Transcription factor binding on designed libraries measured by CCRAs
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ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE144437 | GEO | 2020/01/30
REPOSITORIES: GEO
Similar Datasets
Project description:Gene expression is governed by transcription factors (TFs) that commonly recognize short DNA sequence motifs. However, TF recruitment to genomic target sites in chromatin is complex and many parameters that ultimately dictate binding-site specificity are still unknown. Here, we systematically explore the interaction of TFs with synthetic and endogenous G-quadruplexes (G4s) DNA secondary structures. Our findings reveal that certain TFs are directly recruited to promoters by endogenous G4s with binding affinities comparable to canonical B-DNA binding and that endogenous G4-TF interactions can be disrupted with synthetic small molecule ligands. G4s in promoters are bound by a large number of TFs and associated with high transcriptional activity. This discovery of structure-specific recognition expands our understanding of how TFs regulate gene transcription.
2021-03-24 | GSE145090 | GEO
Project description:Most eukaryotic transcription factors (TFs) are part of large protein families, with members of the same family (i.e. paralogous TFs) recognizing similar DNA-binding motifs but performing different regulatory functions. Many TF paralogs are co-expressed in the cell, and thus can compete for target sites across the genome. Here, we show that direct competition for DNA binding between TF paralogs is a major determinant of their genomic binding patterns. Using yeast proteins Cbf1 and Pho4 as our model system, we designed a high-throughput quantitative assay to capture the genomic binding profiles of competing TFs in a cell-free system. Our data shows that Cbf1 and Pho4 greatly influence each other’s occupancy by competing for their common putative genomic binding sites. The competition is different at different genomic sites, as dictated by the TFs' expression levels and their divergence in DNA-binding specificity and affinity. Analyses of ChIP-seq data show that the biophysical rules that dictate the competitive TF binding patterns in vitro are also followed in vivo, in the complex cellular environment. Furthermore, the Cbf1-Pho4 competition for genomic sites, as characterized in vitro using our new assay, plays a critical role in the specific activation of their target genes in the cell. Overall, our study highlights the importance of direct TF-TF competition for genomic binding and gene regulation by TF paralogs, and proposes an approach for studying this competition in a quantitative and high-throughput manner.
2021-04-22 | GSE163511 | GEO
Project description:Most eukaryotic transcription factors (TFs) are part of large protein families, with members of the same family (i.e. paralogous TFs) recognizing similar DNA-binding motifs but performing different regulatory functions. Many TF paralogs are co-expressed in the cell, and thus can compete for target sites across the genome. Here, we show that direct competition for DNA binding between TF paralogs is a major determinant of their genomic binding patterns. Using yeast proteins Cbf1 and Pho4 as our model system, we designed a high-throughput quantitative assay to capture the genomic binding profiles of competing TFs in a cell-free system. Our data shows that Cbf1 and Pho4 greatly influence each other’s occupancy by competing for their common putative genomic binding sites. The competition is different at different genomic sites, as dictated by the TFs' expression levels and their divergence in DNA-binding specificity and affinity. Analyses of ChIP-seq data show that the biophysical rules that dictate the competitive TF binding patterns in vitro are also followed in vivo, in the complex cellular environment. Furthermore, the Cbf1-Pho4 competition for genomic sites, as characterized in vitro using our new assay, plays a critical role in the specific activation of their target genes in the cell. Overall, our study highlights the importance of direct TF-TF competition for genomic binding and gene regulation by TF paralogs, and proposes an approach for studying this competition in a quantitative and high-throughput manner.
2021-04-22 | GSE163509 | GEO
Project description:This model is from the article:
A regulatory role for repeated decoy transcription factor binding sites in target gene expression.
Lee TH, Maheshri N. Mol Syst Biol.
2012 Mar 27;8:576. 22453733
,
Abstract:
Tandem repeats of DNA that contain transcription factor (TF) binding sites could serve as decoys, competitively binding to TFs and affecting target gene expression. Using a synthetic system in budding yeast, we demonstrate that repeated decoy sites inhibit gene expression by sequestering a transcriptional activator and converting the graded dose-response of target promoters to a sharper, sigmoidal-like response. On the basis of both modeling and chromatin immunoprecipitation measurements, we attribute the altered response to TF binding decoy sites more tightly than promoter binding sites. Tight TF binding to arrays of contiguous repeated decoy sites only occurs when the arrays are mostly unoccupied. Finally, we show that the altered sigmoidal-like response can convert the graded response of a transcriptional positive-feedback loop to a bimodal response. Together, these results show how changing numbers of repeated TF binding sites lead to qualitative changes in behavior and raise new questions about the stability of TF/promoter binding.
Note:
This model corresponds to the basic model for gene expression in the presence of decoys, described in the paper.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1202270000 | BioModels
Project description:Binding of transcription factors (TFs) to regulatory sequences is a pivotal step in the control of gene expression. Despite many advances in the characterization of sequence motifs recognized by TFs, our ability to quantitatively predict TF binding to different regulatory sequences is still limited. Here, we present a novel experimental assay termed BunDLE-seq that provides quantitative measurements of TF binding to thousands of fully designed sequences of 200 bp in length within a single experiment. Applying this binding assay to two yeast TFs we demonstrate that sequences outside the core TF binding site profoundly affect TF binding. We show that TF-specific models based on the sequence or DNA shape of the regions flanking the core binding site are highly predictive of the measured differential TF binding. We further characterize the dependence of TF binding, accounting for measurements of single and co-occurring binding events, on the number and location of binding sites and on the TF concentration. Finally, by coupling our in vitro TF binding measurements, and another application of our method probing nucleosome formation, to in vivo expression measurements carried out with the same template sequences now serving and promoters, we offer insights into mechanisms that may determine the different expression outcomes observed. Our assay thus paves the way to a more comprehensive understanding of TF binding to regulatory sequences, and allows the characterization of TF binding determinants within and outside of core binding sites.
