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. 2020 Jan 28;9:e50670. doi: 10.7554/eLife.50670

GLI transcriptional repression regulates tissue-specific enhancer activity in response to Hedgehog signaling

Rachel K Lex 1,, Zhicheng Ji 2,, Kristin N Falkenstein 1,, Weiqiang Zhou 2, Joanna L Henry 1, Hongkai Ji 2, Steven A Vokes 1,
Editors: Marianne E Bronner3, Marianne E Bronner4
PMCID: PMC6986877  PMID: 31989924

Abstract

Transcriptional repression needs to be rapidly reversible during embryonic development. This extends to the Hedgehog pathway, which primarily serves to counter GLI repression by processing GLI proteins into transcriptional activators. In investigating the mechanisms underlying GLI repression, we find that a subset of GLI binding regions, termed HH-responsive enhancers, specifically loses acetylation in the absence of HH signaling. These regions are highly enriched around HH target genes and primarily drive HH-specific transcriptional activity in the mouse limb bud. They also retain H3K27ac enrichment in limb buds devoid of GLI activator and repressor, indicating that their activity is primarily regulated by GLI repression. Furthermore, the Polycomb repression complex is not active at most of these regions, suggesting it is not a major mechanism of GLI repression. We propose a model for tissue-specific enhancer activity in which an HDAC-associated GLI repression complex regulates target genes by altering the acetylation status at enhancers.

Research organism: Mouse

Introduction

Transcriptional repressors are instrumental in establishing developmental lineages and preventing improper gene expression. Long-term repression is accompanied by stable modifications to DNA and chromatin that prevent rapid transcriptional changes. In contrast, transient repression is rapidly reversible, providing a mechanism for controlling gene activation during the dynamic process of embryogenesis. This control is especially important for spatially restricting gene expression until signal transduction mechanisms alleviate repressor activity. This is exemplified by the Hedgehog (HH) signaling pathway, which ensures proper spatiotemporal regulation of its target genes through the coordination of bifunctional GLI proteins. Activation of HH signaling results in the processing of GLI proteins into transcriptional activators, which are otherwise proteolytically modified into truncated transcriptional repressors in the absence of HH ligand (Wang et al., 2000; Harfe et al., 2004).

The importance of balancing opposing GLI functions is illustrated in the limb bud, where Sonic Hedgehog (SHH) signaling alleviates GLI repression in a spatiotemporal manner to regulate growth of the digit-forming autopod. HH expression initiates in the posterior, distal limb, and forms a gradient along the posterior-anterior axis. Consequently, GLI activators are enriched in the posterior limb bud where many cells are exposed to HH ligands, while an inverse domain of GLI repressors in the anterior limb bud serve to spatially restrict the boundary of HH target gene expression (Wang et al., 2000; Ahn and Joyner, 2004). The presence of both GLI activator and GLI repressor domains makes the limb bud an ideal model for understanding the roles of GLI proteins in regulating HH-responsive transcription.

Interestingly, the limb bud is primarily a GLI repressor-driven system, as most transcriptional targets do not actually require GLI activator for transcription, but can be activated by loss of GLI repressor alone. This property of de-repression rather than activation is exemplified by Shh-/- limb buds (constitutive GLI repression, no GLI activation), which have a nearly complete absence of digits and a severe reduction in limb size. The phenotype is markedly improved in Shh-/-;Gli3-/- double mutants which lack SHH and the main transcriptional repressor, GLI3, and are therefore devoid of most or all GLI activity (both activation and repression) (Litingtung et al., 2002; te Welscher et al., 2002; Bowers et al., 2012). In particular, GLI de-repression is sufficient to activate most GLI target genes in the limb bud, suggesting that the primary role of the HH pathway is to alleviate GLI repression (Lewandowski et al., 2015). The transient nature of GLI repression represents a key mechanism for the dynamic transcriptional regulation of HH targets as HH induction rapidly inactivates GLI repression, resulting in transcription of targets within 4–9 hr of stimulation (Harfe et al., 2004; Panman et al., 2006; Visel et al., 2007).

The mechanisms underlying GLI repression are unknown but could in principle function either by excluding GLI activator binding or by recruiting co-repressors (Wang et al., 2010). Although the former category provides an attractive model for how GLI proteins might interpret gradients of HH ligand (Falkenstein and Vokes, 2014), it fails to account for the large number of GLI target genes that are fully activated upon de-repression in the absence of HH signaling, and likewise, GLI activator. In support of the latter category, several GLI co-repressors have been identified in various contexts, including Atrophin (Zhang et al., 2013), Ski (Dai et al., 2002) and tissue-specific transcription factors (Oosterveen et al., 2012; Hayashi et al., 2016). Members of the BAF chromatin remodeling complex have also been shown to generally regulate GLI transcriptional responses but it is unclear if they specifically regulate GLI repression (Jagani et al., 2010; Zhan et al., 2011; Jeon and Seong, 2016; Shi et al., 2016). Additional studies have described various interactions between Polycomb repression and HH signaling (Wyngaarden et al., 2011; Shi et al., 2014; Weiner et al., 2016; Deimling et al., 2018), indicating the possibility that PRC2 mediates aspects of GLI repression. Since mutations in candidate repressor complexes are pleiotropic, it has been challenging to determine if they directly mediate GLI repression, a challenge compounded by the dual roles of GLI proteins as transcriptional activators and repressors.

Using a genomic approach and the developing limb as a model, we sought to determine if GLI proteins repress HH target genes through altering the chromatin environment at GLI binding regions (GBRs). We hypothesized that GLI repressors regulate gene expression by inactivating enhancers. Consistent with this, we find that GLI repression regulates enhancer modification status, and thus, activity through the de-acetylation of Histone H3K27. This repression occurs independently of Polycomb activity. Enhancers regulated in this fashion correspond to known GLI limb enhancers, are highly enriched around HH target genes, and primarily drive tissue-specific enhancer activity within HH-specific expression domains. Based on these findings, we propose that GLI repressors inhibit gene expression by altering enhancer activity, providing an explanation for the labile nature of GLI repression.

Results

A subset of GLI binding regions is epigenetically regulated by HH signaling

Since most HH targets can be activated by loss of GLI repression, we hypothesized that enhancers may be activated by HH signaling when GLI repression is relieved. To test this, we first identified active GLI enhancers in the developing limb at embryonic day 10.5 (E10.5), when high levels of HH target gene expression are observed. We used an endogenously FLAG tagged Gli3 allele (Lopez-Rios et al., 2014; Lorberbaum et al., 2016) to identify GLI3 binding regions by ChIP-seq and then identified regions enriched for H3K27ac, a marker associated with active enhancers (Heintzman et al., 2007; Heintzman et al., 2009; Creyghton et al., 2010; Rada-Iglesias et al., 2011; Cotney et al., 2012). Altogether we identified 7,282 endogenous GLI3 binding regions (GBRs), with the majority of regions enriched for H3K27ac (83%; 6,064/7,282 GBRs) in wild-type (WT) limb buds which have active HH signaling (Figure 1—figure supplement 1A; Figure 1—source data 1). Nearly all nuclear GLI3 is present in the anterior half of the limb bud in the repressor form with little or no nuclear GLI3 present in the posterior half, consistent with previous findings (Wang et al., 2000) (Figure 1—source data 1B). Therefore, the GBRs identified in this study are likely to exclusively represent GLI3-repressor binding regions.

Next, we asked if HH signaling was required for the activation of GLI enhancers by performing ChIP-seq for H3K27ac in Sonic hedgehog (Shh) null E10.5 forelimbs, prior to overt phenotypes in Shh nulls, and comparing H3K27ac enrichment to that in WT limbs (Chiang et al., 2001) (Figure 1A; Figure 1—source data 2). Since Shh-/- forelimbs have constitutive GLI repression, we hypothesized that in the absence of HH signaling, GLI repressors may prevent activation of their enhancers. We found that most H3K27ac enriched regions were present in both WT and Shh-/- embryos (98.3%; 58,720/59,729 H3K27ac peaks); however a subset of 2,113 WT H3K27ac enriched regions had acetylation that was significantly reduced or completely lost in the absence of HH signaling (Figure 1—source data 2). We then asked whether those regions with reduced acetylation in the absence of HH signaling include GLI-bound enhancers by intersecting H3K27ac enrichment with the endogenous GBRs identified. We found that 94% of GBRs (5,715/6064 GBRs) with acetylation in WT limbs also retain H3K27ac in Shh-/- limb buds, which we have termed Stable GBRs (Figure 1C,D). GBRs that remain stably acetylated regardless of HH signaling likely function as active enhancers whose activity is not predominantly regulated by HH signaling. However, H3K27ac enrichment was reduced or lost in the absence of HH signaling in a smaller subset of GBRs, suggesting that GLI repressor may regulate the activity of this group of enhancers. Within this GBR class with HH-responsive acetylation, we identified populations of GBRs that had either significant reductions (termed HH-sensitive; n = 148) or a complete absence of H3K27ac enrichment (termed HH-dependent; n = 201) in Shh-/- limb buds (Figure 1B,C). The latter two categories are henceforth collectively referred to as HH-responsive GBRs. As H3K27ac is not exclusively localized to enhancers, we also examined the enrichment of histone H3K4me1, a general marker of primed and active enhancers, at these GBRs using publicly available data (ENCODE Project Consortium, 2012) (Figure 1—source data 3). In WT limb buds, 82% of HH-responsive GBRs are enriched for H3K4 mono-methylation, supporting that these regions are likely to act as enhancers (HH-sens: 123/148, 83%; HH-dep: 162/201, 81%).

Figure 1. Hedgehog signaling regulates acetylation of H3K27 at a subset of GLI binding regions.

(A) Pipeline for identifying different categories of GLI bound regions (GBRs). (B) Heatmap depicting differential H3K27ac enrichment in WT over Shh-/- limb buds for HH-responsive and Stable GBRs. (C) Classification of GBR categories from E10.5 GBRs with H3K27ac in WT limbs. (D-F). H3K27ac enrichment in WT and Shh -/- is shown across a representative genomic region near a Stable GBR (D), and biologically validated HH-responsive GBRs: a HH-dependent GBRs, GRE1, at the HH target gene Gremlin 1 (Grem1) (Li et al., 2014) (E) and HH-sensitive GBRs shown to regulate limb-specific expression of the HH target Ptch1 (Lopez-Rios et al., 2014) (F). (G) HH-dependent GBRs, HH-responsive GBRs and Stable GBRs are significantly enriched (2 kb upstream- 1 kb downstream of TSS) near HH target genes compared to randomly chosen genes (p=0, p=0 and p=0, respectively, permutation test based on 1000 permutations). (H) Proportional distribution of Stable and HH-responsive GBRs arounds transcription start sites (TSS), indicating significant enrichment of Stable GBRs at TSS compared to HH-responsive GBRs (p=2.55e-40, Fisher's exact test, two sided). (I) Both HH-dependent and HH-sensitive GBRs have significantly more GLI motifs than Stable GBRs (top)(p=2.2e-16 and p=8.00e-06; one-sided proportional test). HH-dependent and HH-sensitive GBRs containing GLI motifs have significantly higher quality of GLI motifs than Stable GBRs (Quality score; p=5.03e-13 and p=5.98e-08; one-sided Wilcoxon test) and significantly more motifs per GBR within HH-dependent GBRs than Stable GBRs (Quantity score; p=5.92e-06; one-sided Wilcoxon test). See Figure 1—figure supplement 1, Figure 1—source data 1, Figure 1—source data 2, Figure 1—source data 3, Figure 1—source data 4.

Figure 1—source data 1. Endogenous GLI3-Flag ChIP-seq analyzed data and called peaks.
GLI3 binding regions with called peaks with a false discovery rate (FDR) < 0.05 from two biological replicates of E10.5 (32–35S) forelimbs. Rank ordered coordinates, peak length, log2 fold change (log2FC) and FDR are listed for each peak.
elife-50670-fig1-data1.xlsx (346.8KB, xlsx)
Figure 1—source data 2. WT vs Shh-/- H3K27ac ChIP-seq analyzed data and called peaks.
H3K27ac called peaks with a FDR < 0.05 from two biological replicates from WT and Shh-/- E10.5 forelimbs. For each peak, the assigned Peak ID, coordinates, peak type, fold change normalized to input for WT and Shh-/- samples and fold change of WT over Shh-/- are listed. Additional tabs include sorted datasets for sub-classifications. Tabs containing GBRs indicate intersections with GLI binding regions.
Figure 1—source data 3. H3K4me1 ChIP-seq analyzed data and called peaks from GSE86690.
H3K4me1 called peaks with a false discovery rate (FDR) < 0.05 from two biological replicates of E10.5 WT forelimbs. Note that this is a reanalysis of a publicly available ENCODE dataset (see methods).
Figure 1—source data 4. Motifs uncovered from HH-responsive enhancers.
Table showing the top 20 motifs uncovered from de novo motif analysis on HH-responsive GBRs. The enrichment is relative to matched genomic controls. Note that ‘HH_resp_2’ is the only motif with an enrichment value of greater than two and corresponds with a known GLI binding motif.

