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Hierarchy within the mammary STAT5-driven Wap super-enhancer

Nature Genetics volume 48, pages 904–911 (2016)Cite this article

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Abstract

Super-enhancers comprise dense transcription factor platforms highly enriched for active chromatin marks. A paucity of functional data led us to investigate the role of super-enhancers in the mammary gland, an organ characterized by exceptional gene regulatory dynamics during pregnancy. ChIP-seq analysis for the master regulator STAT5A, the glucocorticoid receptor, H3K27ac and MED1 identified 440 mammary-specific super-enhancers, half of which were associated with genes activated during pregnancy. We interrogated the Wap super-enhancer, generating mice carrying mutations in STAT5-binding sites within its constituent enhancers. Individually, the most distal site displayed the greatest enhancer activity. However, combinatorial mutation analysis showed that the 1,000-fold induction in gene expression during pregnancy relied on all enhancers. Disabling the binding sites of STAT5, NFIB and ELF5 in the proximal enhancer incapacitated the entire super-enhancer. Altogether, these data suggest a temporal and functional enhancer hierarchy. The identification of mammary-specific super-enhancers and the mechanistic exploration of the Wap locus provide insights into the regulation of cell-type-specific expression of hormone-sensing genes.

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Figure 1: Identification of mammary-specific super-enhancers.
Figure 2: Transcription factor binding signatures in mammary-specific super-enhancers.
Figure 3: Assembly at constituent enhancers in mammary-specific super-enhancers during pregnancy.
Figure 4: In vivo functions of individual enhancers in the mammary-specific Wap super-enhancer.
Figure 5: Consequences of individual and combined loss of STAT5-binding sites at enhancers in the mammary-specific Wap super-enhancer.
Figure 6: In vivo function of the E1 epicenter in the Wap super-enhancer.

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Acknowledgements

We thank H. Smith from the NIDDK genomics core for never-ending help with next-generation sequencing and C. Liu from the NHLBI transgenic core for generating the CRISPR/Cas9-based mouse mutants. M.W. is a graduate student of the Individual Graduate Partnership Program (GPP) between NIH/NIDDK and the Medical University of Innsbruck. This work was performed in partial fulfillment of the graduation requirements for M.W. We thank K. Kang and S. Oh for discussions in the early stage of this project and Z. Trajanoski for advising M.W. during her graduate studies. This research was funded by the IPR of the NIDDK/NIH.

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  1. Ha Youn Shin, Michaela Willi and Kyung Hyun Yoo: These authors contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Genetics and Physiology, National Institute of Diabetes, Digestive and Kidney Diseases, US National Institutes of Health, Bethesda, Maryland, USA

    Ha Youn Shin, Michaela Willi, Kyung Hyun Yoo, Xianke Zeng, Chaochen Wang, Gil Metser & Lothar Hennighausen

  2. Division of Bioinformatics, Biocenter, Medical University of Innsbruck, Innsbruck, Austria

    Michaela Willi

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Contributions

H.Y.S. designed, executed and supervised genotyping, identified and validated all CRISPR/Cas9-based mutant founders, performed ChIP-seq, gene expression experiments and histological analysis, analyzed data and wrote the manuscript. M.W. designed experiments, analyzed ChIP-seq and RNA-seq data, performed computational and statistical analyses, and wrote the manuscript. K.H.Y. designed and conducted ChIP-seq, performed gene expression experiments and histological analysis, and analyzed data. X.Z. conducted genotyping, and performed and analyzed gene expression experiments for mutant mice. C.W. performed DNase-seq and ChIP-seq experiments and analyzed data. G.M. genotyped mutant mice, performed and analyzed gene expression experiments, and identified founder mice carrying mutations in combination. L.H. conceived and supervised the study, analyzed data and wrote the manuscript. H.Y.S., M.W. and L.H. wrote and finalized the manuscript, and all authors reviewed and approved the submitted version.

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Correspondence to Lothar Hennighausen.

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Integrated supplementary information

Supplementary Figure 1 Representative scatterplots validating the reproducibility of ChIP-seq replicates.