2015-03-04 | GSE66143 | GEO
Project description:TF binding clusters in promoter correlate well with gene expression. We used ChIP-seq to map binding sites of the majority of highly expressed TFs in the cell. The size of clusters of TFs in the promoters of genes were found to correlate well with gene expression. CRC cell lines were grown on plastic This submission reprsents transcriptome component of study.
2013-08-16 | E-GEOD-48448 | biostudies-arrayexpress
Project description:Eukaryotic cells express transcription factor (TF) paralogues that bind to nearly identical DNA sequences in vitro but bind at different genomic loci and perform different functions in vivo. Predicting how 2 paralogous TFs bind in vivo using DNA sequence alone is an important open problem. Here, we analyzed 2 yeast bHLH TFs, Cbf1p and Tye7p, which have highly similar binding preferences in vitro, yet bind at almost completely non-overlapping target loci in vivo. We dissected the determinants of specificity for these 2 proteins by making a number of chimeric TFs in which we swapped different domains of Cbf1p and Tye7p and determined the effects on in vivo binding and cellular function. From these experiments, we learned that the Cbf1p dimer achieves its specificity by binding cooperatively with other Cbf1p dimers bound nearby. In contrast, we found that Tye7p achieves its specificity by binding cooperatively with three other DNA-binding proteins, Gcr1p, Gcr2p, and Rap1p. Remarkably, most promoters (63%) that are bound by Tye7p do not contain a consensus Tye7p binding site. Using this information, we were able to build simple models to accurately discriminate bound and unbound genomic loci for both Cbf1p and Tye7p. We then successfully reprogrammed the human bHLH NPAS2 to bind Cbf1p in vivo targets and a Tye7p target intergenic region to be bound by Cbf1p. These results demonstrate that the genome-wide binding targets of paralogous TFs can be discriminated using sequence information, and provide lessons about TF specificity that can be applied across the phylogenetic tree.
2019-07-18 | GSE134427 | GEO
Project description:This model is from the article:
A regulatory role for repeated decoy transcription factor binding sites in target gene expression.
Lee TH, Maheshri N. Mol Syst Biol.
2012 Mar 27;8:576. 22453733
,
Abstract:
Tandem repeats of DNA that contain transcription factor (TF) binding sites could serve as decoys, competitively binding to TFs and affecting target gene expression. Using a synthetic system in budding yeast, we demonstrate that repeated decoy sites inhibit gene expression by sequestering a transcriptional activator and converting the graded dose-response of target promoters to a sharper, sigmoidal-like response. On the basis of both modeling and chromatin immunoprecipitation measurements, we attribute the altered response to TF binding decoy sites more tightly than promoter binding sites. Tight TF binding to arrays of contiguous repeated decoy sites only occurs when the arrays are mostly unoccupied. Finally, we show that the altered sigmoidal-like response can convert the graded response of a transcriptional positive-feedback loop to a bimodal response. Together, these results show how changing numbers of repeated TF binding sites lead to qualitative changes in behavior and raise new questions about the stability of TF/promoter binding.
Note:
This model corresponds to the comprehensive model encompassing the basic model (MODEL1202270000) as well as the tTA/dox (tet-transcriptional activator/doxycycline) interaction, described in the paper.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1202270001 | BioModels
Project description:DNA sequence-specific transcription factors (TFs) modulate transcription and chromatin architecture, acting from regulatory sites in enhancers and promoters of eukaryotic genes. How TFs locate their DNA targets and how multiple TFs cooperate to regulate individual genes is still unclear. Most yeast TFs are thought to regulate transcription via binding to upstream activating sequences, situated within a few hundred base pairs upstream of the regulated gene. While this model has been validated for individual TFs and specific genes, it has not been tested in a systematic way with the large set of yeast TFs. Here, we have integrated information on the binding and expression targets for the near-complete set of yeast TFs. While we found many instances of functional TF binding sites in upstream regulatory regions, we found many more instances that do not fit this model. In many cases, we find that rapid TF depletion affects gene expression where there is no detectable binding of that TF to the upstream region of the affected gene. We also found that, for most TFs, only a small fraction of bound TFs regulates the nearby gene, showing that TF binding does not automatically correspond to regulation of the linked gene. Overall, our comprehensive mapping of TF binding and regulatory targets have both confirmed known TF relationships and revealed surprising properties of TF function.
2023-08-01 | GSE236944 | GEO
Project description:DNA sequence-specific transcription factors (TFs) modulate transcription and chromatin architecture, acting from regulatory sites in enhancers and promoters of eukaryotic genes. How TFs locate their DNA targets and how multiple TFs cooperate to regulate individual genes is still unclear. Most yeast TFs are thought to regulate transcription via binding to upstream activating sequences, situated within a few hundred base pairs upstream of the regulated gene. While this model has been validated for individual TFs and specific genes, it has not been tested in a systematic way with the large set of yeast TFs. Here, we have integrated information on the binding and expression targets for the near-complete set of yeast TFs. While we found many instances of functional TF binding sites in upstream regulatory regions, we found many more instances that do not fit this model. In many cases, we find that rapid TF depletion affects gene expression where there is no detectable binding of that TF to the upstream region of the affected gene. We also found that, for most TFs, only a small fraction of bound TFs regulates the nearby gene, showing that TF binding does not automatically correspond to regulation of the linked gene. Overall, our comprehensive mapping of TF binding and regulatory targets have both confirmed known TF relationships and revealed surprising properties of TF function.
2023-08-01 | GSE236947 | GEO