Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell

Article Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin  ,1 Daria Shlyueva,1 Christoph Stelzer,1 Daniel Gerlach,1 J. Omar Ya´n˜ez-Cuna,1 Martina Rath,1 qukasz M. Boryn Cosmas D. Arnold,1 and Alexander Stark1,* 1Research Institute of Molecular Pathology (IMP), 1030 Vienna, Austria *Correspondence: [email protected] http://dx.doi.org/10.1016/j.molcel.2014.02.026

SUMMARY

Steroid hormones act as important developmental switches, and their nuclear receptors regulate many genes. However, few hormone-dependent enhancers have been characterized, and important aspects of their sequence architecture, cell-type-specific activating and repressing functions, or the regulatory roles of their chromatin structure have remained unclear. We used STARR-seq, a recently developed enhancer-screening assay, and ecdysone signaling in two different Drosophila cell types to derive genome-wide hormone-dependent enhancer-activity maps. We demonstrate that enhancer activation depends on cis-regulatory motif combinations that differ between cell types and can predict cell-typespecific ecdysone targeting. Activated enhancers are often not accessible prior to induction. Enhancer repression following hormone treatment seems independent of receptor motifs and receptor binding to the enhancer, as we show using ChIP-seq, but appears to rely on motifs for other factors, including Eip74. Our strategy is applicable to study signaldependent enhancers for different pathways and across organisms. INTRODUCTION During animal development, gene expression is regulated spatially and temporally according to information in discrete DNA sequence elements called enhancers or cis-regulatory modules (CRMs) (Buecker and Wysocka, 2012; Levine, 2010). Enhancers recruit transcription factors (TFs) to specific binding sites, and specific combinations of TFs and their coactivators and corepressors result in gene activation or repression (Spitz and Furlong, 2012; Ya´n˜ez-Cuna et al., 2013). In addition, external stimuli such as hormone signaling can induce drastic changes to cellular transcriptional programs by activating or repressing specific target enhancers. Steroid hormones, for example, are crucial for many biological processes including reproduction, metabolism, and immunity (Ashwell

et al., 2000) and have been implicated in widespread diseases such as cancer (Deroo and Korach, 2006; Hah et al., 2011). They can diffuse through membranes, which allows systemic signals to freely enter cells and influence gene expression, often in a cell-type- or tissue-specific manner. This is achieved through nuclear receptors (NRs), which are ligand-activated TFs. Upon hormone binding, NRs bind to cell-type-specific CRMs that contain hormone response elements (HREs), recruit cofactors, and regulate gene expression (King-Jones and Thummel, 2005; Tata, 2002 and references therein). Considering the important role of hormone signaling in development, physiology, and disease, the mechanisms and regulatory targets of hormone-dependent gene regulation have been studied intensely in different biological systems (Ong and Corces, 2011; Tata, 2002). This included more recently the genomewide analysis of hormone-receptor binding and chromatin modifications by chromatin immunoprecipitation sequencing (ChIP-seq) that—typically in combination with DNase I hypersensitivity assays (Hurtado et al., 2011; John et al., 2011) or enhancer RNAs (eRNAs) (Hah et al., 2011, 2013)—allowed the prediction of hormone-responsive enhancers. These approaches found that hormone receptors frequently bind to hundreds of sites, often together with additional TFs (Biddie et al., 2011; Heinz et al., 2010) that typically differ between cell types (Heinz et al., 2010). While some studies concluded that the binding sites are predetermined by chromatin accessibility (Hurtado et al., 2011; John et al., 2011), others reported that hormone receptors can also access closed chromatin (Hah et al., 2013; Ballare´ et al., 2013), consistent with earlier findings (Zaret and Yamamoto, 1984). However, the enhancer function of only a few of these binding sites has been tested using transcriptional reporter assays (e.g., luciferase assays), and genome-wide analyses of hormone-regulated enhancer activities have been lacking. Arguably the best-studied hormone in insects is the steroid hormone ecdysone, which is important for metamorphosis, molting, and nervous system and eye development. It has also more broadly served as a model to study aspects of hormone signaling more generally (King-Jones and Thummel, 2005; Tata, 2002). The active form of ecdysone (20-hydroxyecdysone) binds to a heterodimer of two nuclear receptors, the ecdysone receptor (EcR, the ortholog of the vertebrate farsenoid X or liver X receptor) and ultraspiracle (usp, the ortholog of the vertebrate retinoid X receptor) (King-Jones and Thummel, 2005). Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 1

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell Hormone-Responsive Enhancer-Activity Maps

The EcR-usp heterodimer recognizes a pseudopalindromic sequence containing G(G/A)(T/A)CA half-sites separated by a variable spacer (Riddihough and Pelham, 1987). However, functional studies of ecdysone-responsive cis-regulatory elements have been restricted to a small number of sequences that were originally identified by extensive promoter analysis of ecdysone-induced genes in Drosophila cell lines (mainly S2 cells) and tissues (Laval et al., 1993; Riddihough and Pelham, 1987). The total number of identified ecdysoneinduced enhancers (approximately five) is not comparable to the hundreds of transcripts upregulated by the hormone in different cell types, and the enhancers even for well-known ecdysone targets such as the TF Broad-complex (br) or the microRNA let-7 have remained elusive. Moreover, even though a similar number of genes are downregulated after ecdysone treatment (Gauhar et al., 2009), not a single ecdysone-repressed enhancer has been identified. As a consequence, it has remained unknown how ecdysone leads to repression and how the hormone can both activate and repress gene expression, an important question for signaling pathways more generally (Affolter et al., 2008). The lack of a comprehensive map of ecdysone-responsive enhancers has also prevented the systematic analysis of their sequence requirements. For example, while the EcR motif is required for ecdysone-dependent enhancers (Bernardo et al., 2009), it is clear that EcR motifs are not sufficient and that most EcR motif occurrences in the genome are nonfunctional. Similarly, it has remained unclear how a single hormone via its nuclear receptor can elicit different gene regulatory and physiological responses in different cell types. Here, we use ecdysone signaling in Drosophila melanogaster (D.mel) S2 cells and ovarian somatic cells (OSCs) (Saito et al., 2009) to dissect the sequence basis of hormone-responsive transcriptional enhancers in two different cell types. We build genome-wide quantitative maps of hormone-responsive enhancer activity using the recently developed enhancer screening method self-transcribing active regulatory region sequencing (STARR-seq) (Arnold et al., 2013). We find enhancers that are induced or repressed by ecdysone, which are in agreement with the neighboring genes’ transcriptional responses and can be discriminated computationally based on their motif content. Besides EcR-usp motifs, induced enhancers display distinct sets of motifs for partner TFs, which differ between S2 cells and OSCs and are predictive and required for cell-type-specific enhancer function. Using ChIP-seq, we show that enhancer repression following ecdysone treatment is indirect and independent of EcR binding but might depend on the motifs of other TFs, including Eip74. Finally, we show that most of the ecdysone-induced enhancers lie in regions of chromatin that are closed prior to hormone treatment yet become open upon induction. RESULTS A Genome-wide Set of Ecdysone-Responsive Enhancers To determine ecdysone-responsive sequences and measure their activity in S2 cells genome-wide, we used STARR-seq, a 2 Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc.

