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Genome-wide mapping of autonomous promoter activity in human cells

Nature Biotechnology volume 35, pages 145–153 (2017)Cite this article

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Abstract

Previous methods to systematically characterize sequence-intrinsic activity of promoters have been limited by relatively low throughput and the length of the sequences that could be tested. Here we present 'survey of regulatory elements' (SuRE), a method that assays more than 108 DNA fragments, each 0.2–2 kb in size, for their ability to drive transcription autonomously. In SuRE, a plasmid library of random genomic fragments upstream of a 20-bp barcode is constructed, and decoded by paired-end sequencing. This library is used to transfect cells, and barcodes in transcribed RNA are quantified by high-throughput sequencing. When applied to the human genome, we achieve 55-fold genome coverage, allowing us to map autonomous promoter activity genome-wide in K562 cells. By computational modeling we delineate subregions within promoters that are relevant for their activity. We show that antisense promoter transcription is generally dependent on the sense core promoter sequences, and that most enhancers and several families of repetitive elements act as autonomous transcription initiation sites.

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Figure 1: SuRE provides a genome-wide map of autonomous promoter activity.
Figure 2: Autonomous divergent promoter activity.
Figure 3: Partially overlapping query fragments allow for delineation of regions that drive promoter activity.
Figure 4: Relationship between CpG islands and gene expression.
Figure 5: Autonomous transcription from enhancers.
Figure 6: Autonomous transcription from specific repeat elements.

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Acknowledgements

We thank the NKI Genomics Core Facility for technical support, J. Omar Yáñez Cuna for scripts and advice, and members of our laboratories for helpful discussions, and T. Rube in particular for suggesting the 2D analysis of CpG content. Supported by ERC Advanced Grant 293662 and NWO-ALW VICI (B.v.S.); NIH grants R01HG003008 and S10OD021764 (H.J.B.); and NIH grants R01HG003008 and S10OD021764 and T32GM008281 (V.D.F.). Addgene plasmid # 49157 is a gift from James Thomson, University of Wisconsin, Madison.

Author information

Authors and Affiliations

  1. Division of Gene Regulation, Netherlands Cancer Institute, Amsterdam, the Netherlands

    Joris van Arensbergen, Marcel de Haas, Ludo Pagie, Jasper Sluimer & Bas van Steensel

  2. Department of Biological Sciences, Columbia University, New York, New York, USA

    Vincent D FitzPatrick & Harmen J Bussemaker

  3. Department of Systems Biology, Columbia University Medical Center, New York, New York, USA

    Vincent D FitzPatrick & Harmen J Bussemaker

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  1. Joris van Arensbergen
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Contributions

J.v.A. conceived and developed the SuRE assay, designed and performed experiments, analyzed data and wrote the manuscript.V.D.F. developed algorithms, analyzed data and wrote the manuscript. L.P. developed algorithms and analyzed data. M.d.H. performed experiments. J.S. performed experiments. H.J.B. developed algorithms, analyzed data and wrote the manuscript. B.v.S. designed experiments, analyzed data and wrote the manuscript.

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Correspondence to Joris van Arensbergen, Harmen J Bussemaker or Bas van Steensel.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Detailed schematic representation of SuRE methodology.

See Methods for detailed description. a. Size-selected and A-tailed random fragments (‘queries’) of the human genome are inserted in bulk into barcoded T-overhang plasmids by ligation. BC, barcode; ORF, open reading frame; PAS, polyadenylation signal. b. The library is digested by endonuclease I-CeuI so that the barcode with the query sequence is released. This is then self-ligated and again digested with a frequent cutter restriction enzyme to reduce the insert size. After another self-ligation the circle is linearized, PCR amplified and subjected to high-throughput sequencing. c. Per biological replicate ~100 million cells are transfected. Those plasmids that contain promoter activity in the direction of the barcode will transcribe the barcode into RNA. Cells are harvested after 24 hours, RNA is extracted, polyA purified, reverse transcribed, PCR amplified and subjected to high-throughput sequencing. By normalization to estimated barcode frequencies in the SuRE plasmid library a genome-wide SuRE expression profile is generated.

