Repetitive DNA symmetry elements negatively regulate gene expression in embryonic stem cells.

Transcription factor (TF) binding to genomic DNA elements constitutes one of the key mechanisms that regulates gene expression program in cells. Both consensus and nonconsensus DNA sequence elements influence the recognition specificity of TFs. Based on the analysis of experimentally determined c-Myc binding preferences to genomic DNA, here we statistically predict that certain repetitive, nonconsensus DNA symmetry elements can relatively reduce TF-DNA binding preferences. This is in contrast to a different set of repetitive, nonconsensus symmetry elements that can increase the strength of TF-DNA binding. Using c-Myc enhancer reporter system containing consensus motif flanked by nonconsensus sequences in embryonic stem cells, we directly demonstrate that the enrichment in such negatively regulating repetitive symmetry elements is sufficient to reduce the gene expression level compared with native genomic sequences. Negatively regulating repetitive symmetry elements around consensus c-Myc motif and DNA sequences containing consensus c-Myc motif flanked by entirely randomized sequences show similar expression baseline. A possible explanation for this observation is that rather than complete repression, negatively regulating repetitive symmetry elements play a regulatory role in fine-tuning the reduction of gene expression, most probably by binding TFs other than c-Myc.

Transcription Factor Binding in Embryonic Stem Cells Is Constrained by DNA Sequence Repeat Symmetry.

Transcription factor (TF) recognition is dictated by the underlying DNA motif sequence specific for each TF. Here, we reveal that DNA sequence repeat symmetry plays a central role in defining TF-DNA-binding preferences. In particular, we find that different TFs bind similar symmetry patterns in the context of different developmental layers. Most TFs possess dominant preferences for similar DNA repeat symmetry types. However, in some cases, preferences of specific TFs are changed during differentiation, suggesting the importance of information encoded outside of known motif regions. Histone modifications also exhibit strong preferences for similar DNA repeat symmetry patterns unique to each type of modification. Next, using an in vivo reporter assay, we show that gene expression in embryonic stem cells can be positively modulated by the presence of genomic and computationally designed DNA oligonucleotides containing identified nonconsensus-repetitive sequence elements. This supports the hypothesis that certain nonconsensus-repetitive patterns possess a functional ability to regulate gene expression. We also performed a solution NMR experiment to probe the stability of double-stranded DNA via imino proton resonances for several double-stranded DNA sequences characterized by different repetitive patterns. We suggest that such local stability might play a key role in determining TF-DNA binding preferences. Overall, our findings show that despite the enormous sequence complexity of the TF-DNA binding landscape in differentiating embryonic stem cells, this landscape can be quantitatively characterized in simple terms using the notion of DNA sequence repeat symmetry.

Control of transcriptional pausing by biased thermal fluctuations on repetitive genomic sequences.

In the process of transcription elongation, RNA polymerase (RNAP) pauses at highly nonrandom positions across genomic DNA, broadly regulating transcription; however, molecular mechanisms responsible for the recognition of such pausing positions remain poorly understood. Here, using a combination of statistical mechanical modeling and high-throughput sequencing and biochemical data, we evaluate the effect of thermal fluctuations on the regulation of RNAP pausing. We demonstrate that diffusive backtracking of RNAP, which is biased by repetitive DNA sequence elements, causes transcriptional pausing. This effect stems from the increased microscopic heterogeneity of an elongation complex, and thus is entropy-dominated. This report shows a linkage between repetitive sequence elements encoded in the genome and regulation of RNAP pausing driven by thermal fluctuations.

Specificity-Determining DNA Triplet Code for Positioning of Human Preinitiation Complex.