Figure 1.

Figure 1—figure supplement 1. Nuclear localization of GLI3 and properties of GLI binding regions.

Figure 1—figure supplement 1.

(A) Intersection of endogenous GLI3 binding and H3K27ac in E10.5 WT limb buds. (B) Western blots from anterior and posterior E10.5 limb buds indicating the distribution of endogenous GLI3-FLAG in cytoplasmic and nuclear fractions (C = cytoplasmic fraction, N = nuclear fraction; Ant = Anterior forelimb, Post = Posterior forelimb) (n = 3). (C) Hedgehog-responsive enhancers that are not bound by GLI are clustered near GLI binding regions. Box plot indicates the proximity of HH-responsive H3K27ac peaks that are not bound by GLI to either HH-Responsive GBRs or Stable GBRs compared to random peaks. For both HH-responsive and stable GBRs, the number of HH-Responsive non-GBR H3K27ac peaks is significantly larger than the number of random regions (Wilcoxon-test p-value=0). (D) HH-responsive peaks not bound by GLI3 are clustered together. The genome was split into 100,000 base-pair non-overlapping windows and the number of HH-responsive H3K27ac peaks that are not bound by GLI3 were counted as well as the number of random peaks. Only windows that overlapped with at least one HH-responsive H3K27ac peak or random peak were considered. The two counts are significantly different (Wilcoxon-test p-value=0). The dark black line indicates the median. The lower boundary of the box indicates the first quantile, while the upper boundary of the third box is the third quantile. The circles indicate outliers. (E) Box plot showing the conservation scores for different classes of GBRs. The conservation scores correspond to phastCons values linearly scaled from 0 to 255. HH-responsive GBRs have significantly lower conservation scores than stable GBRs (p-value=0.0001134492, one sided Wilcoxon test). None of the other pairs of GBRs are significantly different from each other. ‘Coding regions’ represent conservation scores for all protein coding genes in the mouse mm10 genome while ‘Random regions’ represent conservation scores for a set of 1000 random genomic loci that do not overlap with any gene. The dark black line indicates the median. The lower boundary of the box indicates the first quantile, while the upper boundary of the third box is the third quantile. The circles indicate outliers.

Hedgehog-responsive GBRs are enriched near Hedgehog target genes

To determine if HH-responsive GBRs are associated with HH target genes, we examined biologically validated GLI enhancers in the Gremlin and Ptch1 loci that mediate limb-specific transcription of these HH targets and found that they are among the HH-responsive class of GBRs (Figure 1E,F) (Vokes et al., 2008; Zuniga et al., 2012; Li et al., 2014; Lopez-Rios et al., 2014). This suggests that HH-responsive enhancers may regulate limb-specific gene expression in response to HH signaling. Consistent with this possibility, we found that HH-responsive GBRs are highly enriched around the TSS (2 kb upstream to 1 kb downstream) of genes that have reduced expression in Shh-/- limb buds (Lewandowski et al., 2015). In contrast, Stable GBRs have minimal, albeit still significant enrichment around HH target genes (p=0, permutation test; Figure 1G).

We observed many HH-responsive H3K27ac regions that change acetylation status in response to HH signaling but are not bound by GLI3. This prompted us to ask asked if these regions cluster near GBRs. HH-responsive non-GLI binding regions cluster together and are significantly enriched around HH-responsive GBRs, and to a lesser extent, near Stable GBRs (Figure 1—figure supplement 1C,D). We conclude that HH-responsive GBRs cluster with other HH-responsive regulatory regions, and are strongly associated with HH target genes, supporting their role in driving gene expression in response to HH signaling during limb development.

HH-responsive GBRs are distal enhancers containing high quality GLI motifs

Although Stable GBRs are not highly enriched at HH target genes, 62% of them (3,544/5,715) are located in close proximity to the promoters of genes (2 kb upstream to 1 kb downstream of TSS), compared to 26% (91/349) of HH-responsive GBRs (Figure 1H). Most promoter-associated Stable GBRs (90%; 3,190/3,544) are found at promoters associated with CpG islands (defined as a TSS with a CpG region within 5 kb upstream to 2.5 kb downstream), a quality typically associated with housekeeping genes, and genes that tend to be more broadly expressed and less tissue-specific (Zhu et al., 2008). To examine how different classes of GBRs might be differentially regulated, we examined their GLI binding motifs. A significantly higher percentage of HH-dependent and HH-sensitive GBRs contain GLI motifs compared to Stable GBRs (69.7% HH-dep., 57.4% HH-sens., 39.5% Stable). HH-dependent and HH-sensitive GBRs also contain a higher density (1.51 HH-dep., 1.47 HH-sens., 1.27 Stable) and higher quality of GLI motifs compared to Stable GBRs (5.75 HH-dep., 5.56 HH-sens., 4.88 Stable)(Figure 1I). Interestingly, we did not uncover high levels of enrichment of other motifs using de novo motif analysis (Figure 1—source data 4). Additionally, Stable GBRs are slightly more conserved than HH-dependent, but not HH-sensitive GBRs (see Discussion) (Figure 1—figure supplement 1E).

The Polycomb repressor complex does not regulate most GLI enhancers

GLI activators have been shown to recruit demethylases that remove H3K27me3, a hallmark of the Polycomb repressor complex (PRC2) to promote transcriptional activation of several HH target genes, most notably Gli1 and Ptch1 (Margueron and Reinberg, 2011; Shi et al., 2014; Lorberbaum et al., 2016). If PRC2 is recruited by GLI repressors, there should be enrichment of H3K27me3 at HH-responsive enhancers in Shh-/-, where maximal levels of GLI repression would lead to recruitment of PRC2 and thus methylation at these enhancers. Contrary to this prediction, we identified a minimal number of HH-responsive GBRs enriched for H3K27me3 in E10.5 Shh-/- limb buds (31/349 GBRs; Figure 2A–C, Figure 2—source data 1). As reported for MEFs (Shi et al., 2014), these methylated GBRs include the pathway target Gli1 in addition to other pathway target genes such as Ptch1 and Ptch2 (Figure 2B). In contrast, most HH-responsive GBRs (318/349) and signature target gene promoters (14/22) lack enrichment of H3K27me3 in the absence of HH signaling (Figure 2C; Figure 2—figure supplement 1; Figure 2—source datas 1 and 2 ). We conclude that while the PRC2 complex has the potential to regulate a small number of HH pathway target genes, it is not the primary mechanism by which GLI repressors prevent target gene expression.

Figure 2. Most HH-responsive GBRs are not regulated by Polycomb repression and retain markers of poised enhancers.

(A) Chart depicts HH-responsive GBRs that contain enrichment for the PRC2 marker H3K27me3 in Shh-/- limb buds (n = 2). (B) Tracks depicting a HH-responsive region in Gli1 with differential H3K27ac enrichment in WT and Shh-/- limb buds and H3K27me3 enrichment in Shh-/- limb buds. (C) Tracks depicting a representative HH-dependent GBR that also lacks H3K27me3. (D) Scatter plot for H3K4me2 enrichment of Stable and HH-responsive GBRs from WT and Shh-/- limb buds (n = 2). No GBRs show significant changes in di-methylation of H3K4 between WT and Shh-/-. (E) Representative track showing comparable levels of H3K4me2 enrichment for a HH-responsive GBR in WT and Shh-/- limb buds. (F) Quantitative-PCR assays indicating H3K4me1 ChIP enrichment in WT and Shh-/- limb buds at HH-dependent GBRs (n = 2). See Figure 2—figure supplement 1, Figure 2—source data 1, Figure 2—source data 2, Figure 2—source data 3.

Figure 2—source data 1. Shh-/- H3K27me3 ChIP-seq analyzed data and called peaks.
H3K27me3 called peaks with a FDR < 0.05 from two replicates of Shh-/- E10.5 forelimbs. For each peak, the assigned Peak ID, coordinates, log2 fold change normalized signal to input. Additional tab includes H3K27me3 peaks that overlap with GLI3 binding regions; the GBR sub-classifications are specified.
elife-50670-fig2-data1.xlsx (387.1KB, xlsx)
Figure 2—source data 2. Hedgehog responsive genes with H3K27me3 enrichment.
The first column indicates genes previously identified as differentially expressed between Shh-/- and WT E10.5 limb buds (Lewandowski et al., 2015). The second column indicates the fold enrichment of H3K27me3 at the promoter compared to Input with the adjusted P-value indicated in the third column. The fourth column indicates whether the gene has a HH-dependent GBR (indicated by one and yellow shading) within the same presumptive TAD (Dixon et al., 2012). There are 22 HH-dependent target genes out of 80 HH-responsive genes.
Figure 2—source data 3. WT vs Shh-/- H3K4me2 ChIP-seq analyzed data and called peaks.
H3K4me2 called peaks with a FDR < 0.05 from two replicates from WT and Shh-/- E10.5 forelimbs. For each peak, the assigned Peak ID, coordinates, peak type, fold change normalized to input for WT and Shh-/- samples and fold change of WT over. Shh-/- are listed. Additional tabs include sorted files for each peak type. Under the ‘GLI3 binding’ column, ‘TRUE’ implies overlap with a GBR, while ‘FALSE’ indicates no overlap.

Figure 2.

Figure 2—figure supplement 1. H3K27Me3 enrichment at the promoters of GLI target genes.

Figure 2—figure supplement 1.

(A) Schematic illustrating a hypothetical mechanism by which GLI repressors bound to distal enhancers could facilitate the deposition of PRC2-marked H3K27Me3 at the promoters of target genes. (B) H3K27Me3 enrichment within the promoters of 22 HH responsive genes that also have HH-dependent GBRs (Figure 2—source data 2) was determined as for the enhancers except that the reads were summed in gene promoters instead of peak regions within a window spanning from 1500 bp upstream to 500 bp downstream of the transcriptional start site. H3K27Me3 enrichment was present in the promoters of 8/22 target genes.

Hedgehog signaling does not regulate other histone modifications at enhancers

We considered two possible mechanisms by which GLI repression could regulate H3K27ac enrichment in response to HH signaling: first, GLI repression could cause large-scale modifications to chromatin at enhancers resulting in an overall loss of their identity as enhancers. Alternatively, GLI repressors could regulate H3K27ac specifically. To address the first mechanism, we asked if HH regulates H3K4me2, another histone modification enriched at active enhancers and most promoters (Ernst et al., 2011; Pekowska et al., 2011; Wang et al., 2014). Consistent with H3K4me2 being enriched at promoters and our finding that Stable GBRs are enriched around promoters, we find H3K4 di-methylation at 73% of Stable GBRs (4,172/5,715), while only 26% of HH-responsive GBRs (91/349) which are less enriched around promoters. None of the GLI-bound H3K4me2 enriched regions had significant reductions in H3K4me2 in Shh-/- limbs compared to WT controls (Figure 2D,E). Furthermore, essentially all peaks remained unchanged between the two genotypes, where only 12 peaks were reduced in Shh-/- limbs, none overlapping with GLI binding regions or non-GBR HH-responsive peaks (Figure 2—source data 3).

H3K4me2 marked most Stable GBRs, but only a subset of HH-responsive GBRs which are primarily located within 2 kb upstream to 1 kb downstream of TSS (79% (72/91) of H3K4me2+ HH-responsive GBRs are near promoters). Since we found that most HH-responsive GBRs in wildtype limb buds are enriched for H3K4me1 (see results above), we asked if this mark was altered at HH-responsive GBRs in response to HH signaling. We performed ChIP on WT and Shh-/- limb buds and assessed enrichment of H3K4me1 at several HH-responsive GBRs by quantitative PCR, selecting intergenic regions that would not overlap with promoters (regions are at least 7 kb from the nearest TSS). All tested regions retained H3K4me1 enrichment in Shh-/- limb buds (Figure 2F). We conclude that HH-responsive regions retain enrichment of other active or poised enhancer marks, suggesting that HH signaling and GLI repression specifically regulate H3K27ac enrichment at these regions.

