Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA308235 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3091490.fastq.gz | Fastqsanger.gz | |||
| SRR3091500.fastq.gz | Fastqsanger.gz | |||
| SRR3091491.fastq.gz | Fastqsanger.gz | |||
| SRR3091501.fastq.gz | Fastqsanger.gz | |||
| SRR3091492.fastq.gz | Fastqsanger.gz |
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Project description:Analysis of p53 binding sites using multiplex enhancer reporter assays, ChIP-seq data and RNA-seq data. Transcription factors establish and maintain the specific transcriptome of a cell by binding to genomic regulatory regions, thereby regulating the transcription of their target genes. Like many transcription factors, the DNA sequence-specific binding preferences of p53 are known. However, it remains largely unclear what distinguishes functional enhancers from other bound genomic regions that have no regulatory activity. In addition, the genome is scattered with seemingly perfect recognition sequences that remain unoccupied. To disentangle the rules of genome-wide p53 binding, we employed two complementary techniques of multiplex enhancer-reporter assays, one using barcoded reporters and the other using enhancer self-transcription. We compared the activity of more than one thousand candidate p53 enhancers under loss and gain of p53 conditions and identified several hundred high-confidence p53-responsive enhancers. Strikingly, the large majority (99%) of these target enhancers can be characterized and distinguished from negative sequences by the occurrence of a single p53 binding site. By training a machine learning classifier on these data, and integrating the resulting genome-wide predictions with fifteen publicly available human p53 ChIP-seq data sets, we identified a consensus set of 1148 functional p53 binding sites in the human genome. Unexpectedly, this direct p53 cistrome is invariably used between cell types and experimental conditions, while differences between experiments can be largely attributed to indirect non-functional binding. Our data suggest that direct p53 enhancers function in a context-independent manner and do not contain obvious combinatorial complexity of binding sites for multiple transcription factors. They represent a class of unsophisticated cell-autonomous enhancers with a single binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors. This suggests that context-dependent regulation of p53 target genes is not encoded in the p53 enhancer, but at different upstream or downstream layers of the cell's gene regulatory network.
2016-05-07 | GSE76653 | GEO
Project description:Analysis of p53 binding sites using multiplex enhancer reporter assays, ChIP-seq data and RNA-seq data. Transcription factors establish and maintain the specific transcriptome of a cell by binding to genomic regulatory regions, thereby regulating the transcription of their target genes. Like many transcription factors, the DNA sequence-specific binding preferences of p53 are known. However, it remains largely unclear what distinguishes functional enhancers from other bound genomic regions that have no regulatory activity. In addition, the genome is scattered with seemingly perfect recognition sequences that remain unoccupied. To disentangle the rules of genome-wide p53 binding, we employed two complementary techniques of multiplex enhancer-reporter assays, one using barcoded reporters and the other using enhancer self-transcription. We compared the activity of more than one thousand candidate p53 enhancers under loss and gain of p53 conditions and identified several hundred high-confidence p53-responsive enhancers. Strikingly, the large majority (99%) of these target enhancers can be characterized and distinguished from negative sequences by the occurrence of a single p53 binding site. By training a machine learning classifier on these data, and integrating the resulting genome-wide predictions with fifteen publicly available human p53 ChIP-seq data sets, we identified a consensus set of 1148 functional p53 binding sites in the human genome. Unexpectedly, this direct p53 cistrome is invariably used between cell types and experimental conditions, while differences between experiments can be largely attributed to indirect non-functional binding. Our data suggest that direct p53 enhancers function in a context-independent manner and do not contain obvious combinatorial complexity of binding sites for multiple transcription factors. They represent a class of unsophisticated cell-autonomous enhancers with a single binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors. This suggests that context-dependent regulation of p53 target genes is not encoded in the p53 enhancer, but at different upstream or downstream layers of the cell's gene regulatory network.
