Large-scale mapping of gene regulatory logic reveals 5 context-dependent repression by transcriptional 65 activators
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ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE92306 | GEO | 2016/12/14
REPOSITORIES: GEO
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Project description:Cooperative DNA-binding by transcription factor (TF) proteins is critical for gene expression regulation in eukaryotes. In the human genome, many regulatory regions contain TF binding sites in close proximity to each other, which can facilitate cooperative interactions. However, binding site proximity does not necessarily imply cooperative binding, as two TFs could also bind independently to each of their neighboring target sites. Currently, the rules that drive cooperative versus independent binding of TFs to neighboring sites are not well understood. In addition, it is oftentimes difficult to infer direct cooperativity between TFs from existing DNA-binding data. Here, we show that in vitro binding assays using DNA libraries of a few thousand genomic sequences with putative cooperative TF binding events can be used to develop accurate models of cooperativity and to gain insights into cooperative binding mechanisms. Using human factors ETS1 and RUNX1 as our case study, we show that the distance and orientation between ETS1 sites are critical determinants of cooperative ETS1-ETS1 binding, while cooperative ETS1- RUNX1 interactions show more flexibility in distance and orientation and can be accurately predicted based on binding affinity and the sequence/shape features of the binding sites. The approach described here, combining custom experimental design with machine learning modeling, can be easily applied to study the cooperative DNA-binding patterns of any TFs.
2023-07-30 | GSE171734 | GEO
Project description:Cooperative DNA-binding by transcription factor (TF) proteins is critical for gene expression regulation in eukaryotes. In the human genome, many regulatory regions contain TF binding sites in close proximity to each other, which can facilitate cooperative interactions. However, binding site proximity does not necessarily imply cooperative binding, as two TFs could also bind independently to each of their neighboring target sites. Currently, the rules that drive cooperative versus independent binding of TFs to neighboring sites are not well understood. In addition, it is oftentimes difficult to infer direct cooperativity between TFs from existing DNA-binding data. Here, we show that in vitro binding assays using DNA libraries of a few thousand genomic sequences with putative cooperative TF binding events can be used to develop accurate models of cooperativity and to gain insights into cooperative binding mechanisms. Using human factors ETS1 and RUNX1 as our case study, we show that the distance and orientation between ETS1 sites are critical determinants of cooperative ETS1-ETS1 binding, while cooperative ETS1- RUNX1 interactions show more flexibility in distance and orientation and can be accurately predicted based on binding affinity and the sequence/shape features of the binding sites. The approach described here, combining custom experimental design with machine learning modeling, can be easily applied to study the cooperative DNA-binding patterns of any TFs.
2023-07-30 | GSE171732 | GEO
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: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: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:Previous studies have analyzed patterns of transcription, transcription factor (TF) binding or mapped nucleosome occupancy across the genome. These suggest that the three aspects are genetically connected but the cause and effect relationships are still unknown. For example, physiologic TF binding studies involve many TFs, consequently, it is difficult to assign nucleosome reorganization to the binding site occupancy of any particular TF. Therefore, several aspects remain unclear: does TF binding influence nucleosome (re)organizations locally (in close vicinity of their binding sites) or impact the chromatin landscape at a more global level; are all or only a fraction of TF binding a result of reorganization in nucleosome occupancy; finally, do all TF binding and associated nucleosome occupancy changes result in altered gene expression? With these in mind, we sought to study a single TF that induces physiological changes, and following characterization of the two states (before and after induction of the TF) we determined: (a) genomic binding sites of the TF, (b) promoter nucleosome occupancy and (c) transcriptome profiles, independently in both conditions. Results demonstrate that TF binding influences expression of the target gene only when it is coupled to nucleosome repositioning at or close to its binding site, and not when transcription factor binding occurs without local associated nucleosome reorganization. The nature of interaction between TF binding and nucleosomes and what extent it influences transcription
2014-08-04 | E-GEOD-40363 | biostudies-arrayexpress
Project description:Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a novel sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target for two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NN) and biophysical models trained on these data, we establish that dinucleotide specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more non-additivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest-affinity sites.
2018-03-17 | GSE111936 | GEO
Project description:Despite decades of research, predicting where a transcription factor (TF) binds using its sequences alone continues to be an outstanding problem. Here, our thermodynamic model of Gal4p-DNA binding revealed a new mechanism of binding site selection in which Gal4p can bind to promoters that lacks it consensus site. Further investigation revealed that these sequences that Gal4p unexpectedly binds to have a high density of its half site, CGG. Analyses showed the ability of CGG half sites to predict zinc cluster TF in vivo binding and exposed a clear relationship between CGG half sites and zinc cluster binding in multiple binding datasets. To dissect the molecular logic of this half site mode of binding we designed a Sort-seq library containing 6,798 yeast promoter sequences and measured their expression. We learned that there is a linear relationship between CGG half site density and zinc cluster driven expression in vivo. Additionally, we found that promoters encoding 10 half sites have the same transcriptional output as a single consensus site and found no clear effects of half site orientation and spacing on strength of activation. Our experiments demonstrate that this novel mode of half site binding is widespread across the yeast genome and expands our knowledge about TF binding specificity that can be applied to higher eukaryotes.
2022-11-04 | GSE216839 | GEO
Project description:Despite decades of research, predicting where a transcription factor (TF) binds using its sequences alone continues to be an outstanding problem. Here, our thermodynamic model of Gal4p-DNA binding revealed a new mechanism of binding site selection in which Gal4p can bind to promoters that lacks it consensus site. Further investigation revealed that these sequences that Gal4p unexpectedly binds to have a high density of its half site, CGG. Analyses showed the ability of CGG half sites to predict zinc cluster TF in vivo binding and exposed a clear relationship between CGG half sites and zinc cluster binding in multiple binding datasets. To dissect the molecular logic of this half site mode of binding we designed a Sort-seq library containing 6,798 yeast promoter sequences and measured their expression. We learned that there is a linear relationship between CGG half site density and zinc cluster driven expression in vivo. Additionally, we found that promoters encoding 10 half sites have the same transcriptional output as a single consensus site and found no clear effects of half site orientation and spacing on strength of activation. Our experiments demonstrate that this novel mode of half site binding is widespread across the yeast genome and expands our knowledge about TF binding specificity that can be applied to higher eukaryotes.
2022-11-04 | GSE216838 | GEO