Chromatin at HH-responsive GBRs compacts in the absence of Hedgehog

The dynamic acetylation of HH-responsive GBRs, yet unaltered methylation of H3K4 in Shh-/- limb buds are properties consistent with ‘poised’ enhancers, which retain H3K4me1 and accessible chromatin in the absence of H3K27ac (Heintzman et al., 2009; Creyghton et al., 2010; Rada-Iglesias et al., 2011). Therefore, if HH-responsive enhancers are not active but ‘poised’ in the absence of HH, we predicted that chromatin accessibility would be unchanged in response to HH signaling. Using ATAC-seq to measure regions of open chromatin, we compared the accessibility of GBRs between WT and Shh-/- posterior limb buds, a fraction providing a more homogenous WT population of cells exposed to HH signaling (Figure 3A; Figure 3—source data 1) (Buenrostro et al., 2013; Buenrostro et al., 2015). Overall, in HH stimulated WT limbs, 87% of Stable GBRs (4,978/5,715) are accessible, while only 66% of HH-responsive GBRs (232/349) are accessible, suggesting a more restricted accessibility of HH-responsive GBRs even in WT conditions (Figure 3B–C). To determine if these regions are likely to be enhancers, we analyzed the co-enrichment of the enhancer markers H3K4me1 and H3K4me2 at ATAC accessible (ATAC+) and inaccessible (ATAC-) HH-responsive GBRs. 93.5% (217/232) of ATAC+ regions are co-enriched with H3K4me1/2 while 72% (84/117) of ATAC- regions are co-enriched with H3K4Me1/2. These results suggest that most of the ATAC- regions are likely to correspond to real enhancers though at a somewhat reduced frequency compared to ATAC+ regions. Contrary to expectations for a poised enhancer, both HH-sensitive and HH-dependent GBRs have significantly reduced accessibility compared to Stable GBRs in the absence of HH signaling, with the majority of HH-responsive GBRs being more compact in Shh-/- compared to wild-type limbs (Figure 3D–F). Overall, we conclude that HH-responsive GBRs are less accessible than Stable GBRs, with access being further restricted in Shh-/- limb buds, which have constitutive GLI repression.

Figure 3. Chromatin accessibility is reduced in the absence of Hedgehog signaling.

Figure 3.

(A) ATAC-seq pipeline for single pairs of dissected posterior halves of forelimbs (n = 2). ATAC peaks, signifying accessible chromatin regions were intersected with Stable GBRs and HH-responsive GBRs. (B) Many HH-responsive GBRs that are accessible in WT limb buds are inaccessible Shh-/- limb buds, while the accessibility of Stable GBRs remains largely unchanged. (C) Plot of log2 normalized signal in chromatin accessibility in WT limbs indicating that Stable GBRs are more accessible than HH-dependent and HH-responsive GBRs (p=3.98e-19, p=9.21e-11; Wilcoxon rank sum test). Each data point represents a single GBR and red bars indicate the median, upper and lower quartiles. D-E. Representative ATAC-seq peaks showing lack of accessibility in Shh-/- limb buds at HH-responsive GBRs (D), but not in Stable GBRs (E, F) Plot of log2 fold changes in chromatin accessibility in the presence and absence of HH signaling. HH-responsive GBRs are significantly less accessible than Stable GBRs (Stable vs. HH-sensitive. p=0.001; Stable vs. HH-dependent p=4.99e-09; Wilcoxon rank sum test). See Figure 3—source data 1.

Figure 3—source data 1. WT vs Shh-/- ATAC Seq analyzed data and called peaks.
Coordinates for all ATAC peaks in the WT group that overlap with GBRs are listed. ‘Shh_ATAC_peak’ identifies the corresponding id# for that peak in the Shh-/- data, and if a peak is not present in the Shh-/- samples, it is marked as NA. A column for each GBR type identifies which GBR type a given ATAC peak overlaps with. The number indicates the peak ID. If a peak region does not overlap with the type of peak in that list, it will be marked as NA. The normalized log2 transformed signals are shown for each sample in addition to the ‘average’ signal across all samples. The ‘t’ statistic calculates the difference in signals between WT and Shh-/- by taking into consideration fold-change and variance among samples. A positive t statistic values indicate a peak is more accessible in WT than Shh-/- and a negative t statistic indicates higher accessibility in Shh-/-. The ‘p.value’ is obtained from a moderated t-test using limma. The ‘p.value.adj’ is the adjusted p-value (FDR) using the Benjamini-Hochberg procedure.

De-repression is the dominant mechanism regulating GLI enhancer activation

The presence of multiple GLI proteins and their bifunctional roles as both transcriptional activators and repressors has made it challenging to determine how HH genes are primarily regulated. To test the roles of activator and repressor on enhancers, we performed H3K27ac ChIP on Shh-/-;Gli3-/- limb buds (devoid of GLI activators and most GLI repressors). We hypothesized that loss of H3K27ac at most HH-responsive enhancers in the absence of HH signaling is due to constitutive GLI repression preventing acetylation of GLI enhancers. Thus, in Shh-/-;Gli3-/- limbs, we predicted H3K27ac should be maintained at HH-responsive enhancers. Alternatively, if GLI activator is required, H3K27ac would remain absent or reduced as it does in Shh-/- limbs (Figure 1A).

To overcome the reduced tissue available for ChIP samples, we optimized a ‘MicroChIP’ approach to allow ChIP-seq on single pairs of limb buds and assessed H3K27ac enrichment at GLI enhancers in E10.5 Shh-/-;Gli3-/- limb buds (Figure 4A; Figure 4—source data 1). As anticipated, there was reduced signal compared to our standard protocol, however we were still able to detect many of the HH-responsive GBRs (59%; 207/349) and most Stable GBRs (91%; 5,211/5,715). Consistent with expectations, HH-responsive GBRs associated with Gli1 and Ptch1, which require GLI activation (Litingtung et al., 2002; te Welscher et al., 2002), had greatly reduced H3K27ac enrichment in the double mutants along with a small number of additional GBRs (24 total; Figure 4B,D,E). However, consistent with a GLI repression-driven model, most HH-responsive GBRs retained or increased H3K27ac enrichment in the absence of both GLI activator and repressor (88%; 183/207; Figure 4C–E). Despite being unchanged in Shh-/- limbs, Stable GBRs had slight but significant increases in H3K27ac enrichment (Figure 4F), indicating that on a population level, some of these regions respond to GLI repression (see Discussion).

Figure 4. GLI de-repression activates most HH-responsive enhancers.

Figure 4.

(A) Shh-/-;Gli3-/- H3K27ac ‘MicroChIPs’ on single pairs of E10.5 forelimbs (33–34S) Shh-/-;Gli3-/- and WT littermate controls (n = 2, respectively). (B) A HH-responsive GBR near Gli1 which requires GLI activator for H3K27ac enrichment. (C) Representative examples of HH-responsive GBRs, activated by loss of GLI repressor that do not require GLI activator. (D-F) Scatter plot of H3K27ac enrichment of HH-dependent, HH-sensitive and Stable GBRs in WT and Shh-/-;Gli3-/- limbs. Each dot represents a single GBR. The p-values indicate a significant enrichment of acetylation in Shh-/-;Gli3-/- among all GBR classes (p-values: HH-dependent = 2.26e-08, HH-sensitive = 5.41e-11, Stable = 3.4e-185;Wilcoxon-rank sum tests). (G-H) E10.5 WT and Gli3-/- limb buds were dissected into anterior and posterior halves as indicated and selected HH-dependent GBRs were tested for H3K27ac enrichment by quantitative PCR in each fraction (n = 4). HH-dependent GBRs have higher ratios of posterior to anterior H3K27ac enrichment in WT limb buds (G), while many HH-dependent GBRs have equal ratios of posterior to anterior H3K27ac enrichment in Gli3-/- limb buds (H) (n = 3) (asterisks indicate p<0.05, paired T-test). See Figure 4—source data 1.

Figure 4—source data 1. WT vs Shh-/-;Gli3-/- H3K27ac MicroChIP-seq analyzed data and called peaks.
H3K27ac called peaks with a FDR < 0.05 from two replicates of WT, Shh-/- and Shh-/-;Gli3-/- E10.5 (33–34S) forelimbs. Separate tabs for each genotype include peak coordinates and log2 fold change over input. Additional tabs include a peak summary and differential analysis of WT vs. Shh-/-;Gli3-/-. Differential analysis tab lists peak coordinates, peak type, fold change normalized to input for WT and Shh-/-;Gli3-/- samples and fold change of WT over Shh-/-;Gli3-/-.
Figure 4—source data 2. MicroChIP H3K27ac enrichment in Shh-/-;Gli3-/- limb buds at HH-responsive GBRs with H3K27me3 in Shh-/- limbs.
List of 31 HH-responsive GBRs with H3K27me3 enrichment in Shh-/- limb buds and their enrichment of H3K27ac in Shh-/-;Gli3-/-. 20 of the 31 regions were detected in the H3K27ac MicroChIP analyses, those not detected are noted. For the 20 regions detected, they are classified as having H3K27ac in Shh-/-;Gli3-/- as ‘present/increased’ or ‘absent/decreased’ compared to WT controls.

In a parallel series of experiments, we noted that HH-responsive GBRs have higher levels of H3K27ac enrichment in posterior limb halves, where HH is active, compared to anterior limb halves, which have little exposure to HH and are dominated by GLI repression (Figure 4G). This contrasts with Gli3-/- limb buds, where H3K27ac levels in anterior halves are comparable to those in posterior halves in many GBRs, as both domains lack GLI repression (Figure 4H). Together these results strongly support a GLI repressor centric mode of regulation where GLI de-repression is responsible for activation of most GLI limb enhancers. We conclude that GLI activator does not mediate acetylation levels at most HH-responsive GBRs.

HDACs dynamically regulate H327ac enrichment at HH-responsive enhancers

The simplest interpretation of the above results is that GLI repressor regulates the activity of histone deacetylases (HDACs) at HH-responsive GBRs, in which loss of an HDAC-GLI repressor complex leads to acetylation. To test this, we cultured limb buds in the presence of the HDAC inhibitors FK228 (Furumai et al., 2002) or SAHA for 2 hr. As expected, there were greatly upregulated levels of H3K27ac within two hours of treatment (Figure 5—figure supplement 1A,B). We then dissected the anterior halves of limb buds cultured in control or HDAC inhibitor-containing media and compared the levels of H3K27ac enrichment at HH-responsive GBRs previously shown to have enriched H3K27ac levels in posterior limb halves (+HH, no GLI repression) (Figure 4G). Inhibition of HDACs with both FK228 and SAHA resulted in increased acetylation at HH-responsive enhancers compared to untreated control anterior limb buds (Figure 5A). The increased enrichment of H3K27ac acetylation in HDAC-inhibited anterior limb buds was comparable to that seen in posterior limb buds (Figure 4G). HDACs could regulate H3K27ac activity in a GLI-responsive fashion through a variety of different mechanisms including direct interactions with responsive GBRs, potentially mediated by a repression complex including GLI3 proteins and HDACs. We asked if GBRs were bound by HDACs, focusing on HDAC1, which along with HDAC2 is preferentially inhibited by FK228 (Furumai et al., 2002). We identified HDAC1 binding regions in E11.5 limb buds by CHIP-seq and intersected them with GBRs. 78% (4,109/5,282) of stable GBRs and 41% (144/349) of HH-responsive GBRs overlapped with HDAC1 peaks (Figure 5B–D), consistent with a possible role for HDAC1 in regulating H3K27ac levels. We conclude that GLI repressors regulate H3K27ac levels at HH-responsive GBRs through HDACs (see discussion).

Figure 5. HDACs regulate H3K27ac at HH-responsive GBRs.

(A) Inhibition of HDACs using 250 nM of FK228 or 20 μM SAHA in cultured limb buds for two hours resulted in significant increases of H3K27ac enrichment at HH-dependent GBRs from anterior cultured limb buds compared to DMSO control anterior limbs (FK228 n = 4; SAHA n = 5; asterisks indicate p<0.05, paired T-test). (B) HDAC1 binding at Stable and HH-responsive GBRs (n = 4). (C-E) HDAC1 at GLI3 binding regions, shown at a representative Stable GBR (C), limb-specific HH-sensitive GBRs near the HH target genes Ptch12 (Lopez-Rios et al., 2014) (D), and a HH-dependent GBR, (region also shown in Figure 4C) (E, D) See Figure 5—figure supplement 1, Figure 5—source data 1.

Figure 5—source data 1. HDAC1 ChIP-seq analyzed data and called peaks.
HDAC1 binding regions with called peaks with a false discovery rate (FDR) < 0.05 from four biological replicates of E11.5 (40–44S) pooled forelimbs and hindlimbs. Rank ordered coordinates, peak length, log2 fold change (log2FC) and FDR are listed for each peak.

Figure 5.

Figure 5—figure supplement 1. H3K27ac is increased upon HDAC inhibition.

Figure 5—figure supplement 1.

