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Transcription imparts architecture, function and logic to enhancer units

Abstract

Distal enhancers play pivotal roles in development and disease yet remain one of the least understood regulatory elements. We used massively parallel reporter assays to perform functional comparisons of two leading enhancer models and find that gene-distal transcription start sites are robust predictors of active enhancers with higher resolution than histone modifications. We show that active enhancer units are precisely delineated by active transcription start sites, validate that these boundaries are sufficient for capturing enhancer function, and confirm that core promoter sequences are necessary for this activity. We assay adjacent enhancers and find that their joint activity is often driven by the stronger unit within the cluster. Finally, we validate these results through functional dissection of a distal enhancer cluster using CRISPR–Cas9 deletions. In summary, definition of high-resolution enhancer boundaries enables deconvolution of complex regulatory loci into modular units.

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Fig. 1: Divergent transcription identifies enhancer boundaries in high resolution.
Fig. 2: Transcription marks active eSTARR-seq enhancers.
Fig. 3: Enhancer unit boundaries reveal sequence architecture.
Fig. 4: Function and features of enhancer TSS.
Fig. 5: Functional dissection of adjacent enhancers.
Fig. 6: Dissection of the NMU enhancer.

Data availability

The eSTARR-seq data are available through the ENCODE data portal (www.encodeproject.org) under accession nos. ENCSR514FNW, ENCSR729EGU and ENCSR585AGE. Processed GRO-cap data were obtained from the Gene Expression Omnibus (accession no. GSE60456). Raw sequencing files for the HiDRA study were obtained from the Sequence Read Archive (accession no. SRP118092). All candidate regulatory element clones generated in this study and used for the eSTARR-seq and luciferase assays are available upon request. Please address requests to haiyuan.yu@cornell.edu. Source data are provided with this paper.

Code availability

All analysis scripts are available as R Jupyter Notebooks on Github (https://github.com/hyulab/eSTARR).

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Acknowledgements

The human pSTARR-seq plasmid was a gift from A. Stark (plasmid 71509; Addgene). We thank M. Gasperini, J. Tome and J. Shendure for sharing the clonal ∆eNMU K562 cells and helpful advice. We thank C. Fulco and J. Engreitz for helpful discussions and guidance. This work was supported by grants from the National Institutes of Health (HG009393 to J.T.L. and H.Y.; GM25232 to J.T.L.; DK115398 and HG008126 to H.Y.). N.D.T. was supported by a Cornell University Center for Vertebrate Genomics Scholarship and National Institutes of Health training grant T32HD057854.

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Authors and Affiliations

Authors

Contributions

N.D.T., J.L., A.O., J.T.L. and H.Y. conceived the project and designed the enhancer comparison screen. N.D.T. conceived the dissecting enhancer cooperativity and mechanisms. J.L. performed cloning, primer design, Cas9 deletions and all eSTARR- and Clone-seq assays. N.D.T. optimized and prepared the enhancer fusions with guidance from A.O., H.Y. and J.T.L. N.D.T. and A.K-Y.L. performed the analysis with feedback from J.G.B., J.L., A.O., J.T.L. and H.Y. S.D.W. designed the single guide RNAs. N.D.T. wrote the manuscript with feedback from all authors.

Corresponding authors

Correspondence to John T. Lis or Haiyuan Yu.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Design and validation of eSTARR-seq and selected candidates.

a, Size distribution of candidates is shown by ChromHMM class. b, Correlation between luciferase, STARR-seq, and eSTARR-seq reporter activity in HeLa cells. Luciferase and STARR-seq data are from (Arnold et al., 2013). c, eSTARR-seq activity is shown relative to each elements’ size for both candidate elements (blue) and negative controls (gray). Line indicates a fitted loess curve estimate of size bias for eSTARR-seq and 95% confidence interval in gray.

Extended Data Fig. 2 Comparison with the SCP1 promoter.

a, Correlation between replicates using SCP1. b, eSTARR-seq activity vs element length using SCP1, averaged from n = 3 transfection replicates. c, eSTARR-seq activity in forward vs reverse cloning orientations using SCP1 (averaged from n = 3). d, Percent of elements from each ChromHMM class with significant enhancer activity for SCP1. Error bars indicate standard error calculated for a sample of binary trials, centered on the observed success rate. e, SCP1 eSTARR-seq activity of elements cloned using TSS + 60 bp boundaries (x) or TSS + 200 boundaries (y). Gray area shows 95% confidence interval of linear regression from n = 93 elements. f, eSTARR-seq activity of MYC (x) vs SCP1 (y) as the promoter. Colors indicate enhancers shared by both promoters (blue), active with only one promoter (red), or inactive with both promoters (gray). g, Percent of elements from each ChromHMM class with significant enhancer activity for both MYC promoter and SCP1. Error bars indicate standard error calculated for a sample of binary trials, centered on the observed probability. h, Venn diagram showing overlap of the MYC promoter and SCP1 active enhancer sets.

