Transcriptional enhancers function as docking platforms for combinations of transcription factors (TFs) to control gene expression. How enhancer sequences determine nucleosome occupancy, TF recruitment and transcriptional activation in vivo remains unclear. Using ATAC–seq across a panel of Drosophila inbred strains, we found that SNPs affecting binding sites of the TF Grainy head (Grh) causally determine the accessibility of epithelial enhancers. We show that deletion and ectopic expression of Grh cause loss and gain of DNA accessibility, respectively. However, although Grh binding is necessary for enhancer accessibility, it is insufficient to activate enhancers. Finally, we show that human Grh homologs—GRHL1, GRHL2 and GRHL3—function similarly. We conclude that Grh binding is necessary and sufficient for the opening of epithelial enhancers but not for their activation. Our data support a model positing that complex spatiotemporal expression patterns are controlled by regulatory hierarchies in which pioneer factors, such as Grh, establish tissue-specific accessible chromatin landscapes upon which other factors can act.

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We would like to thank F. Casares for helpful discussions, L. Vanden Broeck (KU Leuven) for sharing the DGRP lines with us, S. Bray (University of Cambridge) for sharing the UAS::grhN line and for insightful discussions, and M. Harrison (UW School of Medicine and Public Health) for sharing antibody to the C terminus of Grh. Stocks obtained from the Bloomington Drosophila Stock Center (NIH grant no. P40OD018537) were used in this study. Computing was performed at the Flemish Supercomputer Center (VSC). This work was supported by funding from FWO project grants (grant no. G.0640.13 (S. Aerts), G.0791.14 (S. Aerts), G.0C04.17 (S. Aerts) and G.0954.16 N (G. Halder)), Special Research Fund (BOF) KU Leuven grants (grant no. PF/10/016 and OT/13/103; to S. Aerts), the Foundation Against Cancer (grant no. 2012-F2 and 2016-070; to S. Aerts), an ERC CoG grant (724226_cis-CONTROL; S. Aerts), PhD fellowships from the Flemish Agency for Innovation by Science and Technology (J.J., K.D. and H.I.) and a postdoctoral research fellowship from Kom op tegen Kanker (Stand up to Cancer), the Flemish Cancer Society (J.W.).

Author information


  1. VIB Center for Brain and Disease Research, Laboratory of Computational Biology, Leuven, Belgium

    • Jelle Jacobs
    • , Kristofer Davie
    • , Hana Imrichova
    • , Valerie Christiaens
    • , Gert Hulselmans
    • , Delphine Potier
    • , Jasper Wouters
    • , Carmen B. González-Blas
    • , Duygu Koldere
    • , Sara Aibar
    •  & Stein Aerts
  2. KU Leuven, Department of Human Genetics, Leuven, Belgium

    • Jelle Jacobs
    • , Kristofer Davie
    • , Hana Imrichova
    • , Valerie Christiaens
    • , Gert Hulselmans
    • , Delphine Potier
    • , Jasper Wouters
    • , Carmen B. González-Blas
    • , Duygu Koldere
    • , Sara Aibar
    •  & Stein Aerts
  3. VIB Center for Cancer Biology, Leuven, Belgium

    • Mardelle Atkins
    • , Lucia Romanelli
    •  & Georg Halder
  4. KU Leuven, Department of Oncology, Leuven, Belgium

    • Mardelle Atkins
    • , Lucia Romanelli
    •  & Georg Halder
  5. Bogazici University, Molecular Biology and Genetics, Istanbul, Turkey

    • Ibrahim I. Taskiran
  6. Politecnico di Torino, Automatics and Informatics, Turin, Italy

    • Giulia Paciello


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J.J. and S. Aerts conceived and designed the experiments; J.J. and V.C. performed all of the bulk ATAC–seq analyses and generated flies; K.D. and V.C. performed single-cell ATAC–seq and sorted ATAC–seq; D.P. and V.C. performed ATAC–seq on the Drosophila species; V.C. performed Grh-specific ChIPmentation; L.R., M.A., V.C., D.K. and J.J. performed imaginal disc dissections, staining and imaging; J.J. analyzed the data, with assistance from G. Hulselmans on the evolution part and BLS, assistance from I.I.T. and G.P. on the random forest analyses, assistance from C.B.G.-B. and K.D. on the single-cell analysis and assistance from S. Aibar on DNA footprinting; J.W. performed omni-ATAC–seq on MCF-7 cells and GRHL knockdown; H.I. analyzed the human GRHL data; and J.J. and S. Aerts wrote the manuscript, with insightful feedback from M.A. and G. Halder.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Stein Aerts.