2016-05-07 | GSE76656 | GEO
Project description:Analysis of p53 binding sites using multiplex enhancer reporter assays, ChIP-seq data and RNA-seq data. Transcription factors establish and maintain the specific transcriptome of a cell by binding to genomic regulatory regions, thereby regulating the transcription of their target genes. Like many transcription factors, the DNA sequence-specific binding preferences of p53 are known. However, it remains largely unclear what distinguishes functional enhancers from other bound genomic regions that have no regulatory activity. In addition, the genome is scattered with seemingly perfect recognition sequences that remain unoccupied. To disentangle the rules of genome-wide p53 binding, we employed two complementary techniques of multiplex enhancer-reporter assays, one using barcoded reporters and the other using enhancer self-transcription. We compared the activity of more than one thousand candidate p53 enhancers under loss and gain of p53 conditions and identified several hundred high-confidence p53-responsive enhancers. Strikingly, the large majority (99%) of these target enhancers can be characterized and distinguished from negative sequences by the occurrence of a single p53 binding site. By training a machine learning classifier on these data, and integrating the resulting genome-wide predictions with fifteen publicly available human p53 ChIP-seq data sets, we identified a consensus set of 1148 functional p53 binding sites in the human genome. Unexpectedly, this direct p53 cistrome is invariably used between cell types and experimental conditions, while differences between experiments can be largely attributed to indirect non-functional binding. Our data suggest that direct p53 enhancers function in a context-independent manner and do not contain obvious combinatorial complexity of binding sites for multiple transcription factors. They represent a class of unsophisticated cell-autonomous enhancers with a single binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors. This suggests that context-dependent regulation of p53 target genes is not encoded in the p53 enhancer, but at different upstream or downstream layers of the cell's gene regulatory network.
2016-05-07 | GSE76655 | GEO
Project description:Analysis of p53 binding sites using multiplex enhancer reporter assays, ChIP-seq data and RNA-seq data. Transcription factors establish and maintain the specific transcriptome of a cell by binding to genomic regulatory regions, thereby regulating the transcription of their target genes. Like many transcription factors, the DNA sequence-specific binding preferences of p53 are known. However, it remains largely unclear what distinguishes functional enhancers from other bound genomic regions that have no regulatory activity. In addition, the genome is scattered with seemingly perfect recognition sequences that remain unoccupied. To disentangle the rules of genome-wide p53 binding, we employed two complementary techniques of multiplex enhancer-reporter assays, one using barcoded reporters and the other using enhancer self-transcription. We compared the activity of more than one thousand candidate p53 enhancers under loss and gain of p53 conditions and identified several hundred high-confidence p53-responsive enhancers. Strikingly, the large majority (99%) of these target enhancers can be characterized and distinguished from negative sequences by the occurrence of a single p53 binding site. By training a machine learning classifier on these data, and integrating the resulting genome-wide predictions with fifteen publicly available human p53 ChIP-seq data sets, we identified a consensus set of 1148 functional p53 binding sites in the human genome. Unexpectedly, this direct p53 cistrome is invariably used between cell types and experimental conditions, while differences between experiments can be largely attributed to indirect non-functional binding. Our data suggest that direct p53 enhancers function in a context-independent manner and do not contain obvious combinatorial complexity of binding sites for multiple transcription factors. They represent a class of unsophisticated cell-autonomous enhancers with a single binding site, distinct from complex developmental enhancers that integrate signals from multiple transcription factors. This suggests that context-dependent regulation of p53 target genes is not encoded in the p53 enhancer, but at different upstream or downstream layers of the cell's gene regulatory network.
2016-05-07 | GSE76654 | GEO
Project description: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.
| S-EPMC4937571 | biostudies-literature
Project description:Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic [STARR-seq]
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Project description:Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic [ChIP-seq]
| PRJNA308239 | ENA
Project description:Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic [CHEQ-seq]
| PRJNA308237 | ENA
Project description:Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic [RNA-seq]
| PRJNA308240 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-05-07 | GSE76657 | GEO