Supplementary Figure 2 SuRE genome coverage, reproducibility and peaks.

a. Coverage of the human genome by unique elements in the SuRE library. b. Distribution (fold enrichment) of SuRE peaks among the 25 types of chromatin1. c. Correlation of SuRE enrichment between biological replicates at TSSs. d. Correlation between CAGE1 and SuRE at the TSSs. e. Same as Fig. 1e but with Histone genes indicated in red. Correlation between relative promoter autonomy (log10(SuRE/GRO-cap)) and tissue specificity (number of cell types and tissues in which each TSS is active, out of 889 tested2). Grey line shows linear fit. f. Correlation between relative promoter autonomy and the total number of promoters (ENCODE chromatin type ‘Tss’) that are found in a fixed window of 5-50 kb from the TSS. g. Size distribution of genomic fragments in the SuRE library. h. Number of reads (per individual replicate) of barcodes in cDNA. Only barcodes linked to a unique genomic fragment were counted. i. Venn diagram representing the overlap between the summits of SuRE peaks as called by the MACS algorithm3 and ENCODE-annotated promoters (‘Tss’) and enhancers (‘Enh’ and ‘EnhW’ combined)1. Because >1 peak summit can overlap a ENCODE annotation, overlaps are given for each direction of the comparison in the color of the annotation. j. Relative SuRE expression (SuRE/GRO-cap) of SuRE fragments for which the 3’ ends either in an intron (black) or an exon (red). Expression is normalized to GRO-cap to avoid systematic biases resulting from possible correlations between gene structure and expression level. A LOESS curve was separately fit to the logratios for all exon- and intron-terminal fragments using the distance each fragment ended downstream of the corresponding TSS, then predicted ratios were normalized to a maximum of 1.

1. Encode Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74 (2012).

2. FANTOM Consortium. A promoter-level mammalian expression atlas. Nature 507, 462-470 (2014).

3. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol 9, R137 (2008).

Supplementary Figure 3 Focused BAC library.

a. Correlation between biological replicates for the focused SuRE library. Data is shown for all TSSs within in the BAC library. b. Correlation between SuRE enrichment obtained with the genome-wide library (x-axis) and the focused library (y-axis) for all peaks overlapping the BAC library. c. Same as (b) but for all TSSs in the BAC library. d. Correlation between SuRE enrichment obtained with the genome-wide library (x-axis) and a conventional reporter assay (y-axis) for 23 promoters. Grey line shows linear fit. e. Correlation between pre-transfection read-counts and post-transfection read-counts for all TSSs in the BAC library.

Supplementary Figure 4 Run-on transcription around LTR12C elements, antisense.

Average PRO-seq run-on transcription activity4 around LTR12C elements as in Fig. 5e, but in antisense orientation.

4. Core, L.J. et al. Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat Genet 46, 1311-1320 (2014).

Supplementary Figure 5 Chromatin marks associated to unannotated SuRE peaks.

a. Mean enrichment for 4 chromatin marks centered on the summit of unannotated SuRE peaks, i.e. peaks that did not overlap ENCODE annotated promoters or enhancers (‘Tss’ or ‘Enh’ chromatin state) or repetitive elements of the ERV1 or ERVL-MaLR family. b. Same as (a) but for SuRE peaks that overlapped encode annotated promoters. c. Mean SuRE enrichment for all peaks overlapping ENCODE annotated promoters (green) and unannotated SuRE peaks. d. Same as (c) but for mean GRO-cap signal.

Supplementary Figure 6 Envisioned SuRE methodology for enhancer detection.

a. Current SuRE reporter construct for promoter detection. b. Envisioned reporter construct for enhancer detection. Query: genomic fragment, BC: barcode, ORF: open reading frame, PAS: polyadenylation signal, mPR: minimal promoter.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6 and Supplementary Tables 1 and 2 (PDF 1042 kb)

Supplementary Source Code 1

software for SuRE sequencing data processing (ZIP 148 kb)

Supplementary Source Code 2

software for Generalized Linear Modeling (ZIP 198 kb)

Supplementary Data Set

Genomic coordinates of SuRE peaks, and their overlap with promoters, enhancers and repetitive elements. (ZIP 1637 kb)

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van Arensbergen, J., FitzPatrick, V., de Haas, M. et al. Genome-wide mapping of autonomous promoter activity in human cells. Nat Biotechnol 35, 145–153 (2017). https://doi.org/10.1038/nbt.3754

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