Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq

Arnold, Cosmas D.; Gerlach, Daniel; Stelzer, Christoph; Boryń, Łukasz M.; Rath, Martina; Stark, Alexander

doi:10.1126/science.1232542

Cited by 955 publications

(1,309 citation statements)

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“…Next, we compared the barcode reporter activity levels measured by CHEQ-seq to the existing multiplex enhancer-reporter method STARR-seq (Arnold et al 2013), using the same captured fragments and the same transfection conditions (Supplemental Figs. S9, S10; Supplemental Table S3).…”

Section: Resultsmentioning

confidence: 99%

“…S1A). These enriched DNA fragments, averaging 500 base pairs, are then cloned upstream of a fluorescent protein reporter preceded by a minimal promoter and a synthetic intron (Arnold et al 2013) and followed by a 17 base pair random barcode allowing for 17 × 10 9 possible barcodes (Methods). Using CHEQ-seq, we tested the enhancer activity of 1526 TP53 ChIP-seq peaks obtained in MCF7 breast cancer cells treated with Nutlin-3a (Janky et al 2014).…”

Section: Resultsmentioning

confidence: 99%

“…Whereas classically enhancer-reporter assays consist of cloning each enhancer one by one, first in vitro, later in vivo (Banerji et al 1981;O'Kane and Gehring 1987;Chiocchetti et al 1997;Dailey 2015), now hundreds to thousands of enhancers can be tested in parallel (Patwardhan et al 2009(Patwardhan et al , 2012Kwasnieski et al 2012;Melnikov et al 2012;Arnold et al 2013;Kheradpour et al 2013;Smith et al 2013;White et al 2013;Vanhille et al 2015). These methods can be broadly categorized in two groups, namely, massively parallel reporter assays (MPRA) utilizing barcodes as a measure of activity of synthesized enhancer fragments (Patwardhan et al 2009(Patwardhan et al , 2012Kwasnieski et al 2012;Melnikov et al 2012;Kheradpour et al 2013;Smith et al 2013;White et al 2013) and self-transcribing active regulatory region sequencing (STARR-seq) (Arnold et al 2013;Vanhille et al 2015).…”

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Multiplex enhancer-reporter assays uncover unsophisticated TP53 enhancer logic

et al. 2016

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Transcription factors regulate their target genes by binding to regulatory regions in the genome. Although the binding preferences of TP53 are known, it remains unclear what distinguishes functional enhancers from nonfunctional binding. In addition, the genome is scattered with recognition sequences that remain unoccupied. Using two complementary techniques of multiplex enhancer-reporter assays, we discovered that functional enhancers could be discriminated from nonfunctional binding events by the occurrence of a single TP53 canonical motif. By combining machine learning with a meta-analysis of TP53 ChIP-seq data sets, we identified a core set of more than 1000 responsive enhancers in the human genome. This TP53 cistrome is invariably used between cell types and experimental conditions, whereas differences among experiments can be attributed to indirect nonfunctional binding events. Our data suggest that TP53 enhancers represent a class of unsophisticated cell-autonomous enhancers containing a single TP53 binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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confidence: 99%

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Multiplex enhancer-reporter assays uncover unsophisticated TP53 enhancer logic

et al. 2016

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“…For example, recently several high-throughput enhancer screens (e.g. STARR-seq) (Arnold et al, 2013) have been reported. Similarly, more hi-C based datasets are also available for different cell types.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

EnhancerAtlas: a resource for enhancer annotation and analysis in 105 human cell/tissue types

et al. 2016

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Motivation: Multiple high-throughput approaches have recently been developed and allowed the discovery of enhancers on a genome scale in a single experiment. However, the datasets generated from these approaches are not fully utilized by the research community due to technical challenges such as lack of consensus enhancer annotation and integrative analytic tools. Results: We developed an interactive database, EnhancerAtlas, which contains an atlas of 2,534,123 enhancers for 105 cell/tissue types. A consensus enhancer annotation was obtained for each cell by summation of independent experimental datasets with the relative weights derived from a cross-validation approach. Moreover, EnhancerAtlas provides a set of useful analytic tools that allow users to query and compare enhancers in a particular genomic region or associated with a gene of interest, and assign enhancers and their target genes from a custom dataset. Availability and Implementation: The database with analytic tools is available at http://www.enhan ceratlas.org/.

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“…STAP-seq is a clever inverse of the successful STARR-seq method 9 for probing enhancer activity developed by the same group. The authors construct a candidate libraryand use it to assess sequence-intrinsic core promoter strength and promoter potential of candidate regions that span the entire Drosophila genome (Figure 1a In the second paper, van Arensbergen et al 8 introduce SuRE, which similarly queries the autonomous promoter activity of random genomic fragments outside of their genomic context using a defined reporter assay.…”

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confidence: 99%