newly established enhancer screening method (Arnold et al., 2013). STARR-seq measures the enhancer activity of candidate sequences directly and quantitatively and constitutes a genomewide equivalent of luciferase assays. The STARR-seq vector couples the candidates’ activities to their sequences in cis, such that active enhancers transcribe themselves and are present among cellular RNAs. This setup allows the assessment of candidates independent of whether they are associated with endogenous eRNAs (Hah et al., 2011; Kim et al., 2010; Lam et al., 2013) and irrespective of their locations at or near promoters or transcription start sites (TSSs) or in transcribed regions (e.g., introns or exons), enabling genome-wide enhancer screens (Arnold et al., 2013). We transfected a STARR-seq reporter library generated from randomly sheared D.mel genomic DNA into S2 cells, treated half of the cells with ecdysone, and harvested all cells after 24 hr to further process the reporter transcripts as described previously (Arnold et al., 2013) (Figure 1A). After ecdysone treatment, we identified 1,593 peaks, of which 788 were induced at least 2.5-fold and 352 at least 4-fold, and of which 732 were only detectable after treatment (Figure 1B). Interestingly, the opposite was also true: 889 peaks were at least 2.5-fold and 328 were at least 4-fold repressed after treatment (Figure 1B), consistent with previous reports that ecdysone can also have repressive effects on genes (King-Jones and Thummel, 2005; Sempere et al., 2003). We separated the identified peaks into three stringently defined classes based on their activity before and after treatment (ecdysone-induced, ecdysone-repressed, and constitutive; Figures 1C–1E) and validated examples from all three classes by luciferase assays (46 total; Figure 2A; Figure S1A available online). Consistent with STARR-seq, we found strongly increased luciferase activity upon treatment for ecdysone-induced peaks (17.5-fold; n = 16); decreased activity for repressed peaks (7.8-fold; n = 17), and no difference for constitutive regions (1.6-fold increase; n = 13) (Figure 2A; Figure S1A). The strongest peak after treatment was located in the promoter region of Eip75A (STARR-seq signal 85-fold, p % 0.001) (Figure 1C), a well-studied early target of ecdysone (Bialecki et al., 2002; Segraves and Hogness, 1990). This sequence was not known to be an enhancer and did not show any STARR-seq signal in the absence of ecdysone (1-fold; p = 0.24). We also detected all previously identified S2 cell-specific enhancers for Eip75 (Figure S1C) (Bernardo et al., 2009). Furthermore, we observed ecdysone-induced peaks near other known ecdysone target genes for which no enhancers were known, including br (Figure 6A), Eip78, Eip93, Eip74 (Figures S1D, S1F, and S1H), and confirmed the inducibility of the Hsp27 proximal promoter (Figure S1I) (Riddihough and Pelham, 1987). We also found ecdysone-induced peaks near the let-7, mir-125, and mir-100 microRNAs (Figure S1E), which are known to be upregulated in S2 cells after ecdysone treatment (Sempere et al., 2003). Similarly, we found repressed enhancers near genes that were known to be downregulated after ecdysone treatment, including the microRNAs mir-14 and mir-34 (Figures S1G and S1J) (Sempere et al., 2003).

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

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Figure 1. Identification of Genome-wide Sets of Hormone-Responsive Enhancers (A) Schematic representation of the STARR-seq pipeline to screen for hormone-induced enhancers. (B) The three types of STARR-seq peaks considered for this study, the criteria for each group, and the number of peaks per group (‘‘ratio’’ denotes the ratio of STARR-seq enrichments after versus before treatment). (C–E) UCSC genome browser (Kent et al., 2002) screenshots of STARR-seq and strand-specific RNA-seq tracks for the Eip75, Pvf2, and UGP gene loci (only representative isoforms are shown). Red shading highlights induced, blue repressed, and green constitutive peaks, respectively. Other known ecdysone target gene loci are shown in Figures S1C–S1J.

Ecdysone-Responsive Enhancers Regulate Neighboring Genes In Vivo We next performed RNA-seq for S2 cells before and after ecdysone treatment, which revealed the upregulation of a large number of genes: 1,164 were at least 2-fold upregulated (p % 0.001) after ecdysone treatment, including the known early (Eip75, br, Eip74, Eip93, and Hsp27) and the delayed (Eip78 and Hr46) ecdysone targets. Known genes from the second wave of induction showed a more heterogeneous response: some were induced and had enhancers nearby (e.g., ftz-f1 and Eip93), whereas some did not (e.g., Hr78 and L71). Ecdysone treatment also resulted in the repression of many genes (1,347 were at least 2-fold downregulated; p % 0.001), including genes known to be repressed by ecdysone in D.mel Kc167 cells such as PDGF- and VEGF-related factor 2 (Pvf2) (Figure 1D) and PAR-domain protein 1 (Pdp1) (Gonsalves et al., 2011). Even globally, about 50% of the upregulated genes and 41% of the early downregulated genes in Kc167 cells (Gauhar et al., 2009) were regulated consistently in S2 cells, and 20% of the EcR binding regions detected by DamID (Gauhar et al., 2009) contained STARR-seq enhancers, 5-fold more than expected (binomial p value = 9.4 3 10 34).

Interestingly, enhancers that differentially responded to ecdysone were located near distinct sets of genes (Figure 2B), suggesting different functions for both classes. A total of 26% of the genes near induced enhancers were at least 2-fold upregulated, whereas only 9% were downregulated and the reverse was true for genes near repressed enhancers (18% downregulation and 9% upregulation; Figure 2C; and Figure S1B). This suggests that the identified enhancers function correspondingly in their endogenous context. Together, the above results imply that we obtained a genomewide map of bona fide hormone-responsive enhancers. Strong Induction Is Mediated via Multiple HormoneInduced Enhancers Enhancer strengths and gene expression levels agreed also quantitatively, in accordance with previous findings (Arnold et al., 2013): the sum of STARR-seq enhancer strengths per gene strongly linearly correlated on average with the gene expression levels before (Pearson correlation coefficient [PCC] = 0.89) and after (PCC = 0.87) ecdysone treatment (Figure S2A), as did the respective changes upon hormone Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 3

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Figure 2. Validation of Hormone-Responsive Enhancers and Gene Induction via Multiple Enhancers (A) Validation of peaks from the induced, repressed, and constitutive classes by luciferase assays. Log2 fold induction of normalized luciferase signal is shown (see also Figure S1A). Wilcoxon rank-sum test: *p % 0.0001, **p % 10 13. (B) Venn diagram showing the number of genes near induced, repressed, and constitutive STARR-seq enhancers (±3 kb TSS). (C) The percent of assigned genes that are up- or downregulated at least 2-fold for each class of enhancers. See Figure S1B for a 4-fold cutoff and Figure S2 for a quantitative analysis. (D) Boxplot showing the gene expression changes (log2 scale) depending on the number of gained enhancers after treatment. Wilcoxon rank-sum test: p = 0.0015. (E and F) UCSC genome browser screenshots of STARR-seq and strand-specific RNA-seq tracks for E23 (E) and Alh (F), which are induced by multiple and a single enhancer, respectively. Red shading highlights induced peaks. See Figure S2D for an additional gene locus.

