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Cited by 159Genomics and Chromatin DynamicsChromatin Remodeling and CancerEpigenetics and DNA Methylation

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Functional assessment of human enhancer activities using whole-genome STARR-sequencing

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Liu, Yuwen, Yu, Shan, Dhiman, Vineet K., Brunetti, Tonya, Eckart, Heather, White, Kevin P.·2017·Genome Biology
DOI 10.1186/s13059-017-1345-5PMC PMC5694901
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Abstract

BACKGROUND: Genome-wide quantification of enhancer activity in the human genome has proven to be a challenging problem. Recent efforts have led to the development of powerful tools for enhancer quantification. However, because of genome size and complexity, these tools have yet to be applied to the whole human genome. RESULTS: In the current study, we use a human prostate cancer cell line, LNCaP as a model to perform whole human genome STARR-seq (WHG-STARR-seq) to reliably obtain an assessment of enhancer activity. This approach builds upon previously developed STARR-seq in the fly genome and CapSTARR-seq techniques in targeted human genomic regions. With an improved library preparation strategy, our approach greatly increases the library complexity per unit of starting material, which makes it feasible and cost-effective to explore the landscape of regulatory activity in the much larger human genome. In addition to our ability to identify active, accessible enhancers located in open chromatin regions, we can also detect sequences with the potential for enhancer activity that are located in inaccessible, closed chromatin regions. When treated with the histone deacetylase inhibitor, Trichostatin A, genes nearby this latter class of enhancers are up-regulated, demonstrating the potential for endogenous functionality of these regulatory elements. CONCLUSION: WHG-STARR-seq provides an improved approach to current pipelines for analysis of high complexity genomes to gain a better understanding of the intricacies of transcriptional regulation.