Western blot of cultured limb buds treated with 0.4% DMSO or the HDAC inhibitors, FK228 (250 nM, n = 2) (A) or SAHA (20 μM, n = 2) (B), for 2 hr showing increased overall levels of H3K27 acetylation. Approximately, 20 pairs of E10.5 forelimbs were lysed and 15 μg of protein was loaded on gel. Note that these are whole limb buds rather than anterior and posterior fractions shown in Figure 5.

HH-responsive GBRs have increased tissue-specificity compared to Stable GBRs

Having identified distinct classes of GBRs that respond differently to HH signaling, we next addressed the biological significance of these properties. To this end, we used the VISTA enhancer database to identify a total of 305 Stable and 23 HH-responsive GBRs that had been tested for enhancer activity in transgenic embryos (Visel et al., 2007). While nearly half of each class have enhancer activity in the limb, HH-responsive GBRs tend to drive activity specific to the HH-responsive posterior limb bud, while Stable GBRs tend to have activity throughout the limb or regions that are not responsive to HH (Figure 6A,B) (Ahn and Joyner, 2004; Probst et al., 2011; Lewandowski et al., 2015). Additionally, HH-responsive enhancers are active more specifically within the limb (drive expression in an average of 1.9 tissues) while Stable GBRs are more broadly active throughout the embryo (drive expression in an average of 2.9 tissues; p<0.01; Figure 6C; Figure 6—source data 1). While all GBRs examined in the VISTA database with limb activity are by definition enriched for H3K27ac, 91% of HH-responsive GBRs and 95% of Stable GBRs are also enriched for H3K4me1. Additionally, all GBRS are enriched for at least two markers of enhancers (H3K27ac, H3K4me1, H3K4me2, ATAC) while most are enriched for 3–4 of these markers (67% HH-responsive GBRs; 93% Stable GBRs) (Figure 6D,E).

Figure 6. Hedgehog-responsive GBRs have tissue-specific enhancer activity within HH-specific domains.

Figure 6.

(A) Enhancers with annotated limb activity in VISTA corresponding to representative HH-responsive GBRs (bottom) and Stable GBRs (top) with limbs magnified and outlined in insets. Limb buds containing HH-specific domains of enhancer activity are indicated by an asterisk. (B) Chart indicating total number of VISTA enhancers tested for HH-responsive and Stable GBRs, the numbers of enhancers for each category and their limb enhancer activity. (C) Chart delineating the percentage of HH-responsive and Stable limb enhancers that drive expression in one or more tissues. (D) Venn Diagram of enhancer marks H3K27ac, H3K4me1, H3K4me2 and ATAC, in Stable and HH-responsive GBRs tested in VISTA that drive expression in the limb. GBRs, are by definition are marked by H3K27ac. (E) Enrichment of enhancer markers at a representative HH-responsive GBR tested in VISTA (hs280, Figure 6A). (F) Schematic of NIH3T3 H3K27ac ChIP treated with and without the HH agonist purmorphamine (+HH) and the activity of representative HH-responsive and Stable limb GBRs in response to HH activation in limb and NIH3T3 cells (n = 2). (G) Graph indicating how the acetylation status of HH-responsive and Stable limb GBRs responds to HH signaling in HH-responsive NIH3T3 cells. See Figure 6—source data 1; Figure 6—source data 2.

Figure 6—source data 1. Stable and HH-responsive GLI binding regions with limb enhancer activity in the VISTA dataset.
Tab 1. Columns indicate VISTA enhancer IDs, coordinates, number of tissues with limb enhancer activity as annotated by the VISTA database (Visel et al., 2007) and its corresponding GBR category. Tabs 2–5. Normalized signal and called peaks for H3K27ac, ATAC, H3K4me1 and H3K4me2 in WT, and Shh-/- limbs if applicable, is listed for all HH-responsive GBRs (Tab 2- normalized signal; Tab 3-called peaks) and Stable GBRs (Tab 4- normalized signal, Tab 5-called peaks) that were shown to drive limb activity, as tested in the VISTA database. For called peaks in Tabs 3, 5, ‘NO’ denotes not a significantly called peak, ‘YES’ denotes a called peak.
Figure 6—source data 2. NIH3T3 H3K27ac ChIP-seq analyzed data and called peaks.
H3K27ac called peaks with a FDR < 0.05 from two replicates of purmorphamine (‘pm’) treated or DMSO control NIH3T3 cells. For each peak, the assigned Peak ID, coordinates, peak type, fold change normalized to input for purmorphamine treated and control samples, and fold change of purmorphamine treated over control are listed. Additional tabs include sorted files for each peak type.

These results suggest that Stable GBRs act as general enhancers that drive expression in multiple tissues, while HH-responsive GBRs mediate tissue-specific expression. To test this in another biological context, we treated HH-responsive NIH3T3 cells with and without the HH agonist purmorphamine, identified H3K27ac enriched regions by ChIP-Seq, and assessed the H3K27 acetylation status of different classes of limb GBRs. Strikingly, only 12% (42/349 GBRs) of HH-responsive limb GBRs are acetylated in response to HH signaling in NIH3T3 cells. An additional 18% (63/349 GBRs) of HH-responsive limb enhancers have stable acetylation in NIH3T3 cells, while most lack any activity. In contrast, 70% (4,001/5715) of Stable GBRs in the limb are still active in NIH3T3 cells in both untreated and HH stimulated cells (Figure 6F,G; Figure 6—source data 2). We conclude HH-responsive GBRs are tissue specific enhancers that mediate HH signaling, while Stable GBRs have broadly expressed enhancer activity.

Discussion

We find that a subset of GLI-bound regions have chromatin modifications that change in response to HH signaling. These regions are enriched for multiple enhancer markers and have enhancer activity in transgenic embryos, suggesting that they mark a population of enhancers. However, compared to WT embryos, these regions have reduced or absent levels of histone H3K27 acetylation in Shh-/- embryos, indicating a loss of enhancer activity. Many previously validated GLI limb enhancers have HH-responsive H3K27ac, including those regulating Grem1, Ptch1 and Gli1 (Figure 1E,F) (Vokes et al., 2008; Zuniga et al., 2012; Li et al., 2014; Lopez-Rios et al., 2014). Moreover, HH-responsive GBRs are highly enriched near HH target genes while the much larger class of Stable GBRs are not (Figure 1G). This suggests that HH target gene regulation is primarily mediated through HH-responsive GBRs. The discovery of this response provides important information about the mechanism of GLI repression. It also provides a predictive tool for identifying enhancers regulating HH target genes in other biological contexts.

We propose a model in which GLI repression primarily regulates enhancer activity through deacetylation of histone H3K27. Because H3K4me1 and H3K4me2 levels are unchanged during maximal GLI repression, these enhancers presumably remain poised for activation, albeit in a less accessible state. Upon binding HH-responsive enhancers, GLI repressors either recruit or activate HDACs, which prevent otherwise competent enhancers from acquiring enriched H3K27 acetylation. The loss of GLI repression, either genetically (Shh-/-;Gli3-/- or Gli3-/- limb buds), or developmentally (initiation of Shh expression) results in a loss of GLI repression and accompanying HDAC activity (Figure 7B,C). This chromatin-based mode of regulation enables the dynamic control of a field of cells containing primed enhancers. To determine if this priming event occurs on an ad hoc basis by disparate inputs or if it is the result of coordinated, HH-independent signaling events, we examined HH-responsive GBRs for the enrichment of additional binding motifs. Besides the GLI motif itself, no other motifs are enriched at high levels (Figure 1—source data 4) suggesting that HH-responsive GBRs are a heterogenous population of enhancers with no predominant co-regulators.

Figure 7. Model for GLI transcriptional repression.

(A) Summary of enhancer status at HH-responsive GBRs. (B) In the absence of HH, GLI repressors bind to enhancers for HH target genes, limiting their accessibility and, directly or indirectly, recruiting an HDAC complex that de-acetylates Histone H3K27, inactivating the enhancer. In the presence of HH signaling, GLI de-repression and loss of associated HDAC activity result in increased accessibility, the accumulation of H3K27ac and gene transcription. (C) Schematic showing tissue-restricted activity of HH-responsive GBRs within HH-responsive gene expression domains. (D) Possible roles for Stable GBRs in HH transcriptional regulation.

Figure 7.

Figure 7—figure supplement 1. Summary of enhancer status at Stable GBRs.

Figure 7—figure supplement 1.

Normalized fold enrichment of the indicated enhancer marks at all Stable GBRs.

Despite being critical for the transcriptional regulation of HH targets, HH-responsive enhancers are a distinct minority, constituting 6% (349/6064) of all GLI-bound, active enhancers. The rest are Stable GBRs with an unclear role in HH transcriptional regulation. Although these enhancers do not have significantly reduced levels of H3K27 enrichment in Shh-/- limbs, some of them show a trend toward reduced H3K27ac that suggests a continuum of GLI-bound enhancers that range from completely HH-responsive (HH-dependent) to those Stable GBRs that have no HH response (Figure 7—figure supplement 1). Consistent with this, Stable GBRs do have a modest overall increase in H3K27ac enrichment in Shh-/-;Gli3-/- limbs on a population level, indicating that their H3K27ac levels are regulated by GLI repressor to some extent. On the other hand, these enhancers are enriched at CpG-rich promoters, which are associated with more broadly expressed genes and have minimal enrichment near HH target genes (Figure 1G,H). They are also more highly conserved than HH-dependent GBRs (Figure 1—figure supplement 1E). In contrast to HH-responsive enhancers, they appear to be active in other cell types and tissues besides the limb (Figure 6A, Figure 7C). One possibility is that many Stable GBRs do not have a major role in mediating Hedgehog signaling; GLI repressors at these regions are relatively inert. A second possibility is that GLI repression at Stable GBRs mediates subtle changes to acetylation that confer small reductions in transcription that are beyond the limits of our detection. Finally, it is possible that Stable enhancers are globally active, but engage in long-range collaborations with tissue specific HH-responsive enhancers to activate transcription (Figure 7D).

Previous modeling has suggested that GLI repressors within an enhancer work cooperatively through multiple GLI sites (Parker et al., 2011), providing another mechanism for tuning enhancer response. HH responsive GBRs contain more GLI motifs than Stable GBRs, which may make them more responsive to GLI repression, although in contrast to this model, they have high quality GLI motifs. As many GLI target genes, including Ptch1 and Grem1, are regulated by multiple GLI enhancers (Vokes et al., 2008; Zuniga et al., 2012; Li et al., 2014; Lopez-Rios et al., 2014; Lorberbaum et al., 2016), this integration likely extends to higher level hubs of enhancer organization. For example, HH-responsive H3K27ac regions that are not bound by GLI cluster near HH-responsive GBRs, as do Stable GBRs suggesting that they may be modified based on proximity to GLI-repressor-HDAC complexes (Figure 1—figure supplement 1C).

The majority of HH-responsive GBRs do not have H3K27me3 enrichment even when there is maximal GLI repression (Figure 2A–D; Figure 7A). This indicates that the Polycomb repressor complex is not involved in mediating most GLI repression, a conclusion that seemingly conflicts with several studies showing direct or indirect roles for PRC2 in repressing HH transcription. However, these studies largely considered the transcriptional activator targets Ptch1 or Gli1 or looked at genetic interactions (Wyngaarden et al., 2011; Shi et al., 2014; Lorberbaum et al., 2016; Shi et al., 2016; Deimling et al., 2018). Consistent with their findings, Gli1 has high levels of H3K27me3 enrichment in Shh-/- limb buds (Figure 2B). Although Gli1 and Ptch1 are often examined in the context of GLI de-repression, they are both GLI-activator genes in that they require the loss of GLI repression as well as subsequent GLI activation for their expression (Litingtung et al., 2002; te Welscher et al., 2002). GLI activator targets such as these are likely to differ fundamentally in their mode of regulation from those that are activated upon de-repression. As H3K27me3 enrichment is commonly found at promoters (Young et al., 2011), GLI repressors on distal enhancers not directly enriched by H3K27me3 might still facilitate the recruitment of PRC2 to promoters through enhancer-promoter interactions. However, only one third of HH target genes have H3K27me3 enrichment at their promoters (Figure 2—figure supplement 1; Figure 2—source data 2), arguing against this scenario. Additionally, 65% (20/31) of HH-responsive GBRs enriched for H3K27me3 in Shh-/- limbs were detected in the H3K27ac MicroChIP on Shh-/-;Gli3-/- limbs. 17/20 of these regions maintained or increased H3K27ac enrichment in Shh-/-;Gli3-/- limbs, while the three regions that were reduced were near the GLI-activator-dependent HH pathway genes Gli1, Ptch1 and Ptch2 (Figure 4B; Figure 4—source data 2). Thus, for rare limb GBRs requiring GLI activation, their mode of action is consistent with previously proposed models in which GLI activators recruit a complex to remove H3K27Me3, resulting in the activation of these enhancers and subsequently their cognate target genes (Shi et al., 2014).