treatment (PCC = 0.58). Genes with two or more enhancers were on average expressed more highly than genes with single enhancers (Figure S2B). In addition, enhancer-to-TSS distances had an effect: when considering only genes with single enhancers of similar strengths, genes were more highly expressed if the enhancer was within 1 kb of the TSS compared to genes with more distal enhancers (Figure S2C), consistent with reporter assays (Banerji et al., 1981). Interestingly, some of the most strongly upregulated genes, including the known ecdysone targets Eip75, br, Hr4, Hr46, or E23, appeared to be induced via multiple ecdysone-responsive enhancers (Figures 1C, 2E, 4B, and 6A; Figure S2D). This suggests that strong induction might more generally be mediated via multiple enhancers. Indeed, when we compared the induction of genes that gained different numbers of additional enhancers upon hormone treatment, genes with three or more 4 Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc.

additionally gained enhancers were substantially more highly induced than genes with one gained enhancer (5.5-fold upregulation versus 1.1-fold, respectively; Figure 2D). Interestingly, however, some of the strongly upregulated genes appear to be strongly regulated via a single enhancer only (e.g., Figure 2F). Together, our data show that enhancer strength correlates well with gene expression and suggest that strong induction is mediated by multiple enhancers. Ecdysone-Induced Enhancers Have a Distinct cisRegulatory Signature that Is Predictive and Contains EcR Motifs and Partner TF Motifs To determine the sequence requirements of ecdysone-induced enhancers, we first assessed the occurrence of known and predicted motifs (Stark et al., 2007) in enhancers versus negative control sequences. A total of 30 motifs were enriched in

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

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Figure 3. Differential Motif Content of Ecdysone-Induced Enhancers Allows the Identification of EcR Partner Motifs (A) Heatmap of predictive and differentially enriched motifs (p % 0.01) when comparing induced enhancers versus negative control regions. (B) Logos for the EcR and srp motifs used in the analysis. (C) Percentage of correctly classified sites for each comparison when using an SVM based on motif counts and leave-one-out cross-validation. The black line shows the expected prediction accuracy for random classification (50%). Data are shown as mean ± SD of three replicates. (D) Heatmaps for predictive and differentially enriched motifs (p % 0.01) when comparing induced enhancers versus negative controls selected to contain EcR motifs (note that the enrichment of the EcR motif above the genome merely reflects that the regions have been selected to contain such motifs). (E) Fold induction of normalized luciferase signal for induced enhancers near Eip75, sn, Dip-B, and Nhe-2, assessing the wild-type sequences and variants in which the EcR or srp or both motifs were mutated. Negative region: sequence from the exon of tj as in (Arnold et al., 2013). All DNA sequences are listed in Table S2. NS, not significant. Welch two-sample t test: *p % 0.01; **p % 10 5. Data are shown as mean ± SD of four experiments. See also Figure S3A.

enhancers (1.5-fold and p % 0.001; Table S1; Figure 3A), including the EcR-usp motif (2.2-fold, p = 1.28 3 10 26; Figure 3B). Interestingly, motifs for other TFs were also differentially enriched (Table S1), such as the motifs for serpent (srp) (Figure 3B), Trithorax-like/GAGA (Trl), Adf1, and Aef1. The GATA factor serpent is considered to be a regulator of prehemocyte differentiation (Rehorn et al., 1996) and is required for S2 cells (Ra¨met et al., 2002), whereas Aef1 is a transcriptional repressor (Brodu et al., 2001; Falb and Maniatis, 1992). Intriguingly, both srp and Aef1 were found to cooperate with EcR in the regulation of an ecdysone-dependent fat-body-specific enhancer (Brodu et al., 1999, 2001). To ask if the differential motif content was sufficient to computationally predict ecdysone-induced enhancers, we used an approach based on supervised machine learning that we previously developed for the classification of TF binding sites

(Ya´n˜ez-Cuna et al., 2012) and for the identification of cis-regulatory sequence signatures of early embryonic enhancers (Kvon et al., 2012). Indeed, ecdysone-induced enhancers could be discriminated from negative controls solely based on the number of TF motif occurrences with high accuracy (ACC) (73.8% ± 3.6% versus 50% expected at random; area under the curve [AUC] = 0.79 ± 0.02) (Figure 3C). This indicates that ecdysoneinduced enhancers have a specific cis-regulatory signature that is predictive. Both the EcR-usp motif and motifs for other TFs (e.g., srp) scored as highly discriminative features, suggesting that ecdysone-responsive enhancers are characterized and potentially functionally defined by such additional motifs. Indeed, ecdysone-responsive enhancers could be discriminated from controls even when the EcR-usp motif was not used (ACC = 66.1% ± 1.0%; AUC = 0.71 ± 0.02) or when we selected controls Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 5

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Molecular Cell Hormone-Responsive Enhancer-Activity Maps

that contained EcR-usp motifs (ACC = 67.4% ± 1.9%; AUC = 0.73 ± 0.03) (Figure 3C). In both cases, the srp motif remained among the top discriminative features (Figure 3D), and the vast majority (73%) of the induced enhancers that contained EcR motifs also contained srp motifs (Figure S3B). This shows that ecdysone-induced enhancers are characterized by the EcR motif and motifs for additional TFs such as srp. Srp might be a cell-typespecific partner TF, because the its motif is also enriched in constitutive S2 cell enhancers (Table S1). To test if srp motifs are required for ecdysone-induced enhancer function in S2 cells, we selected four enhancers that all drove expression of a luciferase reporter only upon ecdysone treatment yet responded with different strengths (between 4and 60-fold induction). We introduced point mutations to disrupt the EcR motif, the srp motif, or both (see Table S2), which severely decreased or abolished the inducibility for all constructs (Figure 3E; Figure S3A). This shows that the EcR motif alone cannot account for induction and demonstrates the requirement for both the EcR and the srp motifs, suggesting that the corresponding factors might act synergistically. Despite the functional importance of both motifs, we did not observe them to be in any specific order or particular arrangement relative to each other (Figure S3F). The absence of such an arrangement, or a so-called motif grammar, is consistent with the ‘‘billboard’’ enhancer model (Arnosti and Kulkarni, 2005), which has also been observed for developmental enhancers more generally (Junion et al., 2012; Ya´n˜ez-Cuna et al., 2013). Taken together, we showed that ecdysone-induced enhancers contain predictive and functionally required sequence features, including motifs for EcR and srp. Srp might help define S2 cell-specific target enhancers, consistent with models for enhancers downstream of signaling pathways more generally, which are thought to receive at least two kinds of inputs: one that restricts tissue specificity and another that transduces the extracellular signal (Brodu et al., 2001; Halfon et al., 2002; Mullen et al., 2011). EcR Partner Motifs Differ between Cell Types and Help Define Cell-Type-Specific Target Enhancers The finding that EcR partner TFs such as srp might help define cell-type-specific EcR targets is intriguing, because it might explain how individual hormones and their nuclear receptors can elicit different responses in different developmental contexts, tissues, or cell types (Heinz et al., 2010; Ya´n˜ez-Cuna et al., 2012). To directly assess the cell-type specificity of ecdysone-responsive enhancers and their cis-regulatory signatures, we performed STARR-seq before and after ecdysone treatment in cultured OSCs. OSCs have been derived from adult D.mel ovaries (Saito et al., 2009), in which ecdysone signaling is known to play an important role (Hodin and Riddiford, 1998). After ecdysone treatment, we identified 2,570 peaks, of which 933 were induced at least 2.5-fold and 656 were only detectable after treatment. Of the 4,163 peaks found in S2 cells or OSCs, only 274 (6.5%) were shared between both, including enhancers near a core set of ecdysone targets such as Eip74, Eip75, Eip78, E23, br, vri, ftz-f1, and Hr46 (Figure 4B). The vast majority of the peaks were specific to either S2 cells or OSCs, consistent with the cell-type-specific functions of ecdysone signaling. 6 Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc.