The notion that transcription factors bind DNA only through specific, consensus binding sites has been recently questioned. No specific consensus motif for the positioning of the human preinitiation complex (PIC) has been identified. Here, we reveal that nonconsensus, statistical, DNA triplet code provides specificity for the positioning of the human PIC. In particular, we reveal a highly nonrandom, statistical pattern of repetitive nucleotide triplets that correlates with the genomewide binding preferences of PIC measured by Chip-exo. We analyze the triplet enrichment and depletion near the transcription start site and identify triplets that have the strongest effect on PIC-DNA nonconsensus binding. Using statistical mechanics, a random-binder model without fitting parameters, with genomic DNA sequence being the only input, we further validate that the nonconsensus nucleotide triplet code constitutes a key signature providing PIC binding specificity in the human genome. Our results constitute a proof-of-concept for, to our knowledge, a new design principle for protein-DNA recognition in the human genome, which can lead to a better mechanistic understanding of transcriptional regulation.

Protein-DNA binding in the absence of specific base-pair recognition.

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 repeat symmetries. Based on statistical mechanics modeling, we identify a new protein-DNA binding mechanism induced by DNA sequence symmetry in the absence of specific base-pair recognition, and experimentally demonstrate that this mechanism indeed governs protein-DNA binding preferences.

Nonconsensus Protein Binding to Repetitive DNA Sequence Elements Significantly Affects Eukaryotic Genomes.

Recent genome-wide experiments in different eukaryotic genomes provide an unprecedented view of transcription factor (TF) binding locations and of nucleosome occupancy. These experiments revealed that a large fraction of TF binding events occur in regions where only a small number of specific TF binding sites (TFBSs) have been detected. Furthermore, in vitro protein-DNA binding measurements performed for hundreds of TFs indicate that TFs are bound with wide range of affinities to different DNA sequences that lack known consensus motifs. These observations have thus challenged the classical picture of specific protein-DNA binding and strongly suggest the existence of additional recognition mechanisms that affect protein-DNA binding preferences. We have previously demonstrated that repetitive DNA sequence elements characterized by certain symmetries statistically affect protein-DNA binding preferences. We call this binding mechanism nonconsensus protein-DNA binding in order to emphasize the point that specific consensus TFBSs do not contribute to this effect. In this paper, using the simple statistical mechanics model developed previously, we calculate the nonconsensus protein-DNA binding free energy for the entire C. elegans and D. melanogaster genomes. Using the available chromatin immunoprecipitation followed by sequencing (ChIP-seq) results on TF-DNA binding preferences for ~100 TFs, we show that DNA sequences characterized by low predicted free energy of nonconsensus binding have statistically higher experimental TF occupancy and lower nucleosome occupancy than sequences characterized by high free energy of nonconsensus binding. This is in agreement with our previous analysis performed for the yeast genome. We suggest therefore that nonconsensus protein-DNA binding assists the formation of nucleosome-free regions, as TFs outcompete nucleosomes at genomic locations with enhanced nonconsensus binding. In addition, here we perform a new, large-scale analysis using in vitro TF-DNA preferences obtained from the universal protein binding microarrays (PBM) for ~90 eukaryotic TFs belonging to 22 different DNA-binding domain types. As a result of this new analysis, we conclude that nonconsensus protein-DNA binding is a widespread phenomenon that significantly affects protein-DNA binding preferences and need not require the presence of consensus (specific) TFBSs in order to achieve genome-wide TF-DNA binding specificity.

Genome-wide organization of eukaryotic preinitiation complex is influenced by nonconsensus protein-DNA binding.

