphorylation status of three genes was assessed in the absence or presence of E2 using ChIP in combination with phospho-specific antibodies. The presence of phosphoserine 5 (and surprisingly 7) combined with the absence of phosphoserine 2 shows PPEP in the presence and absence of ligand (Supplementary Figure S6). Figure 4.Promoter proximal enrichment of RNAPII (PPEP). (A) Histogram of the RNAPII occupancy ratio at promoter versus gene body. The distribution of the promoter/gene body ratio of all genes containing RNAPII (light blue) and of E2-responsive genes (red). The dashed lines represent the mean±1 × s.d. The 1228 genes display paused RNAPII of which only 21 are E2-responsive genes. (B) RNAPII occupancy profile. Genes were divided into bins relative to the transcription start site; −500 to −251, −250 to TSS, TSS to +250 and the remaining gene body was divided into four equal bins. For each group of genes, the mean number of tags per bin is plotted. E2-regulated genes on average have less RNAPII at their promoter regions as compared with the mean of all genes. Genes above the set threshold (mean+1 × s.d.) have a higher RNAPII occupancy at their promoter as compared with all genes and E2-regulated genes. Download figure Download PowerPoint Strikingly, only 21 of the 596 E2-regulated genes (4%) display PPEP. Moreover, the median RNAPII occupancy profile over E2-regulated genes in the promoter region and the coding body does not significantly deviate from that of all genes but is very significantly lower than the profile of PPEP genes (Figure 4B). Of the 64 E2-regulated genes shared between our and Kininis datasets, 8% display PPEP, a percent wise increase as compared with our entire data but still a minor fraction. (Kininis et al, 2007). Together, these results show that a large fraction of all genes, but only a very minor fraction of E2-regulated genes display PPEP in MCF-7 cells. Nevertheless, the majority of the 349 E2-upregulated genes do show a rapid and highly significant increase in RNAPII occupancy already at 1 h of E2 induction. Finally, we determined the effect of ligand administration on the 21 E2-regulated genes that display PPEP. E2 induction changes the RNAPII occupancy ratio between promoter and gene body resulting in a loss of PPEP (10/21), whereas tamoxifen and fulvestrant treatment resulted in the abolishment of RNAPII occupancy (and thus PPEP) on 21/21 genes and 15/21 genes, respectively. The observation that (partial) antagonists induce a rapid loss of RNAPII on E2-responsive promoters indicates that at large these ligands prevent the recruitment to and/or stabilization of RNAPII at the promoter and, thus, preinitiation complex (PIC) formation rather than affecting the transition of RNAPII into the elongating form. Overlapping as well as distinct groups of genes respond to (ant)agonists Given that in the majority of the cases, the binding of ERα is not abolished on (partial) antagonist treatment, we determined the effect of tamoxifen and fulvestrant on the RNAPII occupancy. On tamoxifen administration, 719 genes change in RNAPII occupancy; the majority (695/719) is downregulated as compared with the minus ligand control. Strikingly, more genes change their RNAPII occupancy on (partial) antagonist as compared with E2 treatment (596), which has also been observed in expression profiling studies (Frasor et al, 2004). On fulvestrant treatment, 319 genes change in RNAPII occupancy as compared with the minus ligand control of which 230 are downregulated. A typical example is shown in Supplementary Figure S7. Note that in mock-treated cells, the RNAPII occupancy of many ERα-regulated genes was low, but in many cases clearly enriched for RNAPII, which is likely due to incomplete ligand depletion. Collectively, the total number of genes with altered RNAPII occupancy for all three ligands is 1256. To classify genes based on their response to E2, tamoxifen and fulvestrant, we performed K-means clustering of the RNAPII ratios revealing five distinct clusters (Figure 5A and B). Using GO, we assessed whether the genes within the clusters are functionally related (Figure 5D). Supplementary Table SV shows an overview of the ERα-binding sites analysis per cluster. The changes in RNAPII occupancy in response to the various ligand treatments were validated by ChIP-qPCR on 7–8 randomly chosen examples from each cluster (Supplementary Figure S8). Next, we compared the changes in RNAPII occupancy of six genes from each cluster with the changes in the level of primary transcript and mRNA levels as measured by RT–qPCR at 0, 1, 3 and 8 h after treatment using intron-exon and exonic primer pairs, respectively. In particular, the changes in primary transcript levels (Supplementary Figure S9) and to a lesser extent of mRNA levels (Figure 5C; Supplementary Figure S10) of genes in clusters 2, 3 and 4 correlate very well to the changes in RNAPII occupancy in response to the various ligands as determined by ChIP-Seq. Figure 5.Cluster analysis based on changes in RNAPII occupancy. (A) The 1256 genes with changed RNAPII occupancy in response to the various l
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