When we repeated the sequence analyses for ecdysoneinduced enhancers in OSCs, we could again successfully discriminate them from negative controls (ACC = 72.4% ± 1.8%, AUC = 0.81 ± 0.0) (Figure 4C). Importantly, however, the characteristic motifs differed: whereas the EcR-usp motif was still enriched as expected, the srp motif was not, and among the most discriminative features was the motif for traffic jam (tj; Figure 4D). Tj is a master regulator of ovarian development that is highly expressed in OSCs (Saito et al., 2009), suggesting that it could indeed be an important OSC-specific partner TF. Indeed, disrupting either the EcR-usp or the tj motifs by point mutations abolished the activity of an OSC-specific ecdysoneinduced enhancer in the skywalker (sky) locus (Figures 4A and 4E; Figure S3D). This suggests that the identity of the EcR partner motifs has changed from srp in S2 cells to tj in OSCs. Interestingly, this change also applied to enhancers that were active in both cell types: disrupting the srp motif in the Eip75 enhancer abolished activity in S2 cells (see above and Figure 3E), but not in OSCs (Figure 4D; Figure S3D). In contrast, mutating the EcR or tj motifs rendered the enhancer inactive in OSCs (Figure 4E), confirming that EcR partner motif requirements can differ between cell types, even for shared enhancers. These results suggest that the combination of hormone receptor motifs and cell-type-specific partner motifs might define target enhancers in each cell type. Indeed, the motif content of the respective sequences alone allows the discrimination between ecdysone-induced enhancers in S2 cells and OSCs (ACC = 74.8% ± 1.9%, AUC = 0.83 ± 0.00) (Figure 4C; Figure S3C). Enhancer Sequence Signatures and EcR Binding Suggest that Ecdysone-Mediated Repression Is Indirect To understand the differences between ecdysone-induced and ecdysone-repressed enhancers in S2 cells, we carried out computational sequence analyses similar to those above. Solely based on their motif content, ecdysone-repressed enhancers can be successfully discriminated from controls (ACC = 73.5% ± 1.6%, AUC = 0.80 ± 0.04). Similar to induced enhancers, the top enriched and discriminative motif was srp (Table S1). To our surprise, however, the EcR motif was not enriched but slightly depleted (1.3-fold depletion, p = 0.02) (Table S1), suggesting that ecdysone-mediated repression is independent from the EcR binding to its cognate sequence motifs. Repressed enhancers could be successfully discriminated from induced enhancers (ACC = 75.2% ± 1.6%; AUC = 0.84 ± 0.00) (Figure 5A), with the Eip74EF motif among top discriminative features enriched in repressed enhancers (Figure 5B). Eip74 (or E74) is an ETS domain TF that is essential for developmental responses to ecdysone and regulates the timing of secondaryresponse target expression (Fletcher et al., 1995). To test whether the Eip74 motif is required for ecdysone-mediated repression, we introduced point mutations to a repressed enhancer of myoblast city (mbc), which indeed abolished repression (Figure 5C; Figure S3E). We conclude that repression upon ecdysone treatment is likely independent of the EcR motif yet involves the Eip74 motif. We next performed ChIP-seq with an antibody against EcR from S2 cells 24 hr after ecdysone treatment (Figures 5D–5F).

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

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Figure 4. Functionally Required EcR Partner Motifs Differ between Cell Types (A and B) UCSC genome browser screenshots of STARR-seq tracks in S2 cells and OSCs for the sky (A) and Hr46 (B) gene loci. Orange shading highlights OSCspecific induced peaks. (C) Percent of correctly classified sites when using an SVM based on motif counts and leave-one-out cross-validation (the black line shows the expected prediction accuracy for random classification [50%]). Data are shown as mean ± SD of three replicates. (D) Heatmap for predictive and differentially enriched motifs (p % 0.01) when comparing OSC-induced enhancers versus negative controls (the srp motif is added to show that OSC-induced enhancers are depleted of it). (E) Fold induction of normalized luciferase signal for induced enhancers near sky and Eip75, assessing the wild-type sequences and variants in which the EcR, tj, or srp motifs are mutated. Negative region: sequence from the exon of tj as in Arnold et al. (2013). All DNA sequences are listed in Table S2. NS, not significant; NA, not applicable. Welch two-sample t test: *p % 0.01; **p % 10 4. Data are shown as mean ± SD of two experiments (two replicates each). See also Figure S3D.

This showed that 33.5% of the induced but only 5.5% of the repressed enhancers had a significant ChIP enrichment (p % 0.05, binomial test) at the summit position, a more than 6-fold difference that suggests that ecdysone-mediated repression is indeed predominantly independent of EcR binding. Together with the motif analyses, this suggests that the repression of enhancer activity after ecdysone treatment is predominantly indirect and likely does not involve EcR binding, but rather the ETS domain TF Eip74. It is interesting to note that the

absence of EcR binding also means that ecdysone-repressed enhancers are more difficult to detect along the genome, consistent with the fact that none had been described so far. Ecdysone Signaling Targets Enhancers that Are Inaccessible Prior to Hormone Treatment The chromatin structure at enhancers affects their accessibility by TFs and, vice versa, TFs and the cofactors they recruit can alter the chromatin structure. Active enhancers are typically Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 7

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

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Figure 5. Ecdysone-Mediated Repression Is Independent of EcR but Involves Eip74 Motifs (A) Percent of correctly classified sites when comparing induced and repressed enhancers using an SVM (50%, at random). Data are shown as mean ± SD of three replicates. (B) Heatmap for predictive and differentially enriched motifs (p % 0.01) when comparing S2-induced versus repressed enhancers. (C) Fold repression of normalized luciferase signal for repressed intronic enhancer of mbc assessing the wild-type sequence and a variant in which the Eip74 motif was mutated. Negative region: sequence from the exon of tj as in Arnold et al. (2013). All DNA sequences are listed in Table S2. NS, not significant. Welch two-sample t test: **p % 10 7. Data are shown as mean ± SD of four experiments. See also Figure S3E. (D–F) UCSC genome browser screenshots of STARR-seq and EcR ChIP-seq tracks for ecdysone-induced or repressed enhancers in the E23, btn, and mbc gene loci (only representative isoforms are shown). See main text for genome-wide numbers of EcR binding to induced and repressed enhancers.

located in accessible or open chromatin, whereas inaccessible (closed) chromatin is a hallmark of inactive enhancers and heterochromatin. Chromatin states and their potential dynamics are especially interesting for signal-dependent inducible enhancers, which might be closed prior to signaling to avoid improper activation (e.g., progesterone; Ballare´ et al., 2013). Alternatively, the open state might pre-exist and might even define the enhancers in a cell-type-specific manner. For example, the estrogen receptor alpha (ERa) and the glucocorticoid receptor (GR) have been reported to predominantly bind to regions that were open prior to hormone treatment (Hurtado et al., 2011; John et al., 2011). These studies, however, could not assess if or to what extent the binding sites determined by ChIP corresponded to functional hormone-responsive enhancers and disagree with reports that showed that ERa and GR can access closed chromatin (Hah et al., 2013; Zaret and Yamamoto, 1984). 8 Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc.

