Genomic regions flanking E-box sites influence DNA binding specificity of bHLH transcription factors through DNA shape (validation)
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ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE44437 | GEO | 2013/03/29
SECONDARY ACCESSION(S): PRJNA190630
REPOSITORIES: GEO
Similar Datasets
Project description:DNA sequence is a major determinant of the binding specificity of transcription factors (TFs) for their genomic targets. However, eukaryotic cells often express, at the same time, TFs with highly similar DNA binding motifs but distinct in vivo targets. Currently, it is not well understood how TFs with seemingly identical DNA motifs achieve unique specificities in vivo. Here, we used custom protein binding microarrays to analyze TF specificity for putative binding sites in their genomic sequence context. Using yeast TFs Cbf1 and Tye7 as our case study, we found that binding sites of these bHLH TFs (i.e., E-boxes) are bound differently in vitro and in vivo, depending on their genomic context. Computational analyses suggest that nucleotides outside E-box binding sites contribute to specificity by influencing the 3D structure of DNA binding sites. Thus, local shape of target sites might play a widespread role in achieving regulatory specificity within TF families. Two protein binding microarray (PBM) experiments of Saccharomyces cerevisiae transcription factors were performed. Briefly, the PBMs involved binding GST-tagged yeast transcription factors Cbf1 and Tye7 to double-stranded 44K Agilent microarrays in order to determine the accuracy of our regression models for TF-DNA binding specificity. Briefly, this array contains 30-bp genomic sequences from our initial custom array (Gordan et al 2013, submitted), with 0 through 4 mutations designed at various positions in the genomic sequences. Each sequence in represented in 6 replicate spots. We report the PBM signal intensity for each spot. The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).
2013-03-29 | E-GEOD-44437 | biostudies-arrayexpress
Project description:DNA sequence is a major determinant of the binding specificity of transcription factors (TFs) for their genomic targets. However, eukaryotic cells often express, at the same time, TFs with highly similar DNA binding motifs but distinct in vivo targets. Currently, it is not well understood how TFs with seemingly identical DNA motifs achieve unique specificities in vivo. Here, we used custom protein binding microarrays to analyze TF specificity for putative binding sites in their genomic sequence context. Using yeast TFs Cbf1 and Tye7 as our case study, we found that binding sites of these bHLH TFs (i.e., E-boxes) are bound differently in vitro and in vivo, depending on their genomic context. Computational analyses suggest that nucleotides outside E-box binding sites contribute to specificity by influencing the 3D structure of DNA binding sites. Thus, local shape of target sites might play a widespread role in achieving regulatory specificity within TF families.
2013-03-29 | GSE44436 | GEO
Project description:DNA sequence is a major determinant of the binding specificity of transcription factors (TFs) for their genomic targets. However, eukaryotic cells often express, at the same time, TFs with highly similar DNA binding motifs but distinct in vivo targets. Currently, it is not well understood how TFs with seemingly identical DNA motifs achieve unique specificities in vivo. Here, we used custom protein binding microarrays to analyze TF specificity for putative binding sites in their genomic sequence context. Using yeast TFs Cbf1 and Tye7 as our case study, we found that binding sites of these bHLH TFs (i.e., E-boxes) are bound differently in vitro and in vivo, depending on their genomic context. Computational analyses suggest that nucleotides outside E-box binding sites contribute to specificity by influencing the 3D structure of DNA binding sites. Thus, local shape of target sites might play a widespread role in achieving regulatory specificity within TF families. Three protein binding microarray (PBM) experiments of Saccharomyces cerevisiae transcription factors were performed. Briefly, the PBMs involved binding GST-tagged yeast transcription factors Cbf1 and Tye7 to double-stranded 44K Agilent microarrays in order to determine their binding specificity for putative DNA binding sites in native genomic context. Briefly, we represent three categories of 30-bp genomic sequences: 1) ChIP-chip bound probes, 2) ChIP-chip unbound probes, and 3) negative control probes. ChIP-chip bound probes corresponded to genomic regions bound in vivo by Cbf1 or Tye7 (ChIP-chip P < 0.005 in rich medium (YPD) (Harbison et al., Nature 2004, PMID 15343339)) contained at least two consecutive 8-mers with universal PBM E-score > 0.35 (Zhu et al., Genome Research 2009, PMID 19158363). All putative binding sites occurred at the same position within the probes on the array. M-bM-^@M-^\ChIP-chip unboundM-bM-^@M-^] probes corresponded to genomic regions with ChIP-chip P > 0.5 and at least two consecutive 8-mers at a more stringent universal PBM E-score threshold of 0.4. Negative control probes corresponded to S. cerevisiae intergenic regions with a maximum 8-mer E-score < 0.3. We also designed probes that contain, within constant flanking regions, all 10-bp sequences that occur within the M-bM-^@M-^\ChIP-chip boundM-bM-^@M-^] probes and contain the E-box CACGTG, but are flanked by synthetic rather than native genomic sequence. Each DNA sequence represented on the array is present in 4 replicate spots. We report the PBM signal intensity for each spot. The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).