(a) Reproducibility of STAT5A ChIP-seq peaks at L1. r is Spearman’s correlation coefficient. (b) Reproducibility of H3K27ac ChIP-seq peaks at L1. (c) Reproducibility of MED1 ChIP-seq peaks at L1. (d) Reproducibility of NFIB ChIP-seq peaks at L1. (e) Reproducibility of ELF5 ChIP-seq peaks at L1. (f) Reproducibility of STAT5A ChIP-seq peaks at p13.

Supplementary Figure 2 Identification of mammary-specific super-enhancers.

ChIP-seq peak calling was conducted for two STAT5A replicates. Of a total of 15,790 verified peaks, 10,953 coincided with H3K27ac marks (±500 bp). 549 of these peaks coincided with known promoter regions and 10,404 were located in non-promoter regions. 5,503 of these coincided with a GAS motif (TTCNNNGAA) (±250 bp). The non-promoter STAT5 peaks served as the basis for the super-enhancer analysis calculation applying the ROSE algorithm. As the size of mammary-specific super-enhancers might be different from that of super-enhancers identified in embryonic stem cells, the analysis was carried out using three stitched sizes: 12.5 kb, 25 kb and 35 kb. To obtain only mammary-specific super-enhancers, each stitched size was used as a parameter for the calculations based on STAT5A peaks and H3K27ac, GR and MED1. The basic workflow for the analysis was applied for the three stitching sizes. The first step comprised the application of the ROSE algorithm based on STAT5A peaks: (i) a stitching size of 12.5 kb for H3K27ac returned 504 super-enhancers, for GR returned 592 super-enhancers and for MED1 returned 347 super-enhancers; (ii) the stitching size of 25 kb resulted in 392 super-enhancers for H3K27ac, 359 super-enhancers for GR and 191 super-enhancers for MED1; and (iii) the third applied size of 35 kb specified 428 super-enhancers for H3K27ac, 424 super-enhancers for GR and 199 super-enhancers for MED1. Subsequently, these super-enhancers were overlapped, and only super-enhancers identified and reproduced for at least two factors (gray) were considered for following analysis. With regard to the three stitching sizes, this criterion was satisfied by 405 super-enhancers for 12.5 kb, 272 super-enhancers for 25 kb and 311 super-enhancers for 35 kb. Mammary-specific super-enhancers were identified from the subtraction of STAT5 super-enhancers shared with T cells and liver (12.5 kb), if at least 30% of the mammary super-enhancer overlapped with the T cell and liver ones. 347 mammary-specific super-enhancers were identified in the category with 12.5 kb, 233 mammary-specific enhancers were identified for the category with 25 kb and 270 mammary-specific super-enhancers were identified using a stitched size of 35 kb. These mammary-specific super-enhancers were annotated taking into account the two nearest genes, choosing the one with the higher FPKM value based on expression data obtained at day 1 of lactation. In the final step, nested super-enhancers, which had been annotated to the same gene, were removed, and a total of 440 high-confidence mammary-specific super-enhancers were obtained.

Supplementary Figure 3 Super-enhancers in mammary tissue.

(a) The Glycam1 locus is shown as an example of a mammary-specific super-enhancer. STAT5 binding and H3K27ac marks exist only in mammary tissue but not in T cells or liver. (b) The Aldoc locus is shown as an example of a highly expressed mammary gene with a lone enhancer.

Supplementary Figure 4 Transcription factor binding profile within a mammary-specific super-enhancer.

The Olah super-enhancer consists of three constituent enhancers (asterisk) that feature colocalization of STAT5A, GR, NFIB, ELF5, MED1 and H3K27ac.

Supplementary Figure 5 Gene expression of super-enhancers at day 13 of pregnancy.

Established super-enhancers (n = 22; mean of ~205 FPKM) show higher gene expression at day 13 of pregnancy than progressive super-enhancers from groups II and III (n = 386; mean of ~46 FPKM). Median, middle bar inside the box; IQR, 50% of the data; whiskers, 1.5 times the IQR.

Supplementary Figure 6 Transcription factor binding at a putative super-enhancer controlling the Csn locus.

(a) Transcription factor binding is shown at day 13 of pregnancy and day 1 of lactation. Transcription factor binding and H3K27ac marks are similar at these two developmental stages. (b) STAT5A binding and H3K27ac marks are shown at days 13, 14 and 16 of pregnancy and day 1 of lactation. STAT5A binding and H3K27ac marks are similar across the developmental stages.