To investigate the relationship between ecdysone signaling and chromatin, we performed DNase I hypersensitivity assays coupled to deep sequencing (DHS-seq) (Boyle et al., 2008) for S2 cells before and 24 hr after ecdysone treatment (Figures 6A–6C; Figure S1D–S1J). Interestingly, only 29.6% of the ecdysone-induced enhancers were open prior to treatment (DHS-seq signal p < 0.05) with an average DHS-seq enrichment at the enhancer summits of only 1.2-fold (Figure 6D). This is in contrast to 74.4% of the ecdysone-repressed and 71.2% of the constitutive enhancers that were open prior to treatment with high average DHS-seq enrichments (Figure 6D). After treatment, 60% of the inducible enhancers showed an increased DHS-signal, whereas the majority of the repressed enhancers (74%) showed decreased DHS signals and the constitutive enhancers did not change their accessibility on average (Figure 6E).

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell Hormone-Responsive Enhancer-Activity Maps

A

B

C

D

E Induced (n = 351)

Repressed (n = 328)

Constitutive (n = 374)

Random (n = 1,000)

Figure 6. Ecdysone Signaling Can Target Inaccessible Chromatin (A–C) UCSC genome browser screenshots of STARR-seq, strand-specific RNA-seq, and DHS-seq tracks for the br, Sur-8, and Dip-B gene loci. Red and blue shading highlights STARR-seq enhancers that become open or closed upon treatment, respectively. (D) DHS-seq read density profiles ±5 kb around the summit of enhancers from three different classes before (black) and after (purple) treatment. (E) Boxplots showing the difference in chromatin accessibility upon ecdysone treatment at the summit positions (±5 bp) for the different enhancer classes (log2 scale). Wilcoxon rank-sum test: *p % 0.001.

This shows that ecdysone signaling functionally targets predominantly closed chromatin and suggests a model in which the EcR potentially with auxiliary partners (e.g., srp) can mediate chromatin opening. DISCUSSION In this study, we obtained a quantitative genome-wide map of hormone-dependent enhancer activity using STARR-seq, a direct activity-based method for enhancer identification (Arnold et al., 2013). The availability of hundreds of hormone-activated enhancers allowed the systematic dissection of their sequence features, revealing characteristic motif signatures that are predictive within strict cross-validation settings (i.e., when the sequences used for training and testing are strictly

separated). These successful predictions mean that the motif signatures are shared across different enhancers and sufficiently general to predict previously unseen sequences not used for training. Interestingly, ecdysone-induced enhancers do not only contain the EcR motif but are also strongly enriched in motifs of putative partner TFs, which differ between cell types and are required for enhancer function. The insufficiency of the EcR to activate transcription and the strict dependence on additional cell-type-specific factors is an important prerequisite to achieve cell-type-specific transcriptional responses via combinatorial regulation. It has been observed for individual transcriptional enhancers that depend on different signaling pathways (Barolo and Posakony, 2002; Flores et al., 2000; Halfon et al., 2000). Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 9

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell Hormone-Responsive Enhancer-Activity Maps

Such strictly combinatorial function has been termed ‘‘activator insufficiency’’ (Barolo and Posakony, 2002) and proposes that ligand-activated TFs function combinatorially with tissueand cell-specific TFs that act as competence determinants (Biddie et al., 2011; Hurtado et al., 2011) and/or coactivators. Here, the combination of STARR-seq and computational sequence analyses allowed us to identify the motif combinations required for ecdysone-activated enhancer function in two different cell types without prior knowledge regarding the hormone receptor and/or putative partners. Repression of enhancer activity after ecdysone treatment appears to be independent of EcR motifs and receptor binding but seems to involve Eip74 motifs. Interestingly, Eip74 had previously been proposed to repress a subset of secondary ecdysone targets, because late puffs in salivary glands appeared larger in Eip74 mutant flies (Fletcher et al., 1995). Because the Eip74 motif mutant enhancer is also less strongly active in the absence of ecdysone (Figure S3E), this could mean that Eip74 competes with an activator or that Eip74 activates the enhancer itself prior to treatment and is then depleted of cofactors, a phenomenon called transrepression that is known for hormone signaling pathways (e.g., glucocorticoid receptor; Affolter et al., 2008; Ogawa et al., 2005). Previous studies showed that hormone receptors bound predominantly to regions that were already accessible prior to treatment and suggested that the chromatin might predetermine hormone-responsive enhancers (Hurtado et al., 2011; John et al., 2011). We also found enhancers that are activated by ecdysone signaling and open prior to treatment (e.g., a strong enhancer in the Eip75 locus). Some of these open enhancers are already bound by the EcR, which might premark regions to prepare them for fast activation or repress them in the absence of ligand, which is an established function of the EcR (Dobens et al., 1991; Tsai et al., 1999). The latter—‘‘default repression’’—is another hallmark of TFs and enhancers downstream of signaling pathways, which might ensure reliable regulatory switching (Barolo and Posakony, 2002). We did not find evidence for default repression via the EcR and its motifs, because our disruption of EcR motifs in several enhancers did not activate them. The majority of the ecdysone-activated enhancers (>60%) are, however, closed prior to treatment with no detectable DHS-seq signal. The discrepancy between these results and the ones for the ERa and GR above might stem from the fact that not all ERa and GR binding sites determined by ChIP-seq correspond to functional hormone-responsive enhancers (Kvon et al., 2012; Li et al., 2008). Interestingly, a recent study that considered ERa binding sites that produced eRNAs and were thus likely active (Hah et al., 2011) concluded that ERa can access and activate enhancers in closed chromatin (Hah et al., 2013). Together, our findings that are based on directly assessing enhancer activities caution the interpretation of TF binding sites determined by ChIP: because TFs (and other proteins including GFP) can be frequently crosslinked to open chromatin (Kvon et al., 2012; Li et al., 2008; Poorey et al., 2013; Teytelman et al., 2013), the majority of ChIP-seq signals might not correspond to active enhancers. Furthermore, it questions the validity of the frequently used categorization of TF binding sites into enhancers that are regulated positively or negatively based on the 10 Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc.

