GEO DataSets

(Submitter supplied) 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. more...

Organism:

Homo sapiens

Type:

Genome binding/occupancy profiling by array

Platform:

GPL17173

3 Samples

Download data: TXT

(Submitter supplied) Until now, it has been reasonably assumed that specific base-pair recognition is the only mechanism controlling the specificity of transcription factor (TF)−DNA binding. Contrary to this assumption, here we show that nonspecific DNA sequences possessing certain repeat symmetries, when present outside of specific TF binding sites (TFBSs), statistically control TF−DNA binding preferences. We used high-throughput protein−DNA binding assays to measure the binding levels and free energies of binding for several human TFs to tens of thousands of short DNA sequences with varying re- peat symmetries. more...

Organism:

Homo sapiens; synthetic construct

Type:

Other

Platform:

GPL19252

4 Samples

Download data: GPR, TXT

(Submitter supplied) The E2F family of transcription factors is typically described as binding the family consensus sequence TTTSSCGC, were S is G or C. Analysis of ChIP-seq experiments, however, reveals that this consensus sequence is found in only 10% of ChIP-seq peaks, suggesting that the mechanism for E2F sequence recognition cannot be explained using previous assumptions. In order to better understand E2F sequence specificity, we performed high-throughput Universal Protein Binding Microarray experiments to obtain the relative binding affinity for every possible 8-mer, as well a large number of bound and unbound probes intheir native genomic sequence context. more...

Organism:

Homo sapiens; synthetic construct

Type:

Other

Platform:

GPL19244

3 Samples

Download data: GPR, TXT

(Submitter supplied) The SELEX-seq platform was used to generate DNA-binding affinity predictions for the human Max transcription factor. This experiment was performed as part of a cross-validation study comparing the accuracy of DNA shape-augmented TF binding specificity models across two different platforms (SELEX-seq and gcPBM)

Organism:

Homo sapiens

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL16791

1 Sample

Download data: TXT

(Submitter supplied) Motivation: The DNA binding specificity of a transcription factor (TF) is typically represented using a position weight matrix (PWM) model, which implicitly assumes that individual bases in a TF binding site contribute independently to the binding affinity, an assumption that does not always hold. For this reason, more complex models of binding specificity have been developed. However, these models have their own caveats: they typically have a large number of parameters, which makes them hard to learn and interpret. more...

Organism:

Homo sapiens

Type:

Genome binding/occupancy profiling by array

Platform:

GPL17173

4 Samples

Download data: TXT

(Submitter supplied) Detecting in vivo transcription factor (TF) binding is important for understanding gene regulatory circuitries. ChIP-seq is a powerful technique to empirically define TF binding in vivo. However, the multitude of distinct TFs makes genome-wide profiling for them all labor-intensive and costly. Algorithms for in silico prediction of TF binding have been developed, based mostly on histone modification or DNase I hypersensitivity data in conjunction with DNA motif and other genomic features. more...

Organism:

Mus musculus

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL13112

1 Sample

Download data: BED

(Submitter supplied) Eukaryotic transcription factors (TFs) form complexes with various partner proteins to recognize their genomic target sites. Yet, how the DNA sequence determines which TF complex forms at any given site is poorly understood. Here, we demonstrate that high-throughput in vitro DNA binding assays coupled with unbiased computational analysis provide unprecedented insight into how different DNA sequences select distinct compositions and configurations of homeodomain TF complexes. more...

Organism:

Drosophila melanogaster

Type:

Genome binding/occupancy profiling by high throughput sequencing; Other; Expression profiling by high throughput sequencing

Platforms:

GPL13304 GPL19132

33 Samples

Download data: BED, BW, HIC

(Submitter supplied) 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. more...

Organism:

Saccharomyces cerevisiae; synthetic construct

Type:

Other

Platform:

GPL6796

27 Samples

Download data

(Submitter supplied) 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. more...

Organism:

synthetic construct

Type:

Other

Platforms:

GPL17769 GPL19424

14 Samples

Download data: TXT

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Arabidopsis thaliana; synthetic construct; Mus musculus; Homo sapiens

Type:

Other

4 related Platforms

12 Samples

Download data: TXT

(Submitter supplied) 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. more...

Organism:

synthetic construct

Type:

Other

Platform:

GPL15228

4 Samples

Download data: XLSX

(Submitter supplied) This protein binding microarray (PBM) involved binding GST-tagged proteins to custom-designed, double-stranded 44K Agilent microarrays in order to determine their sequence preferences. The method is described in Berger et al., Nature Biotechnology 2006. A key feature is that the microarrays are composed of de Bruijn sequences that contain each 10-base sequence once and only once, providing an evenly balanced sequence distribution. more...

Organism:

synthetic construct

4 Series

383 Samples

Download data

(Submitter supplied) 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. more...

Organism:

Drosophila melanogaster

Type:

Other; Genome binding/occupancy profiling by high throughput sequencing

Platforms:

GPL17275 GPL9061

32 Samples

Download data: TXT

(Submitter supplied) We report the development of a deep learning-based tool, DeepTFactor, that predicts whether a protein of question is a transcription factor. DeepTFactor uses a convolutional neural network to extract features of protein sequences. We characterized the genome-wide binding sites of three TFs (i.e., YqhC, YiaU, and YahB), which are predicted by DeepTFactor

Organism:

Escherichia coli

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL18133

6 Samples

Download data: GFF

(Submitter supplied) 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. more...

Organism:

synthetic construct

Type:

Other

Platform:

GPL11260

172 Samples

Download data: TXT

(Submitter supplied) The forkhead transcription factor (TF) FoxN3 recognizes both the canonical forkhead DNA motif (RYAAAYA), as well as a novel alternate motif (GACGC). These two motifs are more distinct than the typically observed primary and secondary motifs of other TFs, as the two motifs cannot be aligned and are not clearly related to each other. Amino acids at the canonical base-contacting positions in the forkhead DNA binding domain are largely conserved throughout the forkhead family, so the ability of FoxN3 and other bispecific forkhead factors to recognize the alternate site cannot be explained by amino acid substitutions at these positions. more...

Organism:

Homo sapiens

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL18573

6 Samples

Download data: NARROWPEAK

(Submitter supplied) This dataset uses DNase-seq to profile the genome-wide DNase I hypersensitivity of mES and mES-derived cells along an early pancreatic lineage and provides the locations of putative Transcription Factor (TF) binding sites using the PIQ algorithm. DNase-seq takes advantage of the preferential cutting of DNase I in open chromatin and steric blockage of of DNase I by tightly bound TFs that protect associated genomic DNA sequences. more...

Organism:

Mus musculus

Type:

Methylation profiling by high throughput sequencing

Platform:

GPL13112

6 Samples

Download data: TXT

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Saccharomyces cerevisiae

Type:

Protein profiling by protein array

Platforms:

GPL16704 GPL16703

5 Samples

Download data: TXT

(Submitter supplied) 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. more...

Organism:

Saccharomyces cerevisiae

Type:

Protein profiling by protein array

Platform:

GPL16704

2 Samples

Download data: TXT

(Submitter supplied) 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. more...

Organism:

Saccharomyces cerevisiae

Type:

Protein profiling by protein array

Platform:

GPL16703

3 Samples

Download data: TXT