A regulatory role for repeated decoy transcription factor binding sites in target gene expression.
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ABSTRACT:
SUBMITTER: Lee TH
PROVIDER: S-EPMC3322331 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The genome contains several high-affinity non-functional binding sites for transcription factors (TFs) creating a hidden and unexplored layer of gene regulation. We investigate the role of such "decoy sites" in controlling noise (random fluctuations) in the level of a TF that is synthesized in stochastic bursts. Prior studies have assumed that decoy-bound TFs are protected from degradation, and in this case decoys function to buffer noise. Relaxing this assumption to consider arbitrary degradation rates for both bound/unbound TF states, we find rich noise behaviors. For low-affinity decoys, noise in the level of unbound TF always monotonically decreases to the Poisson limit with increasing decoy numbers. In contrast, for high-affinity decoys, noise levels first increase with increasing decoy numbers, before decreasing back to the Poisson limit. Interestingly, while protection of bound TFs from degradation slows the time-scale of fluctuations in the unbound TF levels, the decay of bound TFs leads to faster fluctuations and smaller noise propagation to downstream target proteins. In summary, our analysis reveals stochastic dynamics emerging from nonspecific binding of TFs and highlights the dual role of decoys as attenuators or amplifiers of gene expression noise depending on their binding affinity and stability of the bound TF.
| S-EPMC7272470 | biostudies-literature
Project description:Transcription factor decoy binding sites are short DNA sequences that can titrate a transcription factor away from its natural binding site, therefore regulating gene expression. In this study, we harness synthetic transcription factor decoy systems to regulate gene expression for metabolic pathways in Escherichia coli. We show that transcription factor decoys can effectively regulate expression of native and heterologous genes. Tunability of the decoy can be engineered via changes in copy number or modifications to the DNA decoy site sequence. Using arginine biosynthesis as a showcase, we observed a 16-fold increase in arginine production when we introduced the decoy system to steer metabolic flux towards increased arginine biosynthesis, with negligible growth differences compared to the wild type strain. The decoy-based production strain retains high genetic integrity; in contrast to a gene knock-out approach where mutations were common, we detected no mutations in the production system using the decoy-based strain. We further show that transcription factor decoys are amenable to multiplexed library screening by demonstrating enhanced tolerance to pinene with a combinatorial decoy library. Our study shows that transcription factor decoy binding sites are a powerful and compact tool for metabolic engineering.
| S-EPMC7826281 | biostudies-literature
Project description:Studies of transcription regulation are often focused on binding of transcription factors (TFs) to a small number of promoters of interest. It is often assumed that TFs are in great excess to their binding sites (TFBSs) and competition for TFs between DNA sites is seldom considered. With increasing evidence that TFBSs are exceedingly abundant for many TFs and significant variations in TF and TFBS numbers occur during growth, the interplay between a TF and all TFBSs should not be ignored. Here, we use additional decoy DNA sites to quantitatively analyze how the relative abundance of a TF to its TFBSs impacts the steady-state level and onset time of gene expression for the auto-activated Escherichia coli PhoB response regulator. We show that increasing numbers of decoy sites progressively delayed transcription activation and lowered promoter activities. Perturbation of transcription regulation by additional TFBSs did not require extreme numbers of decoys, suggesting that PhoB is approximately at capacity for its DNA sites. Addition of decoys also converted a graded response to a bi-modal response. We developed a binding competition model that captures the major features of experimental observations, providing a quantitative framework to assess how variations in TFs and TFBSs influence transcriptional responses.
| S-EPMC8599769 | biostudies-literature
Project description:Flower development is controlled by the action of key regulatory transcription factors of the MADS-domain family. The function of these factors appears to be highly conserved among species based on mutant phenotypes. However, the conservation of their downstream processes is much less well understood, mostly because the evolutionary turnover and variation of their DNA-binding sites (BSs) among plant species have not yet been experimentally determined. Here, we performed comparative ChIP (chromatin immunoprecipitation)-seq experiments of the MADS-domain transcription factor SEPALLATA3 (SEP3) in two closely related Arabidopsis species: Arabidopsis thaliana and A. lyrata which have very similar floral organ morphology. We found that BS conservation is associated with DNA sequence conservation, the presence of the CArG-box BS motif and on the relative position of the BS to its potential target gene. Differences in genome size and structure can explain that SEP3 BSs in A. lyrata can be located more distantly to their potential target genes than their counterparts in A. thaliana. In A. lyrata, we identified transposition as a mechanism to generate novel SEP3 binding locations in the genome. Comparative gene expression analysis shows that the loss/gain of BSs is associated with a change in gene expression. In summary, this study investigates the evolutionary dynamics of DNA BSs of a floral key-regulatory transcription factor and explores factors affecting this phenomenon.
| S-EPMC4693976 | biostudies-literature
Project description:Identification of transcription factor targets is critical to understanding gene regulatory networks. Here, we uncover transcription factor binding sites and target genes employing systematic evolution of ligands by exponential enrichment (SELEX). Instead of selecting randomly synthesized DNA oligonucleotides as in most SELEX studies, we utilized zebrafish genomic DNA to isolate fragments bound by Fezf2, an evolutionarily conserved gene critical for vertebrate forebrain development. This is, to our knowledge, the first time that SELEX is applied to a vertebrate genome. Computational analysis of bound genomic fragments predicted a core consensus binding site, which identified response elements that mediated Fezf2-dependent transcription both in vitro and in vivo. Fezf2-bound fragments were enriched for conserved sequences. Surprisingly, ?20% of these fragments overlapped well annotated protein-coding exons. Through loss of function, gain of function, and chromatin immunoprecipitation, we further identified and validated eomesa/tbr2 and lhx2b as biologically relevant target genes of Fezf2. Mutations in eomesa/tbr2 cause microcephaly in humans, whereas lhx2b is a critical regulator of cell fate and axonal targeting in the developing forebrain. These results demonstrate the feasibility of employing genomic SELEX to identify vertebrate transcription factor binding sites and target genes and reveal Fezf2 as a transcription activator and a candidate for evaluation in human microcephaly.