flanking genes’ transcriptional responses. Even TFs that function exclusively as activators will have binding sites near downregulated genes, such that a repressive function might erroneously be assumed. For example, contrary to prior expectations, only the activating function of Oct4 appears to be required for pluripotency (Hammachi et al., 2012), and we show here that ecdysone-mediated repression is indirect and independent of EcR binding. In summary, the use of the activity-based enhancer screening method STARR-seq allowed genome-wide identification of functional hormone-responsive enhancers. Combined with the computational dissection of sequence requirements, our approach revealed that the EcR functions together with celltype-specific partner factors, which are required for enhancer activation. The study also establishes STARR-seq as the method of choice to screen for inducible enhancers downstream of signaling pathways. The combination of STARR-seq with sequence analyses promises to be a useful approach applicable to detect signaling-dependent enhancers and elucidate their sequence characteristics more generally for different signaling pathways and across organisms. EXPERIMENTAL PROCEDURES Ecdysone Treatment Unless stated otherwise, we used ecdysone (Sigma; catalog no. H5142) at a concentration of 41 mM and an incubation time of 24 hr. STARR-Seq STARR-seq was performed as described previously (Arnold et al., 2013). In brief, the screening library was generated from genomic DNA isolated of the sequenced D.mel strain (y; cn bw sp). We transfected 5 3 108 to 1 3 109 S2 cells or OSCs total, in batches of 1 3 107 cells, which we electroporated with 10 mg of the input library each. After recovery, 4.8 3 108 cells were transferred to standard growth medium and 9.6 3 108 were transferred to medium with ecdysone (6 3 107 cells per 55 ml of medium). After 24 hr incubation, poly-A RNA was isolated and processed as described elsewhere (Arnold et al., 2013). Note that this includes a reverse transcription and two nested PCR steps, each with primers that are specific to the reporter transcripts such that STARR-seq does not detect endogenous cellular RNAs. It can therefore also assess the enhancer activities of sequences within or overlapping transcribed introns or exons. Strand-Specific RNA-Seq A total of 6 3 107 S2 cells were electroporated with the empty screening vector (10 mg per 1 3 107 cells), and 4 3 107 cells were treated with ecdysone. RNA was isolated and processed as described previously (Arnold et al., 2013; Zhong et al., 2011). DHS-Seq A total of 1 3 108 S2 cells were used per screen. Cells were processed as described elsewhere (Arnold et al., 2013; Cappabianca et al., 1999). ChIP-Seq A total of 108 S2 cells were used. Half were treated with ecdysone for 24 hr. Cells and chromatin were processed as described previously (Lee et al., 2006), with minor modifications. Chromatin was sonicated with tip sonicator (Omni Sonic Ruptor 250 Watt Ultrasonic Homogenizer) for seven cycles (1 min on [duty cycle 30%, output 20%], 1 min off) in 2 ml of lysis buffer 3. The anti-EcR monoclonal antibody (DDA2.7) developed by C. Thummel in the D. Hogness laboratory was obtained from the Developmental Studies Hybridoma Bank developed under the auspices of the NICHD and maintained by The University of Iowa (Department of Biology, Iowa City, IA 52242, USA). A

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell Hormone-Responsive Enhancer-Activity Maps

total of 1 ml of chromatin was incubated with 3 ml of antibody (135 mg/ml) overnight. Chromatin and 25 ml of blocked Dynabeads Protein G (Invitrogen; catalog no. 10004D) were combined and incubated at 4 C for additional 2 hr. A total of 3 ng of material was used for library generation. Deep Sequencing All pair-end or single-end sequencing was performed on an Illumina HiSeq2000 machine. For all experiments, we compared two independent biological replicates and merged them for the subsequent analyses. Data from Arnold et al. (2013) are available at the NCBI Gene Expression Omnibus (GEO) under accession number GSE40739. Mutational Analysis and Luciferase Assay Enhancer candidates were amplified from genomic DNA of the sequenced D.mel strain (y; cn bw sp) (for primers, see Table S3), and the mutant variants were synthesized as gBlocks by Integrated DNA Technologies (for sequences, see Table S2). All candidates were subcloned to pCR8/GW/TOPO (Invitrogen; catalog no. 450642) and delivered to a firefly luciferase vector (Arnold et al., 2013) using the Gateway LR Clonase II enzyme mix (Invitrogen; catalog no. 11791-019) following the manufacturer’s protocol. A total of 1 3 105 S2 cells or OSCs were transfected with 110 ng of DNA including 10 ng of renilla firefly under the control of the ubiquitin (Ubi63E) promoter using JetPei (Polyplus transfection, catalog no. 101-40N). After 48 hr, a luciferase assay was performed with Dual-Luciferase Reporter assay system (Promega; catalog no. E1910). For tests in S2 cells, we performed four biological replicates for each construct but three for the sn enhancer. In OSCs, we performed two biological replicates for each construct (for all, we did two technical replicates per biological replicate). Computational Analysis All deep-sequencing data were mapped and analyzed as described previously (Arnold et al., 2013) and using thresholds described above. For gene expression and DHS-seq analysis, we used three different sets of enhancers as described above (induced: enrichment R 3, p % 0.001 [after treatment] and ratio R 4; repressed: enrichment R 3, p % 0.001 [before treatment] and ratio % ¼; constitutive: enrichment R 3, p % 0.001 [before and after treatment], ½ % ratio % 2). DHS-seq data were subsampled (5 million reads per sample) before processing and peak enrichments were quantile normalized. We evaluated the ChIP-seq enrichment specifically only at induced and repressed STARR-seq enhancers as described above. We used R (version 2.15.0) for all statistical analyses and plotting. For the analysis in Figures 2B and 2C and Figure S2C, genes were assigned to the closest TSS and in other cases we defined a gene locus as a region 5 kb upstream of a gene body, the gene body itself, and 2 kb downstream. SVM Predictions Support vector machine (SVM) predictions and sequence analyses were done as described elsewhere (Ya´n˜ez-Cuna et al., 2012), using the same set of known and predicted TF motifs. For motif analyses, we used three stringent sets of enhancers as described above (induced: enrichment R 7, p % 0.001 [after treatment] and ratio R 4; repressed: enrichment R 7, p % 0.001 [before treatment] and ratio % ¼; constitutive: enrichment R 7 [for S2 cells and R 3 for OSCs], p % 0.001 [before and after treatment], ½ % ratio % 2) and negative control regions with the same genomic distribution as induced enhancers, but not overlapping any STARR-seq enhancers. ACCESSION NUMBERS