Genome-wide binding preferences of the key components of eukaryotic preinitiation complex (PIC) have been recently measured at high resolution in Saccharomyces cerevisiae by Rhee and Pugh. However, the rules determining the PIC binding specificity remain poorly understood. In this study, we show that nonconsensus protein-DNA binding significantly influences PIC binding preferences. We estimate that such nonconsensus binding contributes statistically at least 2-3 kcal/mol (on average) of additional attractive free energy per protein per core-promoter region. The predicted attractive effect is particularly strong at repeated poly(dA:dT) and poly(dC:dG) tracts. Overall, the computed free-energy landscape of nonconsensus protein-DNA binding shows strong correlation with the measured genome-wide PIC occupancy. Remarkably, statistical PIC preferences of binding to both TFIID-dominated and SAGA-dominated genes correlate with the nonconsensus free-energy landscape, yet these two groups of genes are distinguishable based on the average free-energy profiles. We suggest that the predicted nonconsensus binding mechanism provides a genome-wide background for specific promoter elements, such as transcription-factor binding sites, TATA-like elements, and specific binding of the PIC components to nucleosomes. We also show that nonconsensus binding has genome-wide influence on transcriptional frequency.

Positive and negative design for nonconsensus protein-DNA binding affinity in the vicinity of functional binding sites.

Recent experiments provide an unprecedented view of protein-DNA binding in yeast and human genomes at single-nucleotide resolution. These measurements, performed over large cell populations, show quite generally that sequence-specific transcription regulators with well-defined protein-DNA consensus motifs bind only a fraction among all consensus motifs present in the genome. Alternatively, proteins in vivo often bind DNA regions lacking known consensus sequences. The rules determining whether a consensus motif is functional remain incompletely understood. Here we predict that genomic background surrounding specific protein-DNA binding motifs statistically modulates the binding of sequence-specific transcription regulators to these motifs. In particular, we show that nonconsensus protein-DNA binding in yeast is statistically enhanced, on average, around functional Reb1 motifs that are bound as compared to nonfunctional Reb1 motifs that are unbound. The landscape of nonconsensus protein-DNA binding around functional CTCF motifs in human demonstrates a more complex behavior. In particular, human genomic regions characterized by the highest CTCF occupancy, show statistically reduced level of nonconsensus protein-DNA binding. Our findings suggest that nonconsensus protein-DNA binding is fine-tuned around functional binding sites using a variety of design strategies.

Nonspecific protein-DNA binding is widespread in the yeast genome.

Recent genome-wide measurements of binding preferences of ~200 transcription regulators in the vicinity of transcription start sites in yeast, have provided a unique insight into the cis-regulatory code of a eukaryotic genome. Here, we show that nonspecific transcription factor (TF)-DNA binding significantly influences binding preferences of the majority of transcription regulators in promoter regions of the yeast genome. We show that promoters of SAGA-dominated and TFIID-dominated genes can be statistically distinguished based on the landscape of nonspecific protein-DNA binding free energy. In particular, we predict that promoters of SAGA-dominated genes possess wider regions of reduced free energy compared to promoters of TFIID-dominated genes. We also show that specific and nonspecific TF-DNA binding are functionally linked and cooperatively influence gene expression in yeast. Our results suggest that nonspecific TF-DNA binding is intrinsically encoded into the yeast genome, and it may play a more important role in transcriptional regulation than previously thought.

DNA sequence correlations shape nonspecific transcription factor-DNA binding affinity.

Transcription factors (TFs) are regulatory proteins that bind DNA in promoter regions of the genome and either promote or repress gene expression. Here, we predict analytically that enhanced homooligonucleotide sequence correlations, such as poly(dA:dT) and poly(dC:dG) tracts, statistically enhance nonspecific TF-DNA binding affinity. This prediction is generic and qualitatively independent of microscopic parameters of the model. We show that nonspecific TF binding affinity is universally controlled by the strength and symmetry of DNA sequence correlations. We perform correlation analysis of the yeast genome and show that DNA regions highly occupied by TFs exhibit stronger homooligonucleotide sequence correlations, and thus a higher propensity for nonspecific binding, than do poorly occupied regions. We suggest that this effect plays the role of an effective localization potential that enhances quasi-one-dimensional diffusion of TFs in the vicinity of DNA, speeding up the stochastic search process for specific TF binding sites. The effect is also predicted to impose an upper bound on the size of TF-DNA binding motifs.

