DNA Binding Signatures of the Myocyte Enhancer Factor-2B
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE116401 | GEO | 2020/07/21
REPOSITORIES: GEO
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Project description:Binding of transcription factors to DNA is mediated by the recognition of the chemical signatures of the DNA bases and the three-dimensional shape of the DNA molecule. The direct contribution of DNA shape to DNA-binding specificity has been difficult to assess, as DNA shape is a consequence of its sequence. Here, we teased apart these two modes of recognition in the context of Hox-DNA binding. We made a series of mutations in Hox residues that, in a co-crystal structure, only recognize DNA shape, and tested the effect on DNA binding preferences using SELEX-seq. Analysis of shape features of selected sequences revealed that these residues are both necessary and sufficient for selection of sequences with distinct shape features. We used statistical machine learning to show that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence. We conclude that shape readout is a direct and critical component of binding site selection by Hox proteins. Three rounds of SELEX were performed on a series of Hox mutants as described in Slattery et al, Cell, 2011 (PMID 22153072) and Riley et al, Methods in molecular Biology, 2014 (PMID 25151169). Briefly, His-tagged Scr and Antp mutant proteins were incubated with a randomized 16mer oligonucleotide library, and bound DNA was amplified and sequenced as described (PMID 22153072, PMID 25151169).
2015-01-21 | E-GEOD-65073 | biostudies-arrayexpress
Project description:Binding of transcription factors to DNA is mediated by the recognition of the chemical signatures of the DNA bases and the three-dimensional shape of the DNA molecule. The direct contribution of DNA shape to DNA-binding specificity has been difficult to assess, as DNA shape is a consequence of its sequence. Here, we teased apart these two modes of recognition in the context of Hox-DNA binding. We made a series of mutations in Hox residues that, in a co-crystal structure, only recognize DNA shape, and tested the effect on DNA binding preferences using SELEX-seq. Analysis of shape features of selected sequences revealed that these residues are both necessary and sufficient for selection of sequences with distinct shape features. We used statistical machine learning to show that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence. We conclude that shape readout is a direct and critical component of binding site selection by Hox proteins.
2015-01-21 | GSE65073 | GEO
Project description:Accurate predictions of the DNA binding specificities of transcription factors (TFs) are necessary for understanding gene regulatory mechanisms. Traditionally, predictive models are built based on nucleotide sequence features. Here, we employed three- dimensional DNA shape information obtained on a high-throughput basis to integrate intuitive DNA structural features into the modeling of TF binding specificities using support vector regression. We performed quantitative predictions of DNA binding specificities, using the DREAM5 dataset for 65 mouse TFs and genomic-context protein binding microarray data for three human basic helix-loop-helix TFs. DNA shape-augmented models compared favorably with sequence-based models for these predictions. Although both k-mer and DNA shape features encoded the interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space compared to k-mer use. Finally, analyzing the weights of DNA shape-augmented models uncovered TF family- specific structural readout mechanisms that were not obvious from the nucleotide sequence.
2014-11-04 | GSE59845 | GEO
Project description:Accurate predictions of the DNA binding specificities of transcription factors (TFs) are necessary for understanding gene regulatory mechanisms. Traditionally, predictive models are built based on nucleotide sequence features. Here, we employed three- dimensional DNA shape information obtained on a high-throughput basis to integrate intuitive DNA structural features into the modeling of TF binding specificities using support vector regression. We performed quantitative predictions of DNA binding specificities, using the DREAM5 dataset for 65 mouse TFs and genomic-context protein binding microarray data for three human basic helix-loop-helix TFs. DNA shape-augmented models compared favorably with sequence-based models for these predictions. Although both k-mer and DNA shape features encoded the interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space compared to k-mer use. Finally, analyzing the weights of DNA shape-augmented models uncovered TF family- specific structural readout mechanisms that were not obvious from the nucleotide sequence. Three genomic-context protein binding microarray (gcPBM) experiments of human transcription factors were performed. Briefly, the gcPBMs involved binding his-tagged transcription factors c-Myc, Max, and Mad1(Mxd1) to double-stranded 180K Agilent microarrays in order to determine their binding specificity for putative DNA binding sites in native genomic context. Briefly, we represent three categories of 36-bp sequences: 1) bound probes, 2) unbound probes (or negative controls), and 3) test probes. Bound probes corresponded to genomic regions bound in vivo by c-Myc, Max, or Mad2 (ChIP-seq P < 10^(-10) in HeLaS3 or K562 celld (ENCODE)) that contain at least two consecutive 8-mers with universal PBM E-score > 0.4 (Munteanu and Gordan, LNCS 2013). All putative binding sites occur at the same position within the probes on the array. M-bM-^@M-^\UnboundM-bM-^@M-^] probes corresponded to genomic regions with ChIP-seq P < 10^(-10) and a maximum 8-mer E-score < 0.2. We also designed test probes that contain, within constant flanking regions, all nnCACGTGnn 10-mers and 18 nnnCACGTGnnn 12-mers (where n = A, C, G, or T). Each DNA sequence represented on the array is present in 6 replicate spots. We report the gcPBM signal intensity for each spot. The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).
2014-11-04 | E-GEOD-59845 | biostudies-arrayexpress
Project description:Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell.
2020-08-29 | GSE157067 | GEO
Project description:Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell.
2020-08-29 | GSE157066 | GEO
Project description:Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell.
2020-08-29 | GSE157065 | GEO
Project description:Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell.
2020-08-29 | GSE157064 | GEO
Project description:Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell.
2020-08-18 | GSE156373 | GEO
Project description:Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell.
2020-08-16 | GSE156304 | GEO