ACKNOWLEDGMENTS We thank A. Bardet and M. Zabidi for help with the bioinformatics analysis and G. Stampfel, K. Schernhuber, and W. Lugmayr for technical support. Deep sequencing was performed at the CSF NGS Unit (http://www.csf.ac.at). D.S, L.M.B., M.R., and C.D.A. are supported by a European Research Council (ERC) starting grant (no. 242922) awarded to A.S. and the Stark group by the Austrian Science Fund (FWF, F4303-B09). Basic research at the IMP is supported by Boehringer Ingelheim GmbH. Received: August 13, 2013 Revised: December 11, 2013 Accepted: February 14, 2014 Published: March 27, 2014 REFERENCES Affolter, M., Pyrowolakis, G., Weiss, A., and Basler, K. (2008). Signal-induced repression: the exception or the rule in developmental signaling? Dev. Cell 15, 11–22. , q.M., Rath, M., and Stark, A. Arnold, C.D., Gerlach, D., Stelzer, C., Boryn (2013). Genome-wide quantitative enhancer activity maps identified by STARR-seq. Science 339, 1074–1077. Arnosti, D.N., and Kulkarni, M.M. (2005). Transcriptional enhancers: Intelligent enhanceosomes or flexible billboards? J. Cell. Biochem. 94, 890–898. Ashwell, J.D., Lu, F.W., and Vacchio, M.S. (2000). Glucocorticoids in T cell development and function*. Annu. Rev. Immunol. 18, 309–345. Ballare´, C., Castellano, G., Gaveglia, L., Althammer, S., Gonza´lez-Vallinas, J., Eyras, E., Le Dily, F., Zaurin, R., Soronellas, D., Vicent, G.P., and Beato, M. (2013). Nucleosome-driven transcription factor binding and gene regulation. Mol. Cell 49, 67–79. Banerji, J., Rusconi, S., and Schaffner, W. (1981). Expression of a beta-globin gene is enhanced by remote SV40 DNA sequences. Cell 27, 299–308. Barolo, S., and Posakony, J.W. (2002). Three habits of highly effective signaling pathways: principles of transcriptional control by developmental cell signaling. Genes Dev. 16, 1167–1181. Bernardo, T.J., Dubrovskaya, V.A., Jannat, H., Maughan, B., and Dubrovsky, E.B. (2009). Hormonal regulation of the E75 gene in Drosophila: identifying functional regulatory elements through computational and biological analysis. J. Mol. Biol. 387, 794–808. Bialecki, M., Shilton, A., Fichtenberg, C., Segraves, W.A., and Thummel, C.S. (2002). Loss of the ecdysteroid-inducible E75A orphan nuclear receptor uncouples molting from metamorphosis in Drosophila. Dev. Cell 3, 209–220. Biddie, S.C., John, S., Sabo, P.J., Thurman, R.E., Johnson, T.A., Schiltz, R.L., Miranda, T.B., Sung, M.-H., Trump, S., Lightman, S.L., et al. (2011). Transcription factor AP1 potentiates chromatin accessibility and glucocorticoid receptor binding. Mol. Cell 43, 145–155. Boyle, A.P., Davis, S., Shulha, H.P., Meltzer, P., Margulies, E.H., Weng, Z., Furey, T.S., and Crawford, G.E. (2008). High-resolution mapping and characterization of open chromatin across the genome. Cell 132, 311–322. Brodu, V., Mugat, B., Roignant, J.Y., Lepesant, J.A., and Antoniewski, C. (1999). Dual requirement for the EcR/USP nuclear receptor and the dGATAb factor in an ecdysone response in Drosophila melanogaster. Mol. Cell. Biol. 19, 5732–5742.

The NCBI GEO accession number for the deep sequencing and processed data reported in this paper is GSE47691. All data are also available at http:// www.starklab.org.

Brodu, V., Mugat, B., Fichelson, P., Lepesant, J.A., and Antoniewski, C. (2001). A UAS site substitution approach to the in vivo dissection of promoters: interplay between the GATAb activator and the AEF-1 repressor at a Drosophila ecdysone response unit. Development 128, 2593–2602.

SUPPLEMENTAL INFORMATION

Buecker, C., and Wysocka, J. (2012). Enhancers as information integration hubs in development: lessons from genomics. Trends Genet. 28, 276–284.

Supplemental Information includes three figures and three tables and can be found with this article online at http://dx.doi.org/10.1016/j.molcel.2014.02.026.

Cappabianca, L., Thomassin, H., Pictet, R., and Grange, T. (1999). Genomic footprinting using nucleases. Methods Mol. Biol. 119, 427–442.

Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 11

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell Hormone-Responsive Enhancer-Activity Maps

Deroo, B.J., and Korach, K.S. (2006). Estrogen receptors and human disease. J. Clin. Invest. 116, 561–570.

King-Jones, K., and Thummel, C.S. (2005). Nuclear receptors—a perspective from Drosophila. Nat. Rev. Genet. 6, 311–323.

Dobens, L., Rudolph, K., and Berger, E.M. (1991). Ecdysterone regulatory elements function as both transcriptional activators and repressors. Mol. Cell. Biol. 11, 1846–1853.

Kvon, E.Z., Stampfel, G., Ya´n˜ez-Cuna, J.O., Dickson, B.J., and Stark, A. (2012). HOT regions function as patterned developmental enhancers and have a distinct cis-regulatory signature. Genes Dev. 26, 908–913.

Falb, D., and Maniatis, T. (1992). Drosophila transcriptional repressor protein that binds specifically to negative control elements in fat body enhancers. Mol. Cell. Biol. 12, 4093–4103.

Lam, M.T.Y., Cho, H., Lesch, H.P., Gosselin, D., Heinz, S., Tanaka-Oishi, Y., Benner, C., Kaikkonen, M.U., Kim, A.S., Kosaka, M., et al. (2013). Rev-Erbs repress macrophage gene expression by inhibiting enhancer-directed transcription. Nature 498, 511–515.

Fletcher, J.C., Burtis, K.C., Hogness, D.S., and Thummel, C.S. (1995). The Drosophila E74 gene is required for metamorphosis and plays a role in the polytene chromosome puffing response to ecdysone. Development 121, 1455–1465.

Laval, M., Pourrain, F., Deutsch, J., and Lepesant, J.A. (1993). In vivo functional characterization of an ecdysone response enhancer in the proximal upstream region of the Fbp1 gene of D. melanogaster. Mech. Dev. 44, 123–138.

Flores, G.V., Duan, H., Yan, H., Nagaraj, R., Fu, W., Zou, Y., Noll, M., and Banerjee, U. (2000). Combinatorial signaling in the specification of unique cell fates. Cell 103, 75–85.

Lee, T.I., Johnstone, S.E., and Young, R.A. (2006). Chromatin immunoprecipitation and microarray-based analysis of protein location. Nat. Protoc. 1, 729–748.

Gauhar, Z., Sun, L.V., Hua, S., Mason, C.E., Fuchs, F., Li, T.-R., Boutros, M., and White, K.P. (2009). Genomic mapping of binding regions for the Ecdysone receptor protein complex. Genome Res. 19, 1006–1013.

Levine, M. (2010). Transcriptional enhancers in animal development and evolution. Curr. Biol. 20, R754–R763.

Gonsalves, S.E., Neal, S.J., Kehoe, A.S., and Westwood, J.T. (2011). Genomewide examination of the transcriptional response to ecdysteroids 20-hydroxyecdysone and ponasterone A in Drosophila melanogaster. BMC Genomics 12, 475. Hah, N., Danko, C.G., Core, L., Waterfall, J.J., Siepel, A., Lis, J.T., and Kraus, W.L. (2011). A rapid, extensive, and transient transcriptional response to estrogen signaling in breast cancer cells. Cell 145, 622–634. Hah, N., Murakami, S., Nagari, A., Danko, C.G., and Kraus, W.L. (2013). Enhancer transcripts mark active estrogen receptor binding sites. Genome Res. 23, 1210–1223. Halfon, M.S., Carmena, A., Gisselbrecht, S., Sackerson, C.M., Jime´nez, F., Baylies, M.K., and Michelson, A.M. (2000). Ras pathway specificity is determined by the integration of multiple signal-activated and tissue-restricted transcription factors. Cell 103, 63–74. Halfon, M.S., Grad, Y., Church, G.M., and Michelson, A.M. (2002). Computation-based discovery of related transcriptional regulatory modules and motifs using an experimentally validated combinatorial model. Genome Res. 12, 1019–1028. Hammachi, F., Morrison, G.M., Sharov, A.A., Livigni, A., Narayan, S., Papapetrou, E.P., O’Malley, J., Kaji, K., Ko, M.S.H., Ptashne, M., and Brickman, J.M. (2012). Transcriptional activation by Oct4 is sufficient for the maintenance and induction of pluripotency. Cell Rep. 1, 99–109. Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y.C., Laslo, P., Cheng, J.X., Murre, C., Singh, H., and Glass, C.K. (2010). Simple combinations of lineagedetermining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589.