Confusingly, HDACs have been shown to have properties both consistent with and contradictory to our model. HDACs bind to and deacetylate GLI1 and GLI2 proteins, promoting their ability to act as transcriptional activators (Canettieri et al., 2010; Coni et al., 2013; Mirza et al., 2019). HDACs have also been shown to bind cis-regulatory regions in Gli1, consistent with an additional role in positively regulating HH-mediated transcription (Zhan et al., 2011). On the other hand, a SKI-HDAC complex has been shown to bind to and interact genetically with GLI3 to repress anterior digit formation in the limb bud (Dai et al., 2002). Similarly, Atrophin acts as a GLI co-repressor by recruiting an HDAC complex (Zhang et al., 2013). Multiple studies with SWI/SNF BAF complex members also indicate that they regulate aspects of both GLI activation and repression, roles that have in some cases been shown to be directed by the dynamic association of BAF members with HDAC complexes (Jagani et al., 2010; Zhan et al., 2011; Jeon and Seong, 2016). Our results indicate that HDAC1 is bound to about half of all HH-responsive GBRs. The absence of HDAC1 at such a significant percentage of GBRs could possibly be explained by transient binding of HDACs or the presence of partially redundant HDAC proteins. In support of the latter scenario, HDAC2 has been shown to preferentially bind to distal, rather than promoter regions (Wang et al., 2009). Although the simplest model is consistent with GLI repressors directly (via a GLI3 and HDAC-containing repression complex), we cannot exclude the possibility that HDAC1 is constitutively bound at CRMs in a GLI-independent fashion and the HDAC activity occurs indirectly . Collectively, these studies highlight the complexity of GLI regulation and the need for further studies to determine which complexes directly impact GLI repression.

Materials and methods

Key resources table.

Reagent type
(species) or resource
Designation Source or reference Identifiers Additional
information
Genetic reagent (M. musculus) Gli3Xt-J Gli3+/- Jackson Laboratory Jackson Cat# 000026,
MGI Cat# 2169581, RRID:MGI:2169581
Obtained from the Laboratory of Dr. Andy McMahon
Genetic reagent
(M. musculus)
Shhtm1amc Shh+/- Jackson Laboratory Jackson Cat# 003318,
MGI Cat# 3584154, RRID:MGI:3584154
Obtained from the Laboratory of Dr. Andy McMahon
Genetic reagent (M. musculus) Gli3FLAG Laboratory of Dr. Andy McMahon Obtained from the Laboratory of Dr. Andy McMahon
Genetic reagent (M. musculus) Swiss Webster
Wildtype
Charles River Charles River Cat# NCI 551
IMSR Cat# TAC:sw, RRID:IMSR_TAC:sw
Cell line NIH 3T3 ATCC Cat# CRL-6442, RRID:CVCL_0594 Used for conventional ChIP-seq
Antibody Anti-H3K27ac (mouse mono-clonal) Diagenode Diagenode Cat# C15200184, RRID:AB_2713908 Used for conventional ChIP-seq
Antibody Anti-H3K27ac (rabbit polyclonal) Abcam Abcam Cat# ab4729, RRID:AB_2118291 Used for conventional ChIP-qPCRs
Antibody Anti-H3K27ac (rabbit polyclonal) Diagenode Diagenode Cat# C15410196, RRID:AB_2637079 Used for conventional MicroChIP-seq
Antibody Anti-H3K27me3 (rabbit polyclonal) Abcam Abcam Cat# Ab195477,
RRID:AB_2819023
Used for conventional ChIP-seq
Antibody Anti-H3K4me1 (rabbit polyclonal) Millipore Millipore Cat# 07–436, RRID:AB_310614 Used for conventional ChIP-qPCRs
Antibody Anti-H3K4me2 (rabbit polyclonal) Millipore Millipore Cat# 07–030, RRID:AB_11213050 Used for conventional ChIP-seq
Antibody Anti-M2 FLAG (mouse monoclonal) Sigma Sigma-Aldrich Cat# F3165, RRID:AB_259529 Used for conventional ChIP-seq and WB (1:4000)
Antibody Anti-HDAC1 (rabbit polyclonal Abcam Abcam Cat# ab7028, RRID:AB_305705 Used for conventional ChIP-seq
Antibody Anti-Histone H3 (rabbit polyclonal Cell Signaling
Technology
Cell Signaling Technology Cat# 4499, RRID:AB_10544537 Used for WB (1:4000)
Antibody Anti-GAPDH (rabbit polyclonal Cell Signaling
Technology
Cell Signaling Technology Cat# 5174, RRID:AB_10622025 Used for WB (1:1000)
Antibody Anti-B-actin (rabbit polyclonal Cell Signaling
Technology
Cell Signaling Technology Cat# 8457, RRID:AB_10950489 Used for WB (1:2000)
Antibody Donkey-anti-mouse Jackson Immuno-Research Jackson ImmunoResearch Labs Cat# 715-035-150, RRID:AB_2340770 Used for WB (1:5000)
Antibody Donkey-anti-rabbit Jackson Immuno-Research Jackson ImmunoResearch Labs Cat# 711-005-152, RRID:AB_2340585 Used for WB (1:5000)
Antibody Dynabeads M-280 Sheep Anti-Mouse IgG Invitrogen, Thermo Fisher Scientific Thermo Fisher Scientific Cat# 11201D, RRID:AB_2783640
Antibody Dynabeads M-280 Sheep Anti-Rabbit IgG Invitrogen,
Thermo Fisher Scientific
Thermo Fisher Scientific
Cat# 11203D, RRID:AB_2783009
Chemical compound, drug Purmorphamine Stemgent Stemgent Cat# 04–0009 Used in cell culture (400 nM)
Chemical compound, drug SAHA Selleckchem Selleckchem Cat# MK0683 Used in limb bud culture (20 μM)
Chemical compound, drug FK228 Selleckchem Selleckchem Cat# S3020 Used in limb bud culture (250 nM)
Commercial Assay or Reagent SensiFAST SYBR-LoROX Bioline Bioline Cat# BIO-94020
Commercial Assay or Reagent NEBNext DNA Library Prep Master Mix Set for Illumina New England Biolabs NEB Cat# E6040L, E7645L
Commercial Assay or Reagent Agencourt AMPure XP Beckman Coulter Beckman Coulter Cat# A63881
Commercial Assay or Reagent True MicroChIP Kit Diagenode Diagenode Cat# C01010130
Commercial Assay or Reagent MicroPlex Library Prep Kit Diagenode Diagenode Cat# C05010012
Commercial Assay or Reagent Liberase Roche Roche Cat# 05401119001 Cell dissociation (100 µg/mL)
Software, Tools MACS version 2.1.0 (Zhang et al., 2008https://github.com/taoliu/MACS MACS, RRID:SCR_013291
Software, Tools limma (Ritchie et al., 2015) LIMMA, RRID:SCR_010943 http://bioconductor.org/packages/release/bioc/html/limma.html
Software, Tools R statistical software (R Development Core Team, 2014) R Project for Statistical Computing, RRID:SCR_001905 https://www.r-project.org/
Software, Tools CisGenome (Ji et al., 2008) CisGenome, RRID:SCR_001558 http://www.biostat.jhsph.edu/~hji/cisgenome/
Database, Tools JASPAR motif database (Khan et al., 2018) JASPAR, RRID:SCR_003030 http://jaspar.genereg.net/
Database, Tools Transfac motif database (Matys et al., 2006) TRANSFAC, RRID:SCR_005620 http://gene-regulation.com/pub/databases.html
Database, Tools VISTA enhancer browser (Visel et al., 2007) VISTA Enhancer Browser, RRID:SCR_007973 https://enhancer.lbl.gov/

Embryonic manipulations

Experiments involving mice were approved by the Institutional Animal Care and Use Committee at the University of Texas at Austin (protocol AUP-2016–00255). The Gli3Xt-J and Shhtm1amc null alleles have been described previously (Hui and Joyner, 1993; Dassule et al., 2000) and were maintained on a Swiss Webster background. The Gli33XFLAG allele, with an N-terminal 3XFLAG-epitope, (Lopez-Rios et al., 2014; Lorberbaum et al., 2016) was maintained on a mixed background. For ChIP and ChIP-seq experiments, fresh E10.5 (32–35 somite) forelimb buds were pooled from multiple litters to obtain sufficient Gli3-/- and Shh-/- mutant embryos along with somite matched controls (Swiss Webster embryos for Gli3-/- experiments and a mixture of WT and heterozygous littermates for Shh-/-) embryos. For ATAC-seq, fresh pairs E10.5 (35 somite) posterior forelimb buds were dissected from individual embryos.

To inhibit HDAC1/2, E10.5 embryos (32–35S) were dissected in warm limb bud culture media (Panman et al., 2006) and explants still attached to the body wall were cultured in 250 nM of HDAC inhibitor FK228 (Selleckchem S3020), 20 μM of the HDAC inhibitor SAHA (Selleckchem MK0683), or DMSO vehicle control, for two hours at 37C. For each condition, 20–25 embryos were used (n = 4). After incubation, the explants were changed into fresh media (without inhibitor) to dissect anterior limb buds. Cells from anterior limbs were then dissociated and processed for ChIP.

Cell culture

NIH3T3 were authenticated by and purchased from ATCC (NIH3T3 CRL-1658). They have tested negative for Mycoplasma. Cells were seeded on 6 cm plates with 5 × 10^5 cells and grown for three days until completely confluent. They were then switched to low serum (0.5%) and treated with 400 nM purmorphamine (Stemgent 04–0009) or 0.01% DMSO (vehicle control) for 2 days. Under these conditions, a representative purmorphamine-treated sample had substantial elevation of the canonical HH target genes Ptch1 and Gli1 compared to controls (47-fold and 697-fold enrichment, respectively). NIH3T3 cells (ATCC CRL-1658) were authenticated and purchased directly by vendor, and tested negative for Mycoplasma.

Western blots

Whole limb buds from a single litter were lysed for 1 hr at 4C. For fractionation, 500,000 cells from limb buds were then dissociated with 100 ug/mL Liberase (Roche 05401119001), resuspended in CSKT buffer (10 mM PIPES pH6.8, 100 mM NaCl, 300 mM sucrose, 3 mM MgCl2, 1 mM EDTA, 1 mM DTT, 0.5% TritonX-100, incubated on ice for 10 min, and centrifuged for 5 min @ 5000 g. The cytoplasmic fraction (supernatant) and nuclear pellet were each resuspended in loading dye and boiled. Western blots were incubated with the following primary antibodies for 1 hr at room temperature in 3% milk: 1:4000 M2 Flag (Sigma 3165),1:4000 H3 (Cell Signaling 4499), 1:1000 GAPDH (Cell Signaling 5174), 1:1000 H3K27ac (Abcam Ab4729), 1:2000 B-actin (Cell Signaling 8457). Secondary antibodies were incubated for 1 hr at room temperature in 3% milk: 1:5000 Donkey anti-mouse (Jackson 715-035-150), Donkey anti-rabbit (Jackson 711-005-0152).