Integrated Supplementary Information

  1. Supplementary Figure 1 Correlation of ATAC–seq peaks between eye–antennal discs (DGRP) and adult brain tissues.

    Spearman correlation between the accessible regions (normalized ATAC–seq reads) of 30 eye–antennal disc samples (DGRP) and 2 adult brain samples. a, Pairwise correlation matrix of all 32 samples. be, Correlation plots visualizing normalized (RPM) ATAC–seq reads for all 34,768 accessible regions (over the 30 EA discs and 2 brain samples). b, Correlation (Spearman’s ρ = 0.95) between irradiated and control tissue. c, Correlation (Spearman’s ρ = 0.90) between different DGRP lines. d, Correlation (Spearman’s ρ = 0.96) between the two adult brain samples. e, Low correlation (Spearman’s ρ = 0.27) between the accessible regions of eye–antennal discs (DGRP 25,199) and adult brain tissues.

  2. Figure Supplementary 2 Single-cell ATAC–seq.

    Comparing single-cell with bulk ATAC–seq. a, Correlation plot between bulk and aggregate single-cell ATAC–seq signal on all 30,774 accessible regions in eye–antennal discs (Spearman’s ρ = 0.83). b, Track visualizing the aggregate ATAC–seq signal of 68 individual single cells and bulk ATAC–seq signal (1 of 30 similar eye–antennal disc samples is shown) around the grh TSS.

  3. Supplementary Figure 3 Atonal motifs are co-conserved in accessible Grainy head enhancers.

    a, Heat map of Ato motif CRM scores across the conserved Grh enhancers, zoomed in on the 92 regions with a conserved Ato motif (BLS over 3 for each region). b, GSEA visualizing enrichment for gain in expression in the Ato gain-of-function mutants versus Ato loss of function (x axis; 13,087 log2 (FC)–ranked genes (GSE16713)), of the 63 genes that are near the 92 conserved Ato–Grh regions (black bars). FDR was calculated by GSEA by randomly permuting the ranked gene list 10,000 times. c, Visualization of Ato- and Grh-binding sites on 20 previously characterized Ato enhancers using TOUCANjs. Six enhancers that have clear Grh binding (ChIP + ATAC + motif) are marked by a red square.

  4. Supplementary Figure 4 Grainy head–mutant phenotypes in eye–antennal discs.

    a, Cross scheme to generate grhIM mutant clones in eye–antennal discs from wandering third-instar larvae. b,b′, Confocal images of eye–antennal discs with grhIM mutant clones. Wild-type cells are marked with GFP and have Grh protein in their nuclei (red, b′), while the grh-mutant clones do not have GFP or detectable Grh protein (reproducible results for four discs each). Scale bars, 100 μm. c,d, Confocal images of eye–antennal discs; nuclei are stained with DAPI (blue) and wild-type cells are stained with GFP (green) and Dcp1, a marker of apoptosis (red, or white in the bottom panels) (reproducible results for three discs each). c,c′, Control with genotype ey3.5-flp/ey3.5-flp; Ubi-GFP/CyO. A regular but sparse pattern of apoptotic cells is observed across the disc (white, c′). d, Disc with Grh-mutant clones, with genotype ey3.5-flp/ey3.5-flp; FRT42 grhIM/FRT42 Ubi-GFP. The non-GFP clones are homozygous mutant for grh (grhIM). Loss of Grh in these clones is associated with increased levels of apoptotic cells, as visualized by Dcp1 expression (d′). e, Cross schemes for the control and largely grhIM mutant eye–antennal discs that were used for ATAC–seq. The control discs have ubiquitous expression of Grh protein (red + blue) across the disc; in the grh-mutant disc, most cells do not have Grh protein (red) anymore (blue only) (reproducible results for five discs). f, Photographs of pupae originating from the grhIM/cell-lethal cross; the top two pupae are controls, which appear normal and were alive or enclosed (n = 111). Pupae from animals with the grhIM mutant discs are shown on the bottom row (zoomed-in view in f′). These grh-mutant animals have lethal defects during pupation. From the initial cross, one-third of animals are expected to be homozygous mutant for Grh; out of 203 pupae, 71 were dead and 132 were alive.

  5. Supplementary Figure 5 Grh motifs used in the random forest classifier and random forest precision-recall curves.

    a, Logos and origin of the five Grh motifs that were used as features in the random forest classifier. b, Precision-recall curves assessing the performance of a random forest classifier to discriminate between all 1,300 bound and all 4,000 unbound Grh motifs. Shown are curves with random order (gray; AUPRC 0.248), random forest with one Grh motif (brown; AUPRC 0.345), random forest using the five Grh motifs (red; AUPRC 0.550), random forest using the five Grh motifs and positive repeats (green; AUPRC 0.634), random forest using the five Grh motifs and GC content (purple; AUPRC 0.674), and a combination of the five Grh motifs, repeats and GC content (blue; AUPRC 0.736) (Methods).

  6. Supplementary Figure 6 DNA-binding domain conservation between Drosophila Grh and the human GRHLs.

    The amino acids that directly interact with specific DNA bases are marked in green; other amino acids that interact with the DNA backbone through hydrogen bonds or Coulomb interactions are marked in yellow. Interactions for GRHL1 were obtained from Ming et al. (Nucleic Acids Res. https://dx.doi.org/10.1093/nar/gkx1299, 2018).

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    Supplementary Figures 1–6, Supplementary Tables 1–6 and Supplementary Notes 1–3

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