Li, X.-Y., MacArthur, S., Bourgon, R., Nix, D., Pollard, D.A., Iyer, V.N., Hechmer, A., Simirenko, L., Stapleton, M., Luengo Hendriks, C.L., et al. (2008). Transcription factors bind thousands of active and inactive regions in the Drosophila blastoderm. PLoS Biol. 6, e27. Mullen, A.C., Orlando, D.A., Newman, J.J., Love´n, J., Kumar, R.M., Bilodeau, S., Reddy, J., Guenther, M.G., DeKoter, R.P., and Young, R.A. (2011). Master transcription factors determine cell-type-specific responses to TGF-b signaling. Cell 147, 565–576. Ogawa, S., Lozach, J., Benner, C., Pascual, G., Tangirala, R.K., Westin, S., Hoffmann, A., Subramaniam, S., David, M., Rosenfeld, M.G., and Glass, C.K. (2005). Molecular determinants of crosstalk between nuclear receptors and toll-like receptors. Cell 122, 707–721. Ong, C.-T., and Corces, V.G. (2011). Enhancer function: new insights into the regulation of tissue-specific gene expression. Nat. Rev. Genet. 12, 283–293. Poorey, K., Viswanathan, R., Carver, M.N., Karpova, T.S., Cirimotich, S.M., McNally, J.G., Bekiranov, S., and Auble, D.T. (2013). Measuring chromatin interaction dynamics on the second time scale at single-copy genes. Science 342, 369–372. Ra¨met, M., Manfruelli, P., Pearson, A., Mathey-Prevot, B., and Ezekowitz, R.A.B. (2002). Functional genomic analysis of phagocytosis and identification of a Drosophila receptor for E. coli. Nature 416, 644–648. Rehorn, K.P., Thelen, H., Michelson, A.M., and Reuter, R. (1996). A molecular aspect of hematopoiesis and endoderm development common to vertebrates and Drosophila. Development 122, 4023–4031. Riddihough, G., and Pelham, H.R. (1987). An ecdysone response element in the Drosophila hsp27 promoter. EMBO J. 6, 3729–3734.

Hodin, J., and Riddiford, L.M. (1998). The ecdysone receptor and ultraspiracle regulate the timing and progression of ovarian morphogenesis during Drosophila metamorphosis. Dev. Genes Evol. 208, 304–317.

Saito, K., Inagaki, S., Mituyama, T., Kawamura, Y., Ono, Y., Sakota, E., Kotani, H., Asai, K., Siomi, H., and Siomi, M.C. (2009). A regulatory circuit for piwi by the large Maf gene traffic jam in Drosophila. Nature 461, 1296–1299.

Hurtado, A., Holmes, K.A., Ross-Innes, C.S., Schmidt, D., and Carroll, J.S. (2011). FOXA1 is a key determinant of estrogen receptor function and endocrine response. Nat. Genet. 43, 27–33.

Segraves, W.A., and Hogness, D.S. (1990). The E75 ecdysone-inducible gene responsible for the 75B early puff in Drosophila encodes two new members of the steroid receptor superfamily. Genes Dev. 4, 204–219.

John, S., Sabo, P.J., Thurman, R.E., Sung, M.-H., Biddie, S.C., Johnson, T.A., Hager, G.L., and Stamatoyannopoulos, J.A. (2011). Chromatin accessibility pre-determines glucocorticoid receptor binding patterns. Nat. Genet. 43, 264–268.

Sempere, L.F., Sokol, N.S., Dubrovsky, E.B., Berger, E.M., and Ambros, V. (2003). Temporal regulation of microRNA expression in Drosophila melanogaster mediated by hormonal signals and broad-Complex gene activity. Dev. Biol. 259, 9–18.

Junion, G., Spivakov, M., Girardot, C., Braun, M., Gustafson, E.H., Birney, E., and Furlong, E.E.M. (2012). A transcription factor collective defines cardiac cell fate and reflects lineage history. Cell 148, 473–486.

Spitz, F., and Furlong, E.E.M. (2012). Transcription factors: from enhancer binding to developmental control. Nat. Rev. Genet. 13, 613–626.

Kent, W.J., Sugnet, C.W., Furey, T.S., Roskin, K.M., Pringle, T.H., Zahler, A.M., and Haussler, D. (2002). The human genome browser at UCSC. Genome Res. 12, 996–1006. Kim, T.-K., Hemberg, M., Gray, J.M., Costa, A.M., Bear, D.M., Wu, J., Harmin, D.A., Laptewicz, M., Barbara-Haley, K., Kuersten, S., et al. (2010). Widespread transcription at neuronal activity-regulated enhancers. Nature 465, 182–187.

12 Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc.

Stark, A., Lin, M.F., Kheradpour, P., Pedersen, J.S., Parts, L., Carlson, J.W., Crosby, M.A., Rasmussen, M.D., Roy, S., Deoras, A.N., et al.; Harvard FlyBase curators; Berkeley Drosophila Genome Project (2007). Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures. Nature 450, 219–232. Tata, J.R. (2002). Signalling through nuclear receptors. Nat. Rev. Mol. Cell Biol. 3, 702–710.

Please cite this article in press as: Shlyueva et al., Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin, Molecular Cell (2014), http://dx.doi.org/10.1016/j.molcel.2014.02.026

Molecular Cell Hormone-Responsive Enhancer-Activity Maps

Teytelman, L., Thurtle, D.M., Rine, J., and van Oudenaarden, A. (2013). Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins. Proc. Natl. Acad. Sci. USA 110, 18602–18607. Tsai, C.C., Kao, H.Y., Yao, T.P., McKeown, M., and Evans, R.M. (1999). SMRTER, a Drosophila nuclear receptor coregulator, reveals that EcRmediated repression is critical for development. Mol. Cell 4, 175–186. Ya´n˜ez-Cuna, J.O., Dinh, H.Q., Kvon, E.Z., Shlyueva, D., and Stark, A. (2012). Uncovering cis-regulatory sequence requirements for context-specific transcription factor binding. Genome Res. 22, 2018–2030.

Ya´n˜ez-Cuna, J.O., Kvon, E.Z., and Stark, A. (2013). Deciphering the transcriptional cis-regulatory code. Trends Genet. 29, 11–22. Zaret, K.S., and Yamamoto, K.R. (1984). Reversible and persistent changes in chromatin structure accompany activation of a glucocorticoid-dependent enhancer element. Cell 38, 29–38. Zhong, S., Joung, J.-G., Zheng, Y., Chen, Y.-R., Liu, B., Shao, Y., Xiang, J.Z., Fei, Z., and Giovannoni, J.J. (2011). High-throughput illumina strandspecific RNA sequencing library preparation. Cold Spring Harb. Protoc. 2011, 940–949.

Molecular Cell 54, 1–13, April 10, 2014 ª2014 Elsevier Inc. 13

Hormone-responsive enhancer-activity maps reveal predictive motifs, indirect repression, and targeting of closed chromatin.

Steroid hormones act as important developmental switches, and their nuclear receptors regulate many genes. However, few hormone-dependent enhancers ha...
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