Supplementary Figure 7 Alveolar development at days 13, 14 and 16 of pregnancy and day 1 of lactation.

(a) Sections of mammary tissue stained with hematoxylin and eosin at days 13, 14 and 16 of pregnancy and day 1 of lactation with low magnification (400×). The arrow indicates alveoli. At days 13 and 14 of pregnancy, mammary glands were sparsely filled with undeveloped alveoli. The degree of alveolar occupancy was similar at day 16 of pregnancy. At day 1 of lactation, mammary glands were filled with fully differentiated alveoli containing milk (asterisk). (b) Sections of mammary tissue stained with hematoxylin and eosin at days 13, 14 and 16 of pregnancy and day 1 of lactation with high magnification (800×).

Supplementary Figure 8 Scatterplots showing the relationship between mammary epithelial cell and mammary tissue ChIP-seq.

(a) The scatterplot depicts the correlation between mammary tissue and MECs at day 13 of pregnancy. r is Spearman’s correlation coefficient. (b) The scatterplot depicts the correlation between mammary tissue and MECs at day 1 of lactation.

Supplementary Figure 9 Characterization of mutant mice generated by CRISPR/Cas9, TALEN and homologous recombination to introduce point mutations.

ΔE1a carries an 11-bp deletion spanning the GAS motif in E1 (0.7 kb upstream of the TSS), and ΔE1b has a 27-bp deletion spanning the GAS motif and juxtaposed NFIB motif in E1. ΔE1c carries point mutations in the GAS, NFIB and ELF5 motifs in E1. The GAS motif is in red, the NFIB motif is in blue and the ELF5 motif is in green. Point mutations are underlined. ΔE2 has a 26-bp deletion spanning the GAS motif in E2 (1.4 kb upstream of the TSS), and ΔE3 has an 11-bp deletion spanning the GAS motif in E3 (5.6 kb upstream of the TSS). ΔE1a/ΔE2 has a 16-bp deletion spanning the GAS motif in E1 and a 6-bp deletion spanning the GAS motif in E2. ΔE2/ΔE3 has a 9-bp deletion spanning the GAS motif in E2 and an 11-bp deletion spanning the GAS motif in E3. ΔE1a/ΔE2/ΔE3 carries deletions in all three GAS sites.

Supplementary Figure 10 Comparison of transcription factor binding at E1 and E2 of the Wap locus.

(a) Binding of STAT5, NFIB and ELF5 does not coincide with the GAS motif at E1, whereas binding of NFIB and ELF5 colocalizes with STAT5 binding at E2. (b) ELF5 binding remains in ΔE1a, whereas ELF5 binding is absent in ΔE2, indicating that ELF5 binding is dependent on STAT5A at the E2 site.

Supplementary Figure 11 Transcription factor binding at the Wap super-enhancer in ΔE1b and ΔE1c mutant mice.

Binding of STAT5A and NFIB was reduced at the E1 site in ΔE1b mutant mice. Binding of STAT5A, NFIB and ELF5 was completely absent at the E1 site in ΔE1c mutant mice. The Lao1 locus is shown as a ChIP-seq control.

Supplementary Figure 12 Establishment of STAT5 enhancers at the Nfib and Elf5 loci.

(a) STAT5A binding and H3K27ac marks are enriched in a putative regulatory region of the Nfib locus. (b) STAT5A binding and H3K27ac marks are enriched in a putative regulatory region of the Elf5 locus.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–12 and Supplementary Tables 4 and 5. (PDF 1827 kb)

Supplementary Table 1

Genes associated with mammary-specific super-enhancers. (XLSX 1702 kb)

Supplementary Table 2

Summary table for current super-enhancer studies. (XLSX 12 kb)

Supplementary Table 3

ChIP-seq mapping quality. (XLSX 20 kb)

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Shin, H., Willi, M., Yoo, K. et al. Hierarchy within the mammary STAT5-driven Wap super-enhancer. Nat Genet 48, 904–911 (2016). https://doi.org/10.1038/ng.3606

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