Chromatin immunoprecipitation

ChIP experiments were performed as previously described (Vokes et al., 2008) with the following modifications. Histone ChIPs were performed on whole E10.5 (32S-35S) forelimbs pooled from 6 to 8 embryos. The GLI3-FLAG ChIP and the H3K27ac ChIP on cultured and treated limbs were performed on E10.5 (32–35S) forelimbs from 20 to 25 pooled embryos. The HDAC1 ChIP was performed on pooled forelimbs and hindlimbs from 30 E11.5 (40–44S) embryos. Cells were dissociated with 100 ug/ml Liberase (Roche 05401119001) and fixed: 15 min for H3K27ac. 30 min for GLI3-FLAG and 7 min for HDAC1 at room temperature in 1% formaldehyde. After cell lysis, chromatin was sheared. H3K27ac ChIP samples were sheared in buffer containing 0.25% SDS with a Covaris S2 focused ultrasonicator using the following settings: Duty Cycle: 2%, Intensity: 3, Cycles/burst: 200, Cycle time: 60 s, Power mode: frequency sweeping. GLI3-FLAG ChIP samples were sheared using a Branson Sonifier for 10 cycles, 30 s on/60 s off, intensity 3.5. HDAC1 samples were sheared using a Diagenode Bioruptor for 5, 10 min cycles: 30 s on/60 s off, on high power. Sheared chromatin was then split into 3 ChIP reactions and incubated with antibody-dynabead preparations overnight. The H3K27ac antibodies for conventional ChIP were from Diagenode (C15200184) and Abcam (ab4729), while the H3K27Ac antibody for MicroChIPs was from Diagenode (C15410196). Additional antibodies recognized H3K4me1 (Millipore ABE1353) H3K4me2 (Millipore 07–030) and H3K27me3 (Abcam ab195477), FLAG (Sigma F3165) and HDAC1 (Abcam ab7028). Beads were washed 5 times with RIPA buffer (1% NP40, 0.7% Sodium Deoxycholate, 1 mM EDTA pH8, 50 mM Hepes-KOH pH7.5, 2% w/v Lithium Chloride) and 1 time with 100 mM Tris pH8, 10 mM EDTA, 8.0, 50 mM NaCl and then eluted at 70°C for 15 min. For HDAC1 ChIPs beads were washed twice with low salt buffer (0.1% Deoxycholate, 1% Trition X-100, 1 mM EDTA, 50 mM Hepes-KOH pH 7.5, 150 mM NaCl), once in high salt buffer (0.1% Deoxycholate, 1% Trition X-100, 1 mM EDTA, 50 mM Hepes-KOH pH 7.5, 500 mM NaCl), once in LiCl buffer (250 mM LiCl, 0.5% NP-40, 0.5% Deoxycholate, 1 mM EDTA, 10 mM Tris-HCl pH 8), and 2x washes in TE buffer (10 mM Tris-HCl pH 8, 1 mM EDTA). Crosslinking was reversed overnight at 70°C. Chromatin was purified and concentrated, then subjected to quantitative PCR and/or library preparation and sequencing. Quantitative PCR-based analysis was performed using SensiFAST SYBR-LoROX (Bioline BIO-94020) on a Viia7 system (Applied Biosystems). ChIP regions subsequently tested by qPCR are referred to in the figures by the unique peak ID number (Figure 1—source data 2). For each biological replicate, 2–3 technical replicates were performed for each qPCR reaction and the Ct values were averaged. Chromatin enrichment was determined by calculating delta delta Ct method (Livak and Schmittgen, 2001) against a control region (C1).

Primers are described below. Primers are identified by their H3K27ac Peak ID. Primers labeled #1–5 are HH-dependent GBRs.

H3K27ac ID Primers GBR coordinate GBR type Comments
32467 (#1) F: ACGCAGGCAGTTCCAATACA
R: AGGGACTTCACCCAGTTCCA
Chr2:113640572–113641614 HH-dep. GRE1 (near Grem1)
15198 (#2) F: CCCTCCATTCTCCCTCCTTA
R: GGACCTTTCCGTTGAAGTGA
Chr13:63950822–63952750 HH-dep. randomly selected GBR
2666 (#3) F: CTGGCTCCCAGAATCTCTCA
R: TGTGCCCCATCTCTTTCAG
Chr1:155211962–155213426 HH-dep. randomly selected GBR
45094 (#4) F: GGGAGGGGTGAACTTGTCTT
R: TGCAAATGAACACACGCATA
Chr5:134073187–134074116 HH-dep. randomly selected GBR
20941 (#5) F: TTCCCAGCTCAAGGTCATGT
R: AGGAGGCAATGAAGACACTGG
Chr15:86429678–86430690 HH-dep. randomly selected GBR
41492 F: AGAAGGACTCCTATGTGGGTGA
R: ACTGACCTGGGTCATCTTTTCA
NONE NONE Beta actin- normalizing target
41492 F: AGCTAACAGCCTGCCCTCTG
R: TTTTCCGGTGGTACCCTACG
NONE NONE Beta actin-normalizing target for H3K4me1
NONE (C1) F: GCCAGAATTCCATCCCACTA
R: CCAATAACCTGCCCTGACAT
NONE NONE negative normalizing

Samples were processed for ‘MicroChIP’ using the Diagenode True MicroChIP kit (Cat #C01010130) with the following modifications. Briefly, individual limb pairs (~100 k cells) of wildtype, Shh-/- and Shh-/-;Gli3-/- E10.5 embryos (33–34S) were processed separately by dissociating limb buds with 100 ug/mL Liberase (Roche 05401119001), crosslinked for 10 min, lysed and then sheared. Samples were sheared on a Diagenode BioRuptor for six cycles on high, 30 s on/off and processed through shearing while genotyping in parallel for Shh-/-;Gli3-/- and wildtype littermates (Shh+/+;Gli3+/+). Sheared chromatin was then incubated with H3K27ac antibody (Diagenode C15410196) overnight and Protein A magnetic beads (Diagenode C03010020) the following day for 2 hr. Chromatin-bound beads were washed, eluted and de-crosslinked and purified using MicroChIP DiaPure columns (Diagenode C03040001).

ChIP-Seq

The ChIP-seq raw datasets from this study have been deposited in GEO (GSE108880) (see Source Data for Figures 15 for processed ChIP-seq and ATAC-seq data). The H3K4me1 data used in this study (GSE86690) were processed and analyzed as all other ChIP experiments were done, described below. All chromosomal coordinates refer to the mm10 version of the mouse genome.

After ChIP was performed as described above, libraries were generated using the NEBNext Ultra II library preparation kit with 15 cycles of PCR amplification (NEB E7645) or generated using the MicroPlex library prep kit (Diagenode C05010012) and sequenced to a depth of >40 million reads per sample for both ChIP and ‘MicroChIP’ experiments, using two biological replicates. Peaks were called using CisGenome version 2.1.0 (Ji et al., 2008). To identify differentially enriched peaks in the WT and Shh-/- limb buds (or control and purmorphamine-treated NIH3T3 cells), the peaks were merged to determine how many WT, WT input, Shh-/- and Shh-/- input reads overlapped with the peak region. The read numbers were adjusted by library size and log2 transformed after adding a pseudo-count of 1. The differential analysis between WT and WT input used limma (Ritchie et al., 2015). The FDR of the differential test was obtained and peaks with FDR < 0.05 are determined as having differential signal between WT and WT input. The same differential analysis procedure was repeated to compare between Shh-/- and Shh-/- input, and between WT and Shh-/-. To determine GLI motif quality, de novo motif discovery was performed on the 1000 GBRs with the highest quality using the flexmodule_motif function in CisGenome to identify the GLI motif. The GLI motif was mapped to the mouse genome using the motifmap_matrixscan_genome function in CisGenome software with default parameters.

ATAC-Seq

Individual pairs of posterior forelimb fractions were dissected from 35 somite wildtype (n = 2) or Shh-/- embryos (n = 2). ATAC used components from the Nextera DNA Library Preparation Kit (Illumina) as described previously (Buenrostro et al., 2015) with the following variations. 5,000 cells from each sample were added into each reaction and cells were lysed on ice for 8 min. prior to centrifugation. Libraries were generated using 18 cycles of PCR amplification with NEB high fidelity 2x master mix (New England Biolabs), cleaned up with AMPure XP beads (Beckman Coulter) and sequenced on an Illumina NextSeq 500 using PEx75 to a depth of 30 million reads. Peaks were called using MACS2 with a fixed window size of 200 bp and a q-value cutoff of 0.05. Differential analysis of wildtype versus Shh-/- peak signals was performed essentially as described for ChIP above using limma (Ritchie et al., 2015).

Acknowledgements

We thank Blerta Xhemalce, Samantha Brugmann, Kevin Peterson and Janani Ramachandran for comments on the manuscript. We thank Drs. Ken Zaret, Maki Iwafuchi-Doi, Jongwhan Kim and Cathy Rhee for advice on performing ATAC-seq, Andy McMahon for providing the Gli3Flag mice and Jessica Podnar from the Genomic Sequencing and Analysis Facility at the University of Texas at Austin for technical advice. The Texas Advanced Computing Center (TACC) at The University of Texas at Austin provided computational resources. This work was supported by NIH R01HD073151 (to SAV and HJ), The St. Baldrick’s Foundation (to SAV) and F31DE027597 (to RKL).

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Steven A Vokes, Email: svokes@austin.utexas.edu.

Marianne E Bronner, California Institute of Technology, United States.

Marianne E Bronner, California Institute of Technology, United States.

Funding Information

This paper was supported by the following grants:

  • Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD073151 to Hongkai Ji, Steven A Vokes.

  • National Institute of Dental and Craniofacial Research F31DE027597 to Rachel K Lex.

  • St. Baldrick's Foundation to Steven A Vokes.

  • National Institutes of Health R01HG009518 to Hongkai Ji.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Project administration.

Conceptualization, Data curation, Software, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology.

Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology.

Conceptualization, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology.

Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Methodology.

Conceptualization, Data curation, Software, Formal analysis, Supervision, Investigation, Visualization, Methodology, Project administration.

Conceptualization, Software, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Project administration.

Ethics

Animal experimentation: Experiments in this study involving mice were approved by the Institutional Animal Care and Use Committee at the University of Texas at Austin (protocol AUP-2016-00255).

Additional files

Transparent reporting form

Data availability

Sequencing data has been deposited in GEO (accession GSE108880).

The following dataset was generated:

Lex RK, Ji Z, Falkenstein KN, Zhou W, Henry JL, Ji H, Vokes. SA 2020. GLI transcriptional repression regulates enhancer activity and chromatin accessibility for Hedgehog target genes. NCBI Gene Expression Omnibus. GSE108880

The following previously published datasets were used:

Lewandowski JP, Du F, Zhang S, Powell MB, Falkenstein KN, Ji H, Vokes SA. 2015. RNA sequencing of mouse littermate wild-type and Shh null E10.5 forelimbs [Illumina] NCBI Gene Expression Omnibus. GSE58645

ENCODE DCC. 2016. ChIP-seq from limb (ENCSR238SGC) NCBI Gene Expression Omnibus. GSE86690

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Decision letter

Editor: Marianne E Bronner1

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

In this manuscript, Lex et al. investigate chromatin modifications in wildtype and Shh mutant undergoing constitutive Gli repression in limb buds. From these data they propose a model to explain dynamic, tissue-specific derepression of genes. Strengths of the approach include: 1) the potential physiological relevance of using a well-studied in vivo system where there is a clear role for Hh signaling and derepressive mechanisms, 2) using a genome wide approach and 3) using the in vivo data of Hh-responsive enhancers (from VISTA datasets) to show that a subset of the putative enhancers are bona fide. The revised paper makes an important contribution to the literature.

The manuscript investigates an important question about how chromatin modifications solidify the dynamic and quick gene expression changes necessary for development and investigates one of the most complicated mechanisms at play- derepression.

Decision letter after peer review:

Thank you for submitting your article "GLI transcriptional repression regulates tissue-specific enhancer activity in response to Hedgehog signaling" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by Marianne Bronner as the Senior and Reviewing Editor. The reviewers have opted to remain anonymous. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

This manuscript examines how GLI transcriptional repression regulates tissue-specific enhancer activity in response to Hedgehog signaling. The authors investigate chromatin modifications in wildtype and Shh mutant with constitutive Gli repression in the limb buds. From these data they propose a model to explain dynamic, tissue-specific derepression of genes.

Essential revisions:

While the reviewers found the manuscript potentially interesting, they also noted that it was difficult to read and evaluate. In general, the paper needs extensive revision with clear definitions and further support for the conclusions. Overlaying the VISTA enhancer database with the ATAC-seq (and ChIP) data would be important. In addition, you need to provide evidence that the Gli3-HDAC mechanism proposed is direct. As the necessary revisions are quite extensive, we include the full reviews for your information.

Reviewer #1:

The Vokes lab has provided important contributions cementing the finding that a significant part of the transcriptional regulation downstream of Smo is via the release of Gli2/3-mediated suppression of target gene transcription. To further find mechanistic support, this paper probes Gli Binding Regions (GBRs) and finds that GBRs enriched around Hh target genes can lose acetylation in the absence of Shh due to the presence of the repressor forms of Gli3. Although the mechanisms remain unresolved the results indicate that Histone Deacetylases interact with the repressor form of Gli3.

The initial identification of Gli3 binding regions is in WT, E10.5 limb buds, when "high levels of HH target gene expression are observed". According to the release of inhibition model, under these conditions it would be predicted that the Gli3R is not bound to its targets, and would thus not be ChIP-ed. It would seem to me that differential Gli binding in A vs. P or WT vs. Shh-/- (or perhaps even better Smo-/-) limb buds would yield a better collection of relevant GBDs, that would provide a better correlate for the ChIP-seq that is appropriately performed in WT and Shh-/- limb buds. Although some elements of this approach are presented in Figure 4, these results are presented as supporting, and not as driving the question.

Using Ptch1 as the prototypical target for HH signaling is reasonable but Gremlin is more complex, as in the developing neural tube its expression is restricted to the roof plate, and thus at best inhibited by Shh signaling, while in the gut there appears little evidence that it is under Shh control. In general, there is very little resolution whether the observed correlation is general (supported by Gli1 and Ptch1) or limb bud-specific.