Extended Data Fig. 3 Validation of strand bias and TSS function from HiDRA.

a, Pie chart indicating the fraction of HiDRA fragments tested in one (gray) or both (gold) orientations. Some fragments have pairings with more than one fragment in the opposing orientation, providing 763,000 distinct pairs. b, Comparison of HiDRA enhancer activities from opposing orientations of fragment pairs. Color indicates the number of pairs. Gray lines denote approximate statistical cut-off for active enhancers. Quadrants II and III denote orientation-dependent ‘enhancer’ fragment pairs; quadrant IV fragments are active in both orientations. c, Pie chart indicating the percent of HiDRA fragment pairs classified as inactive, orientation-dependent, and orientation-independent. de, Bar charts indicating the percentage of orientation-independent enhancer calls from HiDRA fragments sample from DHSs within the indicated ChromHMM classes. d, fragments are further classified as untranscribed or transcribed (contains divergent GRO-cap TSSs). P-values are from two-sided Fisher’s exact test between indicated ratio and total enhancer ratio (140/4,367). e, fragments are sampled from different areas around unpaired GRO-cap TSSs (see cartoon and Methods). Raw fragment counts are shown above each bar. Gray line marks the average percent activity of all fragments. P-values are from two-sided Fisher’s exact test between indicated ratio and total enhancer ratio (402/11,579). All error bars indicate standard error calculated for a sample of binary trials, centered on the observed probability.

Extended Data Fig. 4 Orientation dependence in the HiDRA dataset.

a, Comparison of forward vs reverse cloning orientation for HiDRA fragments overlapping GM12878 DHS peaks. Data points are shown as log2 fold-change of RNA vs DNA read counts. Elements with significantly elevated activity in both orientations are called orientation-independent enhancers (green). Elements with significantly elevated activity in one orientation are called orientation-dependent (black). Remaining fragments are called inactive (gray). b-c, Percent of orientation-dependent (b) or -independent (c) fragments within each GRO-cap and ChromHMM class. Raw fragment counts are shown above each bar. Gray line marks the percent activity of all fragments judged by the same criteria. P-values are from two-sided Fisher’s exact test between indicated ratio and total enhancer ratio (372/4,367 for b, 41/767 for c). Error bars indicate standard error calculated for a sample of binary trials, centered on the observed probability.

Extended Data Fig. 5 Features of eSTARR-seq enhancers.

a, Scatterplot of activity vs GRO-cap reads from eSTARR enhancers in K562 cells. b, Metaplots of average H3K27ac, H3K4me3, and H3K4me1 ChIP-seq signal from different element classes defined in K562 cells. Promoters are defined as GRO-cap divergent TSSs within 500 bp of GENCODE gene start, whereas enhancers are defined as GRO-cap divergent TSSs with significant eSTARR activity. Below, ChIP-seq to GRO-cap signal ratio is shown within the window. c, Metaplots of average H3K27ac, H3K4me3, and H3K4me1 ChIP-seq signal from different element classes defined in GM12878 cells. Promoters are defined as GRO-cap divergent TSSs within 500 bp of GENCODE gene start, whereas enhancers are defined as GRO-cap divergent TSSs with significant HiDRA activity. Below, ChIP-seq to GRO-cap signal ratio is shown within the window. n = 860 promoter DHS, 119 transcribed enhancer DHS, 1,100 untranscribed DHS.

Extended Data Fig. 6 Functional dissection of genomic TSS clusters.

a, Comparison of forward vs reverse cloning orientation for all tested TSS clusters. Data points are shown as log2 fold-change vs negative controls (magenta), averaged from three replicates. Positive controls (black) are known MYC or viral enhancers. Clusters with significantly elevated activity in both orientations are called enhancers (green). All other clusters are called inactive (gray). b, Comparison of sub-element activities within active enhancer clusters. The stronger sub-element is always chosen to be e1, and the weaker sub-element is e2. Gray lines indicate approximate significance cut-offs.

Extended Data Fig. 7 Design and evaluation of synthetic unit pairs.

a, Comparison of sub-element activities within synthetic enhancer clusters. The stronger sub-element is always chosen to be e1, and the weaker sub-element is e2. Gray lines indicate approximate significance cut-offs. b, Correlation between individual eSTARR-seq activities tested previously and re-tested as controls in the synthetic fusion screen (n = 48 elements). c, Agreement between predicted and observed cluster activities (‘C’) for enhancer-containing synthetic pairs. d, Agreement between predicted and observed cluster activities (‘C’) for enhancer-less synthetic pairs.

Extended Data Fig. 8 Genotyping of Cas9 deletion clones.

a, Illustration of genotyping PCR amplicon design and size relative to elements targeted for deletion. b, Table listing expected amplicon sizes from various genotypes. ‘-‘ indicates that no amplification is expected. c, Gel images from K562 clonal lines used for qRT-PCR experiments in Fig. 6. (eNMU clones were generated, genotyped and generously provided by the Shendure lab.) Genotyping PCRs were performed only once, but biological replication was achieved through independent clones.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Primer sequences used in this study.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 8

Unprocessed stained DNA gels.

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Tippens, N.D., Liang, J., Leung, A.KY. et al. Transcription imparts architecture, function and logic to enhancer units. Nat Genet 52, 1067–1075 (2020). https://doi.org/10.1038/s41588-020-0686-2

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