Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE76657 | GEO | 2016/05/07
SECONDARY ACCESSION(S): PRJNA308235
REPOSITORIES: GEO
Similar Datasets
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: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 | 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 | GSE76654 | GEO
Project description:Multiplex enhancer-reporter assays uncover unsophisticated p53 enhancer logic
| PRJNA308235 | ENA
Project description:Many single nucleotide polymorphisms (SNPs) associated with type 2 diabetes overlap with putative endocrine pancreatic enhancers, suggesting that these SNPs modulate enhancer activity and, consequently, gene expression. We performed in vivo mosaic transgenesis assays in zebrafish to quantitatively test the enhancer activity of type 2 diabetes-associated loci. Six out of 10 tested sequences are endocrine pancreatic enhancers. The risk variant of two sequences decreased enhancer activity, while in another two incremented it. One of the latter (rs13266634) locates in an SLC30A8 exon, encoding a tryptophan-to-arginine substitution that decreases SLC30A8 function, which is the canonical explanation for type 2 diabetes risk association. However, other type 2 diabetes-associated SNPs that truncate SLC30A8 confer protection from this disease, contradicting this explanation. Here, we clarify this incongruence, showing that rs13266634 boosts the activity of an overlapping enhancer and suggesting an SLC30A8 gain of function as the cause for the increased risk for the disease. We further dissected the functionality of this enhancer, finding a single nucleotide mutation sufficient to impair its activity. Overall, this work assesses in vivo the importance of disease-associated SNPs in the activity of endocrine pancreatic enhancers, including a poorly explored case where a coding SNP modulates the activity of an enhancer.
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Project description:Gene regulatory elements play a key role in orchestrating gene expression during cellular differentiation, but what determines their function over time remains largely unknown. Here, we perform perturbation-based massively parallel reporter assays at seven early time points of neural differentiation to systematically characterize how regulatory elements and motifs within them guide cellular differentiation. By perturbing over 2,000 putative DNA binding motifs in active regulatory regions, we delineate four categories of functional elements, and observe that activity direction is mostly determined by the sequence itself, while the magnitude of effect depends on the cellular environment. We also find that fine-tuning transcription rates is often achieved by a combined activity of adjacent activating and repressing elements. Our work provides a blueprint for the sequence components needed to induce different transcriptional patterns in general and specifically during neural differentiation.
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2021-06-30 | GSE167519 | GEO
Project description:The Ikzf1 locus encodes the lymphoid specific transcription factor Ikaros, which plays an essential role in both T and B cell differentiation, while deregulation or mutation of IKZF1/Ikzf1 is involved in leukemia. Tissue-specific and cell identity genes are usually associated with clusters of enhancers, also called super-enhancers, which are believed to ensure proper regulation of gene expression throughout cell development and differentiation. Several potential regulatory regions have been identified in close proximity of Ikzf1, however, the full extent of the regulatory landscape of the Ikzf1 locus is not yet established. In this study, we combined epigenomics and transcription factor binding along with high-throughput enhancer assay and 4C-seq to prioritize an enhancer element located 120 kb upstream of the Ikzf1 gene. We found that deletion of the E120 enhancer resulted in a significant reduction of Ikzf1 mRNA. However, the epigenetic landscape and 3D topology of the locus were only slightly affected, highlighting the complexity of the regulatory landscape regulating the Ikzf1 locus.
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