Figure 4D-F: I don't see the indicated p-values as described in the legend.

Figure 4G-I: What are the "Selected GBRs", and what genes are they associated with?

Purmorphamine is better described as a Smo agonist. I do wander about the choice of Purmorphamine, as much more specific small molecules (e.g. SAG) but in particular Shh should be used in these experiments, as Smo downstream of Ptch1/2 not necessarily equates Ptch1/2 inactivation via Shh.

Reviewer #2:

In their manuscript, GLI transcriptional repression regulates tissue-specific enhancer activity in response to Hedgehog signaling, Lex et al. investigate chromatin modifications in wildtype and Shh mutant (undergoing constitutive Gli repression) limb buds. From these data they propose a model to explain dynamic, tissue-specific derepression of genes. Strengths of the approach include: 1) the potential physiological relevance of using a well-studied in vivo system where there is a clear role for Hh signaling and derepressive mechanisms, 2) using a fairly agnostic genome wide approach and 3) using the in vivo data of Hh-responsive enhancers (from VISTA datasets) to show that a subset of the putative enhancers may be bona fide. However, it is difficult to evaluate whether the data support the conclusions through much of the manuscript due to the lack of definitions and details.

The manuscript investigates an important question about how chromatin modifications solidify the dynamic and quick gene expression changes necessary for development and investigates one of the most complicated mechanisms at play- derepression. As written, the analysis of the VISTA enhancer database provides the only compelling evidence that the authors are, in fact, identifying relevant enhancers. The demonstration that these sites are sensitive to an HDAC inhibitor is consistent with the model that GliR recruits an HDAC but leaves open the possibility of indirect HDAC recruitment. Thus, the manuscript provides further evidence that enhancer-promoter interactions to induce transcription work as the field understands and the advance is that these data may demonstrate it in an in vivo setting.

1) The authors need to define and prove that the GBRs they are examining are, in fact, enhancers. While this possibility is consistent with the data, as currently stands the manuscript does not provide sufficient definitions and analysis for this determination to be made. For example, as stands it is possible that GBRs represent some other type of element, such as a gene body or the 3' ends of genes, or no element at all. As the authors examine H3K4me1/2, they may have appropriate data available.

2) The authors need to define terms such as "around genes", "in close proximity to the promoters", "significantly clustered around", "selecting regions that would not overlap with promoters" as is standard in the field. Without clear definitions of proximity and how the associated genes are being called, these data are not interpretable/overinterpreted. One example: subsection “HH-responsive GBRs are distal enhancers containing high quality GLI motifs”, as explained this paragraph says that the stable GBRs are more likely than Hh-responsive GBRs to be near promoters; however, this does not mean that the rest of the Hh-responsive GBRs are enhancers – – and by the section title “Hedgehog signaling does not regulate other histone modifications at enhancers”, the authors are clearly referring to these distal elements as enhancers.

3) In the section "Hh signaling does not regulate other histone modifications at enhancers", H3K4me1 should shift to H3K4me2 at the active enhancers. The fact that H3K4me2 does not change from Shh mutants to wildtype suggests these may not be active enhancers. In fact H3K4me2 only marked "a subset of Hh-responsive GBRs"- why don't they have H3K4me2? If the thought is that they might represent weak enhancers, they should show bidirectional PolII. Related to this in the subsequent section using ATAC-seq, why are the GBRs less accessible under the wild type "activated" condition?

4) The statement stating that the data suggest "a model in which loss of an HDAC-GLI repressor complex leads to acetylation" is a bit misleading as it sounds like the only possibility. In fact, the data suggest a correlation that would likely be true regardless of mechanism and the subsequent culturing with FK228 are again consistent with the model but do not prove it as the GLI-HDAC interaction need not be direct.

5) The authors should examine and report the ATAC-seq and chromatin data specifically at the enhancers from the VISTA enhancer database and discuss in regards to their model.

eLife. 2020 Jan 28;9:e50670. doi: 10.7554/eLife.50670.sa2

Author response


Essential revisions:

While the reviewers found the manuscript potentially interesting, they also noted that it was difficult to read and evaluate. In general, the paper needs extensive revision with clear definitions and further support for the conclusions. Overlaying the VISTA enhancer database with the ATAC-seq (and ChIP) data would be important. In addition, you need to provide evidence that the Gli3-HDAC mechanism proposed is direct. As the necessary revisions are quite extensive, we include the full reviews for your information.

Reviewer #1:

[…] The initial identification of Gli3 binding regions is in WT, E10.5 limb buds, when "high levels of HH target gene expression are observed". According to the release of inhibition model, under these conditions it would be predicted that the Gli3R is not bound to its targets, and would thus not be ChIP-ed. It would seem to me that differential Gli binding in A vs. P or WT vs. Shh-/- (or perhaps even better Smo-/-) limb buds would yield a better collection of relevant GBDs, that would provide a better correlate for the ChIP-seq that is appropriately performed in WT and Shh-/- limb buds. Although some elements of this approach are presented in Figure 4, these results are presented as supporting, and not as driving the question.

The best way to address this would be with GLI3-Flag ChIPs in Shh-/-or PrxCre;Smoc/c limb buds. However, our current Flag ChIP procedure requires fresh tissue and we need large numbers of synchronously staged embryos for collection (typically 20-25 pairs of limb buds at this stage). The extensive breeding required to generate this synchronous population of Shh-/-;Gli3Flag limb buds for ChIP is not feasible for us with our current procedure (we tried but failed to obtain meaningful enrichment with the Flag antibody using the MicroChIP protocol on single pairs of E10.5 Gli3Flag limb buds).

As an alternative strategy, we dissected E10.5 Gli3Flag limb buds into anterior and posterior halves (as schematized in Figure 4 and new Figure 5) and generated nuclear and cytoplasmic fractions. There are minimal levels of GLI3 protein in the posterior limb bud where HH is active, while the anterior limb nuclei nearly exclusively express repressor specific GLI3. We have added these data as Figure 1—figure supplement 1B and have added the following section to the Results:

“Nearly all nuclear GLI3 is present in the anterior half of the limb bud in the repressor form with little or no nuclear GLI3 present in the posterior half (Figure 1—source data 1B). Therefore, the GBRs identified in this study are likely to exclusively represent GLI3 repressor binding regions.”

Using Ptch1 as the prototypical target for HH signaling is reasonable but Gremlin is more complex, as in the developing neural tube its expression is restricted to the roof plate, and thus at best inhibited by Shh signaling, while in the gut there appears little evidence that it is under Shh control. In general, there is very little resolution whether the observed correlation is general (supported by Gli1 and Ptch1) or limb bud-specific.

We agree and have edited Figure 1 to highlight domains that have been previously shown to be limb-specific. We have added tracks showing H3K27ac levels in WT and Shh null limb buds at Ptch1 (Lopez-Rios et al., 2014). We also focus on the limb specific GLI enhancer, GRE1, near Gremlin (Li et al., 2014), omitting the broader locus.

Figure 4D-F: I don't see the indicated p-values as described in the legend.

2. We have added the p-values to the legend.

Figure 4GI: What are the "Selected GBRs", and what genes are they associated with?

GBR #1 is GRE1, a limb-specific enhancer previously shown to be associated with Gremlin (depicted in Figure 1E). The other 4 regions are randomly selected HH-dependent GBRs that were not selected on the basis of being associated with a particular gene and are not near genes. We have added this information in tabular form to the Materials and methods (subsection “Chromatin Immunoprecipitation”). Please note that the referenced figure panels using these primers are now shown in Figure 4G, H and Figure 5D.

Purmorphamine is better described as a Smo agonist. I do wander about the choice of Purmorphamine, as much more specific small molecules (e.g. SAG) but in particular Shh should be used in these experiments, as Smo downstream of Ptch1/2 not necessarily equates Ptch1/2 inactivation via Shh.

As part of our quality control, we reserved a portion of the NIH3T3 cells prior to harvesting for ChIP-seq experiments and used them for generating cDNA to determine the induction of Gli1 and Ptch1. Compared to vehicle treated control cells, those treated with 400nM of Purmorphamine have 47-fold enrichment of Ptch1 and 697-fold enrichment of Gli1. While we agree that the specificity and quantitative aspects of the response might be improved upon activation with Hedgehog ligand, the robust expression of GLI activator targets under our conditions suggests that there is unlikely to be residual GLI repressor activity. We have added the following information to the Materials and methods section:

“Under these conditions, a representative purmorphamine-treated sample had substantial elevation of the canonical HH target genes Ptch1 and Gli1 compared to controls (47-fold and 697-fold enrichment, respectively).”

Reviewer #2:

[…] 1) The authors need to define and prove that the GBRs they are examining are, in fact, enhancers. While this possibility is consistent with the data, as currently stands the manuscript does not provide sufficient definitions and analysis for this determination to be made. For example, as stands it is possible that GBRs represent some other type of element, such as a gene body or the 3' ends of genes, or no element at all. As the authors examine H3K4me1/2, they may have appropriate data available.

We agree that this is an important point. As H3K4Me2 marks only a minority of regions (see new Figure 7A and response to #3, below), we reanalyzed published H3K4Me1 ChIP-seq data from E10.5 limb buds from the ENCODE consortium and intersected it with GBRs. The majority of the GBRs (83% of HH-responsive GBRs and

81% of Stable GBRs) overlap with H3K4Me1 peaks in addition to being enriched for H3K27ac. Their dual status as H3K27ac+;H3K4Me1+ suggests that these are enhancers. We have added the following statement to the Results:

“As H3K27ac is not exclusively localized to enhancers, we also examined the enrichment of histone H3K4me1, a general marker of primed and active enhancers, at these GBRs, using publicly available data (Encode 2012) (Figure 1—source data 3). In wildtype limb buds, 82% of HH-responsive GBRs are enriched for H3K4 mono-methylation, supporting that these regions are likely to act as enhancers (HH-sens: 123/148, 83%; HH-dep: 162/201, 81%).”

2) The need to define terms such as "around genes", "in close proximity to the promoters", "significantly clustered around", "selecting regions that would not overlap with promoters" as is standard in the field. Without clear definitions of proximity and how the associated genes are being called, these data are not interpretable/overinterpreted. One example: subsection “HH-responsive GBRs are distal enhancers containing high quality authors GLI motifs”, as explained this paragraph says that the stable GBRs are more likely than Hh-responsive GBRs to be near promoters; however, this does not mean that the rest of the Hh-responsive GBRs are enhancers – and by the section title “Hedgehog signaling does not regulate other histone modifications at enhancers”, the authors are clearly referring to these distal elements as enhancers.

We have extensively revised the entire manuscript to define terminology, including the specific example mentioned above, which now reads:

“Although Stable GBRs are not highly enriched at HH target genes, 62% of them (3,544/5,715) are located in close proximity to the promoters of genes (2kb upstream to 1kb downstream of TSS), compared to 26% (91/349) of HH-responsive GBRs (Figure 1H). Most promoter-associated Stable GBRs (90%; 3,190/3,544) are found at promoters associated with CpG islands (defined as a TSS with a CpG region within 5kb upstream to 2.5kb downstream), a quality typically associated with housekeeping genes, and genes that tend to be more broadly expressed and less tissue-specific (Zhu et al., 2008).”

3) In the section "Hh signaling does not regulate other histone modifications at enhancers", H3K4me1 should shift to H3K4me2 at the active enhancers. The fact that H3K4me2 does not change from Shh mutants to wildtype suggests these may not be active enhancers. In fact H3K4me2 only marked "a subset of Hh-responsive GBRs"- why don't they have H3K4me2? If the thought is that they might represent weak enhancers, they should show bidirectional PolII. Related to this in the subsequent section using ATAC-seq, why are the GBRs less accessible under the wild type "activated" condition?

We are unsure why H3K2Me2 is only enriched at a minority of GBRs (now visualized in new Figure 7A). To address this concern more directly, we visualized the presence of several enhancer markers: ATAC-seq, H3K4Me2, H3K4Me1 in those GBRs that have enhancer activity in transgenic embryos and are, by that criteria, functional enhancers. Over half (61% – 81/144) of the Stable GBRs with enhancer activity in the limb have H3K4Me2 enrichment while 25%

(3/12) have H3K4Me2 enrichment in HH-responsive enhancers. To illustrate these findings, we have added Venn Diagrams showing the overlap of enhancer markers in transgenic embryos that drive limb expression (Figure 6D) and have also added ChIP-seq plots for a representative enhancer (Figure 6E).