2013-03-29 | E-GEOD-44436 | biostudies-arrayexpress
Project description:Genomic analyses often involve scanning for potential transcription-factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a protein’s binding specificity by representing sequence motifs, including the gaps and dependencies between binding-site residues, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For 9 TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices learned by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases. In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences. Protein binding microarray (PBM) experiments were performed for a set of 86 mouse transcription factors. Briefly, the PBMs involved binding GST-tagged DNA-binding proteins to two double-stranded 44K Agilent microarrays, each containing a different DeBruijn sequence design, in order to determine their sequence preferences. Details of the PBM protocol are described in Berger et al., Nature Biotechnology 2006.
2012-12-13 | E-GEOD-42864 | biostudies-arrayexpress
Project description:Genomic analyses often involve scanning for potential transcription-factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a protein’s binding specificity by representing sequence motifs, including the gaps and dependencies between binding-site residues, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For 9 TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices learned by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases. In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.
2012-12-13 | GSE42864 | GEO
Project description:Development of the human malaria parasite, Plasmodium falciparum is regulated by a limited number of sequence-specific transcription factors (TFs). However, the mechanisms by which these TFs recognize genome-wide binding sites to regulate target genes is still largely unknown. To address TF target specificity, we investigated the binding of two TF subsets that either bind CACACA or GTGCAC and further characterized PfAP2-G and PfAP2-EXP which bind unique DNA motifs (GTAC and TGCATGCA). We interrogated the impact of DNA sequence context and the chromatin landscape on P. falciparum TF binding using high-throughput in vitro and in vivo binding assays, DNA shape predictions, epigenetic post-translational modifications, and chromatin accessibility. We determined that DNA sequence context does not greatly impact binding site selection for CACACA-binding TFs, while chromatin accessibility, epigenetic patterns, co-factor recruitment, and dimerization contribute to differential binding. In contrast, GTGCAC-binding TFs prefer different sequence contexts, DNA shape profiles, and chromatin dynamics. Finally, we find that TFs that preferentially bind divergent DNA motifs may bind overlapping genomic regions in vivo due to low-affinity binding to other sequence motifs. Our results demonstrate that TF binding site selection relies on a combination of DNA sequence and chromatin features, thereby contributing to the complexity of P. falciparum gene regulatory mechanisms.
2023-12-31 | GSE227873 | 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:A long-standing challenge in human regulatory genomics is that transcription factor (TF) DNA-binding motifs are short and degenerate, while the genome is large. Motif scans therefore produce many false-positive binding site predictions. By surveying TFs across 25 families using >1,500 cyclic in vitro selection experiments with fragmented, naked, and unmodified genomic DNA – a method we term GHT-SELEX (Genomic HT-SELEX) – we find that many human TFs possess much higher sequence specificity than anticipated. Moreover, genomic binding regions from GHT-SELEX are often surprisingly similar to those obtained in vivo (i.e. ChIP-seq peaks). We find that comparable specificity can also be obtained from motif scans, but performance is highly dependent on derivation and use of the motifs, including accounting for multiple local matches in the scans. We also observe alternative engagement of multiple DNA-binding domains within the same protein: long C2H2 zinc finger proteins often utilize modular DNA recognition, engaging different subsets of their DNA binding domain (DBD) arrays to recognize multiple types of distinct target sites, frequently evolving via internal duplication and divergence of one or more DBDs. Thus, contrary to conventional wisdom, it is common for TFs to possess sufficient intrinsic specificity to independently delineate cellular targets.
2024-11-11 | GSE278858 | GEO
Project description:We describe an effort (“Codebook”) to determine the sequence specificity of 332 putative and largely uncharacterized human transcription factors (TFs), as well as 61 control TFs. Nearly 5,000 independent experiments, including in vitro and in vivo assays, produced motifs for most of the uncharacterized TFs analyzed (180, or 53%), the vast majority of which are unique to a single TF. The data highlight the extensive contribution of transposable elements to TF evolution, both in cis and trans, and identify tens of thousands of conserved, base-level binding sites in the human genome. The use of multiple platforms provides an unprecedented opportunity to benchmark and analyze TF sequence specificity, function, and evolution, as further explored in accompanying manuscripts. Over 1,421 human TFs are now associated with a DNA binding motif. Extrapolation from the Codebook benchmarking suggests that many of the binding motifs for well-studied TFs may inaccurately describe the TF’s true sequence preferences.
2024-11-11 | GSE275577 | GEO