| S-EPMC3099680 | biostudies-literature
Project description:The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.
| S-EPMC8235176 | biostudies-literature
Project description:Despite the prominent roles played by R2R3-MYB transcription factors in the regulation of plant gene expression, little is known about the details of how these proteins interact with their DNA targets. For example, while Arabidopsis thaliana R2R3-MYB protein AtMYB61 is known to alter transcript abundance of a specific set of target genes, little is known about the specific DNA sequences to which AtMYB61 binds. To address this gap in knowledge, DNA sequences bound by AtMYB61 were identified using cyclic amplification and selection of targets (CASTing). The DNA targets identified using this approach corresponded to AC elements, sequences enriched in adenosine and cytosine nucleotides. The preferred target sequence that bound with the greatest affinity to AtMYB61 recombinant protein was ACCTAC, the AC-I element. Mutational analyses based on the AC-I element showed that ACC nucleotides in the AC-I element served as the core recognition motif, critical for AtMYB61 binding. Molecular modelling predicted interactions between AtMYB61 amino acid residues and corresponding nucleotides in the DNA targets. The affinity between AtMYB61 and specific target DNA sequences did not correlate with AtMYB61-driven transcriptional activation with each of the target sequences. CASTing-selected motifs were found in the regulatory regions of genes previously shown to be regulated by AtMYB61. Taken together, these findings are consistent with the hypothesis that AtMYB61 regulates transcription from specific cis-acting AC elements in vivo. The results shed light on the specifics of DNA binding by an important family of plant-specific transcriptional regulators.
| S-EPMC3669277 | biostudies-literature
Project description:To represent the sequence specificity of transcription factors, the position weight matrix (PWM) is widely used. In most cases, each element is defined as a log likelihood ratio of a base appearing at a certain position, which is estimated from a finite number of known binding sites. To avoid bias due to this small sample size, a certain numeric value, called a pseudocount, is usually allocated for each position, and its fraction according to the background base composition is added to each element. So far, there has been no consensus on the optimal pseudocount value. In this study, we simulated the sampling process by artificially generating binding sites based on observed nucleotide frequencies in a public PWM database, and then the generated matrix with an added pseudocount value was compared to the original frequency matrix using various measures. Although the results were somewhat different between measures, in many cases, we could find an optimal pseudocount value for each matrix. These optimal values are independent of the sample size and are clearly correlated with the entropy of the original matrices, meaning that larger pseudocount vales are preferable for less conserved binding sites. As a simple representative, we suggest the value of 0.8 for practical uses.
| S-EPMC2647310 | biostudies-literature
Project description:Defining the hardwiring of transcription factors to their cognate genomic binding sites is essential for our understanding of biological processes. We used scanning chromatin immunoprecipitation to identify in vivo binding regions (E boxes) for c-Myc in three target genes as a model system. Along with other c-Myc target genes that have been validated by chromatin immunoprecipitation, we used the publicly available genomic sequences to determine whether experimentally derived in vivo binding sites might be predictable from nonexonic sequence conservation across species. Our studies revealed two classes of target genomic binding sites. Although the majority of target genes studied [class I: B23 (NPM1), CAD, CDK4, cyclin D2, ID2, LDH-A, MNT, PTMa, ODC, NM23B, nucleolin, prohibitin, SHMT1, and SHMT2] demonstrate significant sequence conservation of the E boxes and flanking regions, several genes (cyclin B1, JPO1, and PRDX3) belong to a second class (class II) that does not display sequence conservation at and around the site of c-Myc binding. On the basis of our model, we propose a strategy for predicting transcription factor binding sites using phylogenetic sequence comparisons, which will select potential class I target genes among the many emerging candidates from DNA-microarray studies for experimental validation by chromatin immunoprecipitation.
| S-EPMC154342 | biostudies-literature
Project description:MotivationIdentifying the target genes regulated by transcription factors (TFs) is the most basic step in understanding gene regulation. Recent advances in high-throughput sequencing technology, together with chromatin immunoprecipitation (ChIP), enable mapping TF binding sites genome wide, but it is not possible to infer function from binding alone. This is especially true in mammalian systems, where regulation often occurs through long-range enhancers in gene-rich neighborhoods, rather than proximal promoters, preventing straightforward assignment of a binding site to a target gene.ResultsWe present EMBER (Expectation Maximization of Binding and Expression pRofiles), a method that integrates high-throughput binding data (e.g. ChIP-chip or ChIP-seq) with gene expression data (e.g. DNA microarray) via an unsupervised machine learning algorithm for inferring the gene targets of sets of TF binding sites. Genes selected are those that match overrepresented expression patterns, which can be used to provide information about multiple TF regulatory modes. We apply the method to genome-wide human breast cancer data and demonstrate that EMBER confirms a role for the TFs estrogen receptor alpha, retinoic acid receptors alpha and gamma in breast cancer development, whereas the conventional approach of assigning regulatory targets based on proximity does not. Additionally, we compare several predicted target genes from EMBER to interactions inferred previously, examine combinatorial effects of TFs on gene regulation and illustrate the ability of EMBER to discover multiple modes of regulation.AvailabilityAll code used for this work is available at http://dinner-group.uchicago.edu/downloads.html.
| S-EPMC3259433 | biostudies-literature