The Influence of Transcription Factor Competition on the Relationship between Occupancy and Affinity

Transcription factors (TFs) are proteins that bind to specific sites on the DNA and regulate gene activity. Identifying where TF molecules bind and how much time they spend on their target sites is key to understanding transcriptional regulation. It is usually assumed that the free energy of binding of a TF to the DNA (the affinity of the site) is highly correlated to the amount of time the TF remains bound (the occupancy of the site). However, knowing the binding energy is not sufficient to infer actual binding site occupancy. This mismatch between the occupancy predicted by the affinity and the observed occupancy may be caused by various factors, such as TF abundance, competition between TFs or the arrangement of the sites on the DNA. We investigated the relationship between the affinity of a TF for a set of binding sites and their occupancy. In particular, we considered the case of the transcription factor lac repressor (lacI) in E.coli, and performed stochastic simulations of the TF dynamics on the DNA for various combinations of lacI abundance and competing TFs that contribute to macromolecular crowding. We also investigated the relationship of site occupancy and the information content of position weight matrices (PWMs) used to represent binding sites. Our results showed that for medium and high affinity sites, TF competition does not play a significant role for genomic occupancy except in cases when the abundance of the TF is significantly increased, or when the PWM displays relatively low information content. Nevertheless, for medium and low affinity sites, an increase in TF abundance (for both cognate and non-cognate molecules) leads to an increase in occupancy at several sites. © 2013 Zabet et al

Rare and Frequent Promoter Methylation, Respectively, of TSHZ2 and 3 Genes That Are Both Downregulated in Expression in Breast and Prostate Cancers

Neoplastic cells harbor both hypomethylated and hypermethylated regions of DNA. Whereas hypomethylation is found mainly in repeat sequences, regional hypermethylation has been linked to the transcriptional silencing of certain tumor suppressor genes. We attempted to search for candidate genes involved in breast/prostate carcinogenesis, using the criteria that they should be expressed in primary cultures of normal breast/prostate epithelial cells but are frequently downregulated in breast/prostate cancer cell lines and that their promoters are hypermethylated.We identified several dozens of candidates among 194 homeobox and related genes using Systematic Multiplex RT-PCR and among 23,000 known genes and 23,000 other expressed sequences in the human genome by DNA microarray hybridization. An additional examination, by real-time qRT-PCR of clinical specimens of breast cancer, further narrowed the list of the candidates. Among them, the most frequently downregulated genes in tumors were NP_775756 and ZNF537, from the homeobox gene search and the genome-wide search, respectively. To our surprise, we later discovered that these genes belong to the same gene family, the 3-member Teashirt family, bearing the new names of TSHZ2 