Nonspecific transcription-factor-DNA binding influences nucleosome occupancy in yeast.

Quantitative understanding of the principles regulating nucleosome occupancy on a genome-wide level is a central issue in eukaryotic genomics. Here, we address this question using budding yeast, Saccharomyces cerevisiae, as a model organism. We perform a genome-wide computational analysis of the nonspecific transcription factor (TF)-DNA binding free-energy landscape and compare this landscape with experimentally determined nucleosome-binding preferences. We show that DNA regions with enhanced nonspecific TF-DNA binding are statistically significantly depleted of nucleosomes. We suggest therefore that the competition between TFs with histones for nonspecific binding to genomic sequences might be an important mechanism influencing nucleosome-binding preferences in vivo. We also predict that poly(dA:dT) and poly(dC:dG) tracts represent genomic elements with the strongest propensity for nonspecific TF-DNA binding, thus allowing TFs to outcompete nucleosomes at these elements. Our results suggest that nonspecific TF-DNA binding might provide a barrier for statistical positioning of nucleosomes throughout the yeast genome. We predict that the strength of this barrier increases with the concentration of DNA binding proteins in a cell. We discuss the connection of the proposed mechanism with the recently discovered pathway of active nucleosome reconstitution.

Sequence correlations shape protein promiscuity.

We predict analytically that diagonal correlations of amino acid positions within protein sequences statistically enhance protein propensity for nonspecific binding. We use the term "promiscuity" to describe such nonspecific binding. Diagonal correlations represent statistically significant repeats of sequence patterns where amino acids of the same type are clustered together. The predicted effect is qualitatively robust with respect to the form of the microscopic interaction potentials and the average amino acid composition. Our analytical results provide an explanation for the enhanced diagonal correlations observed in hubs of eukaryotic organismal proteomes [J. Mol. Biol. 409, 439 (2011)]. We suggest experiments that will allow direct testing of the predicted effect.

Avidity observed between a bivalent inhibitor and an enzyme monomer with a single active site.

Although myriad protein-protein interactions in nature use polyvalent binding, in which multiple ligands on one entity bind to multiple receptors on another, to date an affinity advantage of polyvalent binding has been demonstrated experimentally only in cases where the target receptor molecules are clustered prior to complex formation. Here, we demonstrate cooperativity in binding affinity (i.e., avidity) for a protein complex in which an engineered dimer of the amyloid precursor protein inhibitor (APPI), possessing two fully functional inhibitory loops, interacts with mesotrypsin, a soluble monomeric protein that does not self-associate or cluster spontaneously. We found that each inhibitory loop of the purified APPI homodimer was over three-fold more potent than the corresponding loop in the monovalent APPI inhibitor. This observation is consistent with a suggested mechanism whereby the two APPI loops in the homodimer simultaneously and reversibly bind two corresponding mesotrypsin monomers to mediate mesotrypsin dimerization. We propose a simple model for such dimerization that quantitatively explains the observed cooperativity in binding affinity. Binding cooperativity in this system reveals that the valency of ligands may affect avidity in protein-protein interactions including those of targets that are not surface-anchored and do not self-associate spontaneously. In this scenario, avidity may be explained by the enhanced concentration of ligand binding sites in proximity to the monomeric target, which may favor rebinding of the multiple ligand binding sites with the receptor molecules upon dissociation of the protein complex.

Control of Transcription Initiation by Biased Thermal Fluctuations on Repetitive Genomic Sequences.

In the process of transcription initiation by RNA polymerase, promoter DNA sequences affect multiple reaction pathways determining the productivity of transcription. However, the question of how the molecular mechanism of transcription initiation depends on the sequence properties of promoter DNA remains poorly understood. Here, combining the statistical mechanical approach with high-throughput sequencing results, we characterize abortive transcription and pausing during transcription initiation by Escherichia coli RNA polymerase at a genome-wide level. Our results suggest that initially transcribed sequences, when enriched with thymine bases, contain the signal for inducing abortive transcription, whereas certain repetitive sequence elements embedded in promoter regions constitute the signal for inducing pausing. Both signals decrease the productivity of transcription initiation. Based on solution NMR and in vitro transcription measurements, we suggest that repetitive sequence elements within the promoter DNA modulate the nonlocal base pair stability of its double-stranded form. This stability profoundly influences the reaction coordinates of the productive initiation via pausing.