The data are also summarized for all GBRs in Figure 7A and Figure 7—figure supplement 1. We have added the following section to the Results:

“While all GBRs tested in the VISTA database with limb activity are by definition enriched for H3K27ac, 91% of HH-responsive GBRs and 95% of Stable GBRs are also enriched for H3K4me1 (Figure 6D). Additionally, all GBRS are enriched for at least two markers of enhancers (H3K27ac, H3K4me1, H3K4me2, ATAC) while most are enriched for 3-4 of these markers (67% HH-responsive GBRs; 93% Stable GBRs) (Figure 6D, E).”

To address the question concerning wild type ATAC-seq accessibility, we compared WT GBRs that have called ATAC-peaks (ATAC+) with WT GBRs that do not have ATAC-peaks (ATAC-) (Figure 3B). We have added this information to the Results:

“To determine if these regions are likely to be enhancers, we analyzed the co-enrichment of the enhancer markers H3K4me1 and H3K4me2 at ATAC accessible (ATAC+) and inaccessible (ATAC-) HH-responsive GBRs. […] These results suggest that most of the ATAC- regions are likely to correspond to real enhancers though at a somewhat reduced frequency compared to ATAC+ regions.”

4) The statement stating that the data suggest "a model in which loss of an HDAC-GLI repressor complex leads to acetylation" is a bit misleading as it sounds like the only possibility. In fact, the data suggest a correlation that would likely be true regardless of mechanism and the subsequent culturing with FK228 are again consistent with the model but do not prove it as the GLI-HDAC interaction need not be direct.

We agree, and to address this we performed ChIP-seq to identify HDAC1 binding regions in E11.5 limb buds (since HDAC1 ChIPs require ~30 million cells from ~30 pairs of E11.5 forelimbs, it was not feasible to use E10.5 forelimbs, which would have required ~300 embryos). A sizable number of HH-responsive GBRs are enriched for HDAC1, which supports the possibility that this interaction might be direct. We have moved the HDAC inhibitor data (with FK228 as we showed previously along with a new data using an additional HDAC inhibitor, SAHA, which shows the same trends) and HDAC 1 ChIP-seq data (summaries and representative plots) to new Figure 5 and describe these findings in the Results:

“The increased enrichment of H3K27ac acetylation in HDAC-inhibited anterior limb buds was comparable to that seen in posterior limb buds (Figure 4G). […] We conclude that GLI repressors regulate H3K27ac levels at HH-responsive GBRs through HDACs (see Discussion).”

We note that many GBRs are not enriched for HDAC1, possibly because it is difficult to identify more transient HDAC1 binding events or because they are not enriched for HDAC1. Even if these regions are enriched for another HDAC, such as HDAC2, it does not ‘prove’ that the interaction is direct and we have modified the model Figure 7B (Figure 6A in the previous version) to signify that the interaction between GLI3 and HDAC is unknown (a gray box with dashed lines between GLI3 and HDAC). We have also added the following to the Discussion:

“Our results indicate that HDAC1 is bound to about half of all HH responsive GBRs. […] Although the simplest model is consistent with GLI repressors directly (via a GLI3 and HDAC-containing repression complex), we cannot exclude the possibility that HDAC1 is constitutively bound CRMs in a GLI-independent fashion and the HDAC activity is indirect.”

5) The authors should examine and report the ATAC-seq and chromatin data specifically at the enhancers from the VISTA enhancer database and discuss in regards to their model.

We performed this analysis and include it as Venn Diagrams (Figure 6D). We have included these data in the Results and find that all VISTA GBRs are enriched for at least one other enhancer marker besides H3K27ac (see response to point #3 above) while most are marked multiple markers. We have added the following to the Discussion:

“We find that a subset of GLI-bound regions has chromatin modifications that change in response to HH signaling. […] However, compared to WT embryos, these regions have reduced or absent levels of histone H3K27 acetylation in Shh-/- embryos, suggesting a loss of enhancer activity.”

In addition, we depict ATAC-seq and the other enhancer markers examined in this study as Figure 7A and Figure 7—figure supplement 1, which is directly above our model (Figure 7B), which depicts these regions as ‘Enhancer.’

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Lex RK, Ji Z, Falkenstein KN, Zhou W, Henry JL, Ji H, Vokes. SA 2020. GLI transcriptional repression regulates enhancer activity and chromatin accessibility for Hedgehog target genes. NCBI Gene Expression Omnibus. GSE108880
    2. Lewandowski JP, Du F, Zhang S, Powell MB, Falkenstein KN, Ji H, Vokes SA. 2015. RNA sequencing of mouse littermate wild-type and Shh null E10.5 forelimbs [Illumina] NCBI Gene Expression Omnibus. GSE58645
    3. ENCODE DCC. 2016. ChIP-seq from limb (ENCSR238SGC) NCBI Gene Expression Omnibus. GSE86690

    Supplementary Materials

    Figure 1—source data 1. Endogenous GLI3-Flag ChIP-seq analyzed data and called peaks.

    GLI3 binding regions with called peaks with a false discovery rate (FDR) < 0.05 from two biological replicates of E10.5 (32–35S) forelimbs. Rank ordered coordinates, peak length, log2 fold change (log2FC) and FDR are listed for each peak.

    elife-50670-fig1-data1.xlsx (346.8KB, xlsx)
    Figure 1—source data 2. WT vs Shh-/- H3K27ac ChIP-seq analyzed data and called peaks.

    H3K27ac called peaks with a FDR < 0.05 from two biological replicates from WT and Shh-/- E10.5 forelimbs. For each peak, the assigned Peak ID, coordinates, peak type, fold change normalized to input for WT and Shh-/- samples and fold change of WT over Shh-/- are listed. Additional tabs include sorted datasets for sub-classifications. Tabs containing GBRs indicate intersections with GLI binding regions.

    Figure 1—source data 3. H3K4me1 ChIP-seq analyzed data and called peaks from GSE86690.

    H3K4me1 called peaks with a false discovery rate (FDR) < 0.05 from two biological replicates of E10.5 WT forelimbs. Note that this is a reanalysis of a publicly available ENCODE dataset (see methods).

    Figure 1—source data 4. Motifs uncovered from HH-responsive enhancers.

    Table showing the top 20 motifs uncovered from de novo motif analysis on HH-responsive GBRs. The enrichment is relative to matched genomic controls. Note that ‘HH_resp_2’ is the only motif with an enrichment value of greater than two and corresponds with a known GLI binding motif.

    Figure 2—source data 1. Shh-/- H3K27me3 ChIP-seq analyzed data and called peaks.

    H3K27me3 called peaks with a FDR < 0.05 from two replicates of Shh-/- E10.5 forelimbs. For each peak, the assigned Peak ID, coordinates, log2 fold change normalized signal to input. Additional tab includes H3K27me3 peaks that overlap with GLI3 binding regions; the GBR sub-classifications are specified.

    elife-50670-fig2-data1.xlsx (387.1KB, xlsx)
    Figure 2—source data 2. Hedgehog responsive genes with H3K27me3 enrichment.

    The first column indicates genes previously identified as differentially expressed between Shh-/- and WT E10.5 limb buds (Lewandowski et al., 2015). The second column indicates the fold enrichment of H3K27me3 at the promoter compared to Input with the adjusted P-value indicated in the third column. The fourth column indicates whether the gene has a HH-dependent GBR (indicated by one and yellow shading) within the same presumptive TAD (Dixon et al., 2012). There are 22 HH-dependent target genes out of 80 HH-responsive genes.

    Figure 2—source data 3. WT vs Shh-/- H3K4me2 ChIP-seq analyzed data and called peaks.

    H3K4me2 called peaks with a FDR < 0.05 from two replicates from WT and Shh-/- E10.5 forelimbs. For each peak, the assigned Peak ID, coordinates, peak type, fold change normalized to input for WT and Shh-/- samples and fold change of WT over. Shh-/- are listed. Additional tabs include sorted files for each peak type. Under the ‘GLI3 binding’ column, ‘TRUE’ implies overlap with a GBR, while ‘FALSE’ indicates no overlap.

    Figure 3—source data 1. WT vs Shh-/- ATAC Seq analyzed data and called peaks.

    Coordinates for all ATAC peaks in the WT group that overlap with GBRs are listed. ‘Shh_ATAC_peak’ identifies the corresponding id# for that peak in the Shh-/- data, and if a peak is not present in the Shh-/- samples, it is marked as NA. A column for each GBR type identifies which GBR type a given ATAC peak overlaps with. The number indicates the peak ID. If a peak region does not overlap with the type of peak in that list, it will be marked as NA. The normalized log2 transformed signals are shown for each sample in addition to the ‘average’ signal across all samples. The ‘t’ statistic calculates the difference in signals between WT and Shh-/- by taking into consideration fold-change and variance among samples. A positive t statistic values indicate a peak is more accessible in WT than Shh-/- and a negative t statistic indicates higher accessibility in Shh-/-. The ‘p.value’ is obtained from a moderated t-test using limma. The ‘p.value.adj’ is the adjusted p-value (FDR) using the Benjamini-Hochberg procedure.

    Figure 4—source data 1. WT vs Shh-/-;Gli3-/- H3K27ac MicroChIP-seq analyzed data and called peaks.

    H3K27ac called peaks with a FDR < 0.05 from two replicates of WT, Shh-/- and Shh-/-;Gli3-/- E10.5 (33–34S) forelimbs. Separate tabs for each genotype include peak coordinates and log2 fold change over input. Additional tabs include a peak summary and differential analysis of WT vs. Shh-/-;Gli3-/-. Differential analysis tab lists peak coordinates, peak type, fold change normalized to input for WT and Shh-/-;Gli3-/- samples and fold change of WT over Shh-/-;Gli3-/-.

    Figure 4—source data 2. MicroChIP H3K27ac enrichment in Shh-/-;Gli3-/- limb buds at HH-responsive GBRs with H3K27me3 in Shh-/- limbs.

    List of 31 HH-responsive GBRs with H3K27me3 enrichment in Shh-/- limb buds and their enrichment of H3K27ac in Shh-/-;Gli3-/-. 20 of the 31 regions were detected in the H3K27ac MicroChIP analyses, those not detected are noted. For the 20 regions detected, they are classified as having H3K27ac in Shh-/-;Gli3-/- as ‘present/increased’ or ‘absent/decreased’ compared to WT controls.

    Figure 5—source data 1. HDAC1 ChIP-seq analyzed data and called peaks.

    HDAC1 binding regions with called peaks with a false discovery rate (FDR) < 0.05 from four biological replicates of E11.5 (40–44S) pooled forelimbs and hindlimbs. Rank ordered coordinates, peak length, log2 fold change (log2FC) and FDR are listed for each peak.

    Figure 6—source data 1. Stable and HH-responsive GLI binding regions with limb enhancer activity in the VISTA dataset.

    Tab 1. Columns indicate VISTA enhancer IDs, coordinates, number of tissues with limb enhancer activity as annotated by the VISTA database (Visel et al., 2007) and its corresponding GBR category. Tabs 2–5. Normalized signal and called peaks for H3K27ac, ATAC, H3K4me1 and H3K4me2 in WT, and Shh-/- limbs if applicable, is listed for all HH-responsive GBRs (Tab 2- normalized signal; Tab 3-called peaks) and Stable GBRs (Tab 4- normalized signal, Tab 5-called peaks) that were shown to drive limb activity, as tested in the VISTA database. For called peaks in Tabs 3, 5, ‘NO’ denotes not a significantly called peak, ‘YES’ denotes a called peak.

    Figure 6—source data 2. NIH3T3 H3K27ac ChIP-seq analyzed data and called peaks.

    H3K27ac called peaks with a FDR < 0.05 from two replicates of purmorphamine (‘pm’) treated or DMSO control NIH3T3 cells. For each peak, the assigned Peak ID, coordinates, peak type, fold change normalized to input for purmorphamine treated and control samples, and fold change of purmorphamine treated over control are listed. Additional tabs include sorted files for each peak type.

    Transparent reporting form

    Data Availability Statement

    Sequencing data has been deposited in GEO (accession GSE108880).

    The following dataset was generated:

    Lex RK, Ji Z, Falkenstein KN, Zhou W, Henry JL, Ji H, Vokes. SA 2020. GLI transcriptional repression regulates enhancer activity and chromatin accessibility for Hedgehog target genes. NCBI Gene Expression Omnibus. GSE108880

    The following previously published datasets were used:

    Lewandowski JP, Du F, Zhang S, Powell MB, Falkenstein KN, Ji H, Vokes SA. 2015. RNA sequencing of mouse littermate wild-type and Shh null E10.5 forelimbs [Illumina] NCBI Gene Expression Omnibus. GSE58645

    ENCODE DCC. 2016. ChIP-seq from limb (ENCSR238SGC) NCBI Gene Expression Omnibus. GSE86690


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