Iris Dror

Cofactor Binding Evokes Latent Differences in DNA Binding Specificity between Hox Proteins

Members of transcription factor families typically have similar DNA binding specificities yet execute unique functions in vivo. Transcription factors often bind DNA as multiprotein complexes, raising the possibility that complex formation might modify their DNA binding specificities. To test this hypothesis, we developed an experimental and computational platform, SELEX-seq, that can be used to determine the relative affinities to any DNA sequence for any transcription factor complex. Applying this method to all eight Drosophila Hox proteins, we show that they obtain novel recognition properties when they bind DNA with the dimeric cofactor Extradenticle-Homothorax (Exd). Exd-Hox specificities group into three main classes that obey Hox gene collinearity rules and DNA structure predictions suggest that anterior and posterior Hox proteins prefer DNA sequences with distinct minor groove topographies. Together, these data suggest that emergent DNA recognition properties revealed by interactions with cofactors contribute to transcription factor specificities in vivo.

Genomic regions flanking E-box binding sites influence DNA binding specificity of bHLH transcription factors through DNA shape

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 studies, 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 three-dimensional structure of DNA binding sites. Thus, the local shape of target sites might play a widespread role in achieving regulatory specificity within TF families.

DNAshape: a method for the high-throughput prediction of DNA structural features on a genomic scale

We present a method and web server for predicting DNA structural features in a high-throughput (HT) manner for massive sequence data. This approach provides the framework for the integration of DNA sequence and shape analyses in genome-wide studies. The HT methodology uses a sliding-window approach to mine DNA structural information obtained from Monte Carlo simulations. It requires only nucleotide sequence as input and instantly predicts multiple structural features of DNA (minor groove width, roll, propeller twist and helix twist). The results of rigorous validations of the HT predictions based on DNA structures solved by X-ray crystallography and NMR spectroscopy, hydroxyl radical cleavage data, statistical analysis and cross-validation, and molecular dynamics simulations provide strong confidence in this approach. The DNAshape web server is freely available at http://rohslab.cmb.usc.edu/DNAshape/.

TFBSshape: a motif database for DNA shape features of transcription factor binding sites

Transcription factor binding sites (TFBSs) are most commonly characterized by the nucleotide preferences at each position of the DNA target. Whereas these sequence motifs are quite accurate descriptions of DNA binding specificities of transcription factors (TFs), proteins recognize DNA as a three-dimensional object. DNA structural features refine the description of TF binding specificities and provide mechanistic insights into protein–DNA recognition. Existing motif databases contain extensive nucleotide sequences identified in binding experiments based on their selection by a TF. To utilize DNA shape information when analysing the DNA binding specificities of TFs, we developed a new tool, the TFBSshape database (available at http://rohslab.cmb.usc.edu/TFBSshape/), for calculating DNA structural features from nucleotide sequences provided by motif databases. The TFBSshape database can be used to generate heat maps and quantitative data for DNA structural features (i.e., minor groove width, roll, propeller twist and helix twist) for 739 TF datasets from 23 different species derived from the motif databases JASPAR and UniPROBE. As demonstrated for the basic helix-loop-helix and homeodomain TF families, our TFBSshape database can be used to compare, qualitatively and quantitatively, the DNA binding specificities of closely related TFs and, thus, uncover differential DNA binding specificities that are not apparent from nucleotide sequence alone.

Deconvolving the Recognition of DNA Shape from Sequence

Protein-DNA binding is mediated by the recognition of the chemical signatures of the DNA bases and the 3D shape of the DNA molecule. Because DNA shape is a consequence of sequence, it is difficult to dissociate these modes of recognition. Here, we tease them apart in the context of Hox-DNA binding by mutating residues that, in a co-crystal structure, only recognize DNA shape. Complexes made with these mutants lose the preference to bind sequences with specific DNA shape features. Introducing shape-recognizing residues from one Hox protein to another swapped binding specificities in vitro and gene regulation in vivo. Statistical machine learning revealed that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence, and feature selection identified shape features important for recognition. Thus, shape readout is a direct and independent component of binding site selection by Hox proteins.

SFmap: a web server for motif analysis and prediction of splicing factor binding sites

Alternative splicing (AS) is a post-transcriptional process considered to be responsible for the huge diversity of proteins in higher eukaryotes. AS events are regulated by different splicing factors (SFs) that bind to sequence elements on the RNA. SFmap is a web server for predicting putative SF binding sites in genomic data (http://sfmap.technion.ac.il). SFmap implements the COS(WR) algorithm, which computes similarity scores for a given regulatory motif based on information derived from its sequence environment and its evolutionary conservation. Input for SFmap is a human genomic sequence or a list of sequences in FASTA format that can either be uploaded from a file or pasted into a window. SFmap searches within a given sequence for significant hits of binding motifs that are either stored in our database or defined by the user. SFmap results are provided both as a text file and as a graphical web interface.