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling.

DNA primase synthesizes short RNA primers that initiate DNA synthesis of Okazaki fragments on the lagging strand by DNA polymerase during DNA replication. The binding of prokaryotic DnaG-like primases to DNA occurs at a specific trinucleotide recognition sequence. It is a pivotal step in the formation of Okazaki fragments. Conventional biochemical tools that are used to determine the DNA recognition sequence of DNA primase provide only limited information. Using a high-throughput microarray-based binding assay and consecutive biochemical analyses, it has been shown that 1) the specific binding context (flanking sequences of the recognition site) influences the binding strength of the DNA primase to its template DNA, and 2) stronger binding of primase to the DNA yields longer RNA primers, indicating higher processivity of the enzyme. This method combines PBM and primase activity assay and is designated as high-throughput primase profiling (HTPP), and it allows characterization of specific sequence recognition by DNA primase in unprecedented time and scalability.

Transcription pausing: biological significance of thermal fluctuations biased by repetitive genomic sequences.

Transcription of DNA by RNA polymerase (RNAP) takes place in a cell environment dominated by thermal fluctuations. How are transcription reactions including initiation, elongation, and termination on genomic DNA so well-controlled during such fluctuations? A recent statistical mechanical approach using high-throughput sequencing data reveals that repetitive DNA sequence elements embedded into a genomic sequence provide the key mechanism to functionally bias the fluctuations of transcription elongation complexes. In particular, during elongation pausing, such repetitive sequence elements can increase the magnitude of one-dimensional diffusion of the RNAP enzyme on the DNA upstream of the pausing site, generating a large variation in the dwell times of RNAP pausing under the control of these genomic signals.

DNA Sequence Context Controls the Binding and Processivity of the T7 DNA Primase.

Primases are key enzymes involved in DNA replication. They act on single-stranded DNA and catalyze the synthesis of short RNA primers used by DNA polymerases. Here, we investigate the DNA binding and activity of the bacteriophage T7 primase using a new workflow called high-throughput primase profiling (HTPP). Using a unique combination of high-throughput binding assays and biochemical analyses, HTPP reveals a complex landscape of binding specificity and functional activity for the T7 primase, determined by sequences flanking the primase recognition site. We identified specific features, such as G/T-rich flanks, which increase primase-DNA binding up to 10-fold and, surprisingly, also increase the length of newly formed RNA (up to 3-fold). To our knowledge, variability in primer length has not been reported for this primase. We expect that applying HTPP to additional enzymes will reveal new insights into the effects of DNA sequence composition on the DNA recognition and functional activity of primases.

Multi-scale sequence correlations increase proteome structural disorder and promiscuity.

Numerous experiments demonstrate a high level of promiscuity and structural disorder in organismal proteomes. Here, we ask the question what makes a protein promiscuous, that is, prone to nonspecific interactions, and structurally disordered. We predict that multi-scale correlations of amino acid positions within protein sequences statistically enhance the propensity for promiscuous intra- and inter-protein binding. We show that sequence correlations between amino acids of the same type are statistically enhanced in structurally disordered proteins and in hubs of organismal proteomes. We also show that structurally disordered proteins possess a significantly higher degree of sequence order than structurally ordered proteins. We develop an analytical theory for this effect and predict the robustness of our conclusions with respect to the amino acid composition and the form of the microscopic potential between the interacting sequences. Our findings have implications for understanding molecular mechanisms of protein aggregation diseases induced by the extension of sequence repeats.