Mapping and Analysis of Caenorhabditis elegans Transcription Factor Binding Specificities
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ABSTRACT:
ORGANISM(S): synthetic construct
PROVIDER: GSE65719 | GEO | 2015/04/23
SECONDARY ACCESSION(S): PRJNA274785
REPOSITORIES: GEO
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Project description:The nematode Caenorhabditis elegans is a powerful model for studying gene regulation, as it has a compact genome and a wealth of genomic tools. However, identification of regulatory elements has been hampered by the fact that DNA binding motifs are known for only 71 (9%) of the estimated 763 high-confidence sequence-specific transcription factors (TFs). To address this problem, we performed protein binding microarray (PBM) experiments on representatives of canonical TF families in the C. elegans TF repertoire, obtaining motifs for 129 distinct TFs. Moreover, we can infer motifs for 97 additional TFs that have DNA binding domains that are very similar to those already characterized, resulting in a total coverage of binding specificities for almost 40% of the C. elegans TF repertoire. These data highlight the diversification of binding motifs for the nuclear hormone receptor (NHR) and C2H2 zinc finger families, and reveal unexpected diversity of motifs for others, including the T-box and DM families. Enrichment of motifs in the promoters of functionally related genes is consistent with known biology in many cases, and also identifies putative new regulatory roles for poorly characterized TFs. The motifs are available at http:// http://cisbp.ccbr.utoronto.ca. Protein binding microarray (PBM) experiments were performed for a set of 129 diverse C. elegans 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.
2015-04-23 | E-GEOD-65719 | 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. 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: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:The DNA sequence preferences of the vast majority of eukaryotic transcription factors (TFs) are unknown. Using an approach designed to broadly sample both DNA-binding domain types and eukaryotic clades, we have determined DNA-binding motifs for 1,033 TFs from 131 diverse eukaryotes, encompassing 54 domain types. Closely related orthologs and paralogs typically have very similar sequence preferences; this property allows inference of motifs for roughly one third of the 166,851 known or predicted eukaryotic TFs. While the origins of most motifs can be dated to hundreds of millions of years ago, we also characterize more recent TF expansions. Sequences matching the motifs are enriched upstream of TSS in most eukaryotic lineages, and at informative eQTL SNPs in Arabidopsis promoters, demonstrating their utility in mapping transcriptional networks. The motifs are housed at http://cisbp.ccbr.utoronto.ca Protein binding microarray (PBM) experiments were performed for a set of 1048 diverse eukaryotic 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.
2014-08-01 | E-GEOD-53348 | 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. 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:Identifying the DNA-binding specificities of transcription factors (TF) is central to understanding gene networks that regulate growth and development. Such knowledge is lacking in oomycetes, a group of microbes that includes many important plant and animal pathogens. Here we describe the use of protein-binding oligonucleotide microarrays (PBMs) to define the DNA-binding preferences of 14 families of TFs from the oomycete Phytophthora infestans, which causes late blight of potato and tomato. DNA motifs obtained from the PBMs for representatives of each major TF family were validated by electrophoretic mobility shift assays (EMSA) or ChIP-seq. Consistent with the large evolutionary distance of oomycetes from traditional models, only some of the P. infestans DNA-binding preferences resembled those of TFs from human and plants. Some families from P. infestans included clusters with canonical targets and others with novel targets. Paralogs having similar binding preferences often displayed distinct patterns of expression, suggesting functional divergence. Many TFs were predicted to either drive stage-specific expression or serve as general activators based on the representation of their binding sites within developmentally-regulated promoters. One such prediction was confirmed using a reporter gene assay. Our data thus provide a basis for understanding transcriptional regulation in P. infestans by linking TFs with their targets on a genome-wide level.
2024-07-03 | GSE270411 | 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:The human transcription factor (TF) CGGBP1 (“CGG Binding Protein”) is conserved only in amniotes, and is believed to derive from the zf-BED and Hermes transposase DNA-binding domains (DBDs) of a hAT DNA transposon. Here, we examine the DNA binding preferences of a wide variety of metazoan CGGBP1-like TFs with this bipartite domain using PBM experiments. The derived motifs are available at ...
2021-02-09 | GSE157085 | GEO
Project description:Transcription factors (TFs) play a central role in regulating gene expression by interacting with cis regulatory DNA elements associated with their target genes. Recent surveys have examined the DNA binding specificities of most Saccharomyces cerevisiae transcription factors but a comprehensive evaluation of their data has been lacking. Results: We analyzed in vitro and in vivo TF-DNA binding data reported in previous large-scale studies to generate a comprehensive, curated resource of DNA binding specificity data for all characterized S. cerevisiae transcription factors. Our collection comprises DNA binding site motifs and comprehensive in vitro DNA binding specificity data for all possible 8 bp sequences. Included in this database is DNA binding specificity data for 27 TFs independently generated by PBM analysis in this current study. Investigation of the DNA binding specificities within the basic leucine zipper (bZIP) and VHR transcription factor families revealed unexpected plasticity in TF-DNA recognition: intriguingly, the VHR transcription factors, newly characterized by protein binding microarrays in this study, recognize bZIP like DNA motifs, while the bZIP transcription factor Hac1 recognizes a motif highly similar to the canonical E-box motif of basic helix-loop-helix (bHLH) transcription factors. We identified several transcription factors with distinct primary and secondary motifs, which might be associated with different regulatory functions. Finally, integrated analysis of in vivo transcription factor binding data with protein binding microarray data lends further support for indirect DNA binding in vivo by sequence-specific transcription factors.
2011-12-10 | GSE34306 | GEO
Project description:The regulation of transcription is primarily exerted through transcription factors (TFs) binding to genomic DNA. Although molecular mechanisms of TFs have been studied individually for decades, a complete picture of binding profiles of all TFs and their precise targets in the genome are still lacking in the model pathogen Pseudomonas syringae. To this end, we performed a high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX) approach on all 301 annotated TFs in P. syringae. Robust enrichment of specific sequences was deduced to 118 SELEX motifs. We identified 12,464 interactions between 100 TFs and their target genes in the genome, for an individual TF ranging from 6 to 1481 sites. It showed that 90% TF binding was of dimeric site type, in which 85% with the head-to-head palindromic binding preference. To further explore the pathogenic mechanism of TFs in P. syringae, we mapped intricate networks of these TFs and their targets in the virulence-associated pathways, many of which were verified by orthologous methods such as ChIP-seq, EMSA, RT-qPCR and a reporter assay of promoter activity. By checking the enrichment of binding sites in pathways, we identified 25 virulence-associated master regulators of which 14 had never been characterized as TFs before. Overall, the present study provides a valuable resource for TF binding specificities in P. syringae and demonstrates a novel and an integrative analysis for seeking the virulence-associated TFs and its target genes. We expect that the results will significantly benefit future studies on the transcriptional regulation in P. syringae, and facilitate the design of drug targets to protect plants from attacks by relevant pathogens.
2020-08-18 | GSE146697 | GEO