A widespread role of the motif environment in transcription factor binding across diverse protein families

Transcriptional regulation requires the binding of transcription factors (TFs) to short sequence-specific DNA motifs, usually located at the gene regulatory regions. Interestingly, based on a vast amount of data accumulated from genomic assays, it has been shown that only a small fraction of all potential binding sites containing the consensus motif of a given TF actually bind the protein. Recent in vitro binding assays, which exclude the effects of the cellular environment, also demonstrate selective TF binding. An intriguing conjecture is that the surroundings of cognate binding sites have unique characteristics that distinguish them from other sequences containing a similar motif that are not bound by the TF. To test this hypothesis, we conducted a comprehensive analysis of the sequence and DNA shape features surrounding the core-binding sites of 239 and 56 TFs extracted from in vitro HT-SELEX binding assays and in vivo ChIP-seq data, respectively. Comparing the nucleotide content of the regions around the TF-bound sites to the counterpart unbound regions containing the same consensus motifs revealed significant differences that extend far beyond the core-binding site. Specifically, the environment of the bound motifs demonstrated unique sequence compositions, DNA shape features, and overall high similarity to the core-binding motif. Notably, the regions around the binding sites of TFs that belong to the same TF families exhibited similar features, with high agreement between the in vitro and in vivo data sets. We propose that these unique features assist in guiding TFs to their cognate binding sites.

Covariation between homeodomain transcription factors and the shape of their DNA binding sites

Protein–DNA recognition is a critical component of gene regulatory processes but the underlying molecular mechanisms are not yet completely understood. Whereas the DNA binding preferences of transcription factors (TFs) are commonly described using nucleotide sequences, the 3D DNA structure is recognized by proteins and is crucial for achieving binding specificity. However, the ability to analyze DNA shape in a high-throughput manner made it only recently feasible to integrate structural information into studies of protein–DNA binding. Here we focused on the homeodomain family of TFs and analyzed the DNA shape of thousands of their DNA binding sites, investigating the covariation between the protein sequence and the sequence and shape of their DNA targets. We found distinct homeodomain regions that were more correlated with either the nucleotide sequence or the DNA shape of their preferred binding sites, demonstrating different readout mechanisms through which homeodomains attain DNA binding specificity. We identified specific homeodomain residues that likely play key roles in DNA recognition via shape readout. Finally, we showed that adding DNA shape information when characterizing binding sites improved the prediction accuracy of homeodomain binding specificities. Taken together, our findings indicate that DNA shape information can generally provide new mechanistic insights into TF binding.

Sequences flanking the core-binding site modulate glucocorticoid receptor structure and activity.

The glucocorticoid receptor (GR) binds as a homodimer to genomic response elements, which have particular sequence and shape characteristics. Here we show that the nucleotides directly flanking the core-binding site, differ depending on the strength of GR-dependent activation of nearby genes. Our study indicates that these flanking nucleotides change the three-dimensional structure of the DNA-binding site, the DNA-binding domain of GR and the quaternary structure of the dimeric complex. Functional studies in a defined genomic context show that sequence-induced changes in GR activity cannot be explained by differences in GR occupancy. Rather, mutating the dimerization interface mitigates DNA-induced changes in both activity and structure, arguing for a role of DNA-induced structural changes in modulating GR activity. Together, our study shows that DNA sequence identity of genomic binding sites modulates GR activity downstream of binding, which may play a role in achieving regulatory specificity towards individual target genes.

How motif environment influences transcription factor search dynamics: Finding a needle in a haystack.

Transcription factors (TFs) have to find their binding sites, which are distributed throughout the genome. Facilitated diffusion is currently the most widely accepted model for this search process. Based on this model the TF alternates between one‐dimensional sliding along the DNA, and three‐dimensional bulk diffusion. In this view, the non‐specific associations between the proteins and the DNA play a major role in the search dynamics. However, little is known about how the DNA properties around the motif contribute to the search. Accumulating evidence showing that TF binding sites are embedded within a unique environment, specific to each TF, leads to the hypothesis that the search process is facilitated by favorable DNA features that help to improve the search efficiency. Here, we review the field and present the hypothesis that TF‐DNA recognition is dictated not only by the motif, but is also influenced by the environment in which the motif resides.