Probing DNA shape and methylation state on a genomic scale with DNase I.

DNA binding proteins find their cognate sequences within genomic DNA through recognition of specific chemical and structural features. Here we demonstrate that high-resolution DNase I cleavage profiles can provide detailed information about the shape and chemical modification status of genomic DNA. Analyzing millions of DNA backbone hydrolysis events on naked genomic DNA, we show that the intrinsic rate of cleavage by DNase I closely tracks the width of the minor groove. Integration of these DNase I cleavage data with bisulfite sequencing data for the same cell type's genome reveals that cleavage directly adjacent to cytosine-phosphate-guanine (CpG) dinucleotides is enhanced at least eightfold by cytosine methylation. This phenomenon we show to be attributable to methylation-induced narrowing of the minor groove. Furthermore, we demonstrate that it enables simultaneous mapping of DNase I hypersensitivity and regional DNA methylation levels using dense in vivo cleavage data. Taken together, our results suggest a general mechanism by which CpG methylation can modulate protein-DNA interaction strength via the remodeling of DNA shape.

TLS/FUS (translocated in liposarcoma/fused in sarcoma) regulates target gene transcription via single-stranded DNA response elements.

TLS/FUS (TLS) is a multifunctional protein implicated in a wide range of cellular processes, including transcription and mRNA processing, as well as in both cancer and neurological disease. However, little is currently known about TLS target genes and how they are recognized. Here, we used ChIP and promoter microarrays to identify genes potentially regulated by TLS. Among these genes, we detected a number that correlate with previously known functions of TLS, and confirmed TLS occupancy at several of them by ChIP. We also detected changes in mRNA levels of these target genes in cells where TLS levels were altered, indicative of both activation and repression. Next, we used data from the microarray and computational methods to determine whether specific sequences were enriched in DNA fragments bound by TLS. This analysis suggested the existence of TLS response elements, and we show that purified TLS indeed binds these sequences with specificity in vitro. Remarkably, however, TLS binds only single-strand versions of the sequences. Taken together, our results indicate that TLS regulates expression of specific target genes, likely via recognition of specific single-stranded DNA sequences located within their promoter regions.

Building accurate sequence-to-affinity models from high-throughput in vitro protein-DNA binding data using FeatureREDUCE.

Transcription factors are crucial regulators of gene expression. Accurate quantitative definition of their intrinsic DNA binding preferences is critical to understanding their biological function. High-throughput in vitro technology has recently been used to deeply probe the DNA binding specificity of hundreds of eukaryotic transcription factors, yet algorithms for analyzing such data have not yet fully matured. Here, we present a general framework (FeatureREDUCE) for building sequence-to-affinity models based on a biophysically interpretable and extensible model of protein-DNA interaction that can account for dependencies between nucleotides within the binding interface or multiple modes of binding. When training on protein binding microarray (PBM) data, we use robust regression and modeling of technology-specific biases to infer specificity models of unprecedented accuracy and precision. We provide quantitative validation of our results by comparing to gold-standard data when available.

SELEX-seq: a method for characterizing the complete repertoire of binding site preferences for transcription factor complexes.

The closely related members of the Hox family of homeodomain transcription factors have similar DNA-binding preferences as monomers, yet carry out distinct 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 a new experimental and computational platform, termed SELEX-seq, to characterize DNA-binding specificities of Hox-based multiprotein complexes. We found that complex formation with the same cofactor reveals latent specificities that are not observed for monomeric Hox factors. The findings from this in vitro platform are consistent with in vivo data, and the "latent specificity" concept serves as a precedent for how the specificities of similar transcription factors might be distinguished in vivo. Importantly, the SELEX-seq platform is flexible and can be used to determine the relative affinities to any DNA sequence for any transcription factor or multiprotein complex.

Evaluation of methods for modeling transcription factor sequence specificity.

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 DNA-binding specificity, 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 nine 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 the in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices trained by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10% of the TFs examined here). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.