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Fig. 1 Experimental approach and validation of WHG-STARR-seq. a Schematic representation showing experimental setup and approach for WHG-STARR-seq. b Genomic snapshot displaying the GPI locus region as detected by WHG-STARR-seq. There is a strong enhancer region approximately 10 kb upstream of GPI transcriptional start site and another weaker enhancer region in the 3’UTR of GPI. Each blue track signifies normalized WHG-STARR-seq signal of each biological replicate. The gray track represents normalized WHG-STARR-seq signal of input library. c Distribution of WHG-STARR-seq enhancer activity of all detected enhancers. WHG-STARR-seq shows a wide dynamic range of enhancer signal normalized to INPUT (1.33–119.12, median = 3.08). d Distribution of number of detected enhancers associated per gene (enhancers are assigned to their nearest genes). e The enhancer activity of six active (red) and nine inactive (blue) enhancers were validated using traditional luciferase assays in biological triplicates. A strong correlation was observed between luciferase signal and WHG-STARR-seq enhancer activity
Fig. 1 Experimental approach and validation of WHG-STARR-seq. a Schematic representation showing experimental setup and approach for WHG-STARR-seq. b Genomic snapshot displaying the GPI locus region as detected by WHG-STARR-seq. There is a strong enhancer region approximately 10 kb upstream of GPI transcriptional start site and another weaker enhancer region in the 3’UTR of GPI. Each blue track signifies normalized WHG-STARR-seq signal of each biological replicate. The gray track represents normalized WHG-STARR-seq signal of input library. c Distribution of WHG-STARR-seq enhancer activity of all detected enhancers. WHG-STARR-seq shows a wide dynamic range of enhancer signal normalized to INPUT (1.33–119.12, median = 3.08). d Distribution of number of detected enhancers associated per gene (enhancers are assigned to their nearest genes). e The enhancer activity of six active (red) and nine inactive (blue) enhancers were validated using traditional luciferase assays in biological triplicates. A strong correlation was observed between luciferase signal and WHG-STARR-seq enhancer activityCC BY · PubMed Central
Fig. 2 WHG-STARR-seq enhancers are associated with both open and closed chromatin environments. a Heat maps of various chromatin signal around WHG-STARR-seq enhancers. As generating high-resolution heat maps for all active open or active closed enhancers is too computationally intensive, we randomly sampled 5000 WHG-STARR-seq enhancers from open chromatin regions and from closed chromatin regions, respectively, and plotted signal of WHG-STARR-seq, DNase-seq, H3K4M1, H3K3M2, H3K27Ac, and H3K27M3 around these enhancers. We used all enhancers to make the density plots and boxplots. To make the density plots, we first extended the centers of enhancers to ± 10 kb, and then for each 100-bp tiling window in the extended regions, we calculated the fold enrichment of ChIP signal (normalized by library size) to INPUT signal (normalized by library size) across all windows. We plotted the average of the fold enrichment in the density plots (red: WHG-STARR-seq enhancers; blue: 10,000 random genomic regions). b Boxplots of fold enrichment of signal of various histone marks on WHG-STARR-seq enhancers (±200 bp around enhancer centers) and random genomic regions (±200 bp around random genomic region centers). c Association between gene expression level and nearby WHG-STARR-seq enhancers in open and closed chromatin regions. Enhancers were assigned to their nearest gene. All enhancers were binned into five separate groups according to the rank of enhancer signal (red: active/open enhancers; blue: active/closed enhancers)
Fig. 2 WHG-STARR-seq enhancers are associated with both open and closed chromatin environments. a Heat maps of various chromatin signal around WHG-STARR-seq enhancers. As generating high-resolution heat maps for all active open or active closed enhancers is too computationally intensive, we randomly sampled 5000 WHG-STARR-seq enhancers from open chromatin regions and from closed chromatin regions, respectively, and plotted signal of WHG-STARR-seq, DNase-seq, H3K4M1, H3K3M2, H3K27Ac, and H3K27M3 around these enhancers. We used all enhancers to make the density plots and boxplots. To make the density plots, we first extended the centers of enhancers to ± 10 kb, and then for each 100-bp tiling window in the extended regions, we calculated the fold enrichment of ChIP signal (normalized by library size) to INPUT signal (normalized by library size) across all windows. We plotted the average of the fold enrichment in the density plots (red: WHG-STARR-seq enhancers; blue: 10,000 random genomic regions). b Boxplots of fold enrichment of signal of various histone marks on WHG-STARR-seq enhancers (±200 bp around enhancer centers) and random genomic regions (±200 bp around random genomic region centers). c Association between gene expression level and nearby WHG-STARR-seq enhancers in open and closed chromatin regions. Enhancers were assigned to their nearest gene. All enhancers were binned into five separate groups according to the rank of enhancer signal (red: active/open enhancers; blue: active/closed enhancers)CC BY · PubMed Central
Fig. 3 Inaccessible enhancers are functional upon treatment with TSA. a Venn diagram showing the overlap between active, inaccessible WHG-STARR-seq enhancers and TSA-induced sites. b Comparison of gene expression in response to TSA treatment of global genes and the 401 genes that have nearby WHG-STARR-seq enhancers which were inaccessible under vehicle treatment but became accessible under TSA treatment. Statistical significance was calculated using Wilcox Sum Rank Test (*p = 2.2e-16). c Genomic snapshot displaying ATAC-seq signal at LCE1F locus of LNCaP cells treated with TSA vs vehicle. d Comparison of nearby gene expression in response to TSA treatment of WHG-STARR-seq enhancers that were previously inaccessible, but opened up by TSA treatment (Class I) and regions not active in WHG-STARR-seq and opened up by TSA (Class II). Statistical significance was calculated by Wilcoxon sum rank test (*p = 1.6e-2)
Fig. 3 Inaccessible enhancers are functional upon treatment with TSA. a Venn diagram showing the overlap between active, inaccessible WHG-STARR-seq enhancers and TSA-induced sites. b Comparison of gene expression in response to TSA treatment of global genes and the 401 genes that have nearby WHG-STARR-seq enhancers which were inaccessible under vehicle treatment but became accessible under TSA treatment. Statistical significance was calculated using Wilcox Sum Rank Test (*p = 2.2e-16). c Genomic snapshot displaying ATAC-seq signal at LCE1F locus of LNCaP cells treated with TSA vs vehicle. d Comparison of nearby gene expression in response to TSA treatment of WHG-STARR-seq enhancers that were previously inaccessible, but opened up by TSA treatment (Class I) and regions not active in WHG-STARR-seq and opened up by TSA (Class II). Statistical significance was calculated by Wilcoxon sum rank test (*p = 1.6e-2)CC BY · PubMed Central
Fig. 4 Gene expression levels are quantitatively associated with in chromatin accessibility and enhancer strength. a Comparison of expression levels of genes (denoted as RPKM) with different groups of enhancers nearby. Enhancers were assigned to their nearest gene (no distance cutoff). Statistical significance was calculated using Wilcox sum rank test (*p = 2.2e-16). b 3D plot comparing expression levels of nearby genes in relation to both DNase I signal and enhancer activity. Both DNase I and enhancer signals are binned into six separate groups (0–5) according to the ranks of DNase I and enhancer signals, respectively
Fig. 4 Gene expression levels are quantitatively associated with in chromatin accessibility and enhancer strength. a Comparison of expression levels of genes (denoted as RPKM) with different groups of enhancers nearby. Enhancers were assigned to their nearest gene (no distance cutoff). Statistical significance was calculated using Wilcox sum rank test (*p = 2.2e-16). b 3D plot comparing expression levels of nearby genes in relation to both DNase I signal and enhancer activity. Both DNase I and enhancer signals are binned into six separate groups (0–5) according to the ranks of DNase I and enhancer signals, respectivelyCC BY · PubMed Central

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  1. Liu Y, Yu S, Dhiman V, Brunetti T, Scott H, White K. Genome-wide functional assessment of enhancer activities in the human genome. Gene Expression Omnibus. 2017. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE82204 .

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Metadata

Authors
Liu, Y., Yu, S., Dhiman, V. K., Brunetti, T., Eckart, H., & White, K. P.
Affiliations
  • Argonne National Laboratory (US)
  • University of Chicago (US)
Corresponding author
White, Kevin P.
ORCID
Venue
Genome Biology
Publisher
Springer Science and Business Media LLC
Published
2017-11-20
Volume
18
Issue
1
Pages
219-219
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
DOI
10.1186/s13059-017-1345-5
PMC
PMC5694901
OpenAlex
W2769418303
Cited by
136
References
37
Citations by year
2026: 6 · 2025: 18 · 2024: 21 · 2023: 15 · 2022: 17 · 2021: 15 · 2020: 19 · 2019: 13 · 2018: 11 · 2017: 1
FWCI
5.67
Type
journal article
Language
en
Open access
Licence
Locations
  • Genome biology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Institutes of Health (U54HG006996)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
Keywords
enhancer activity, STARR-seq, LNCaP cells, open chromatin, closed chromatin, histone deacetylase inhibition, trichostatin A, transcriptional regulation, library preparation, prostate cancer
MeSH terms
Whole Genome Sequencing, Cell Line, Chromatin, Enhancer Elements, Genetic, Humans, Genomic Library, Genome, Human, Genomics, Chromatin Immunoprecipitation, High-Throughput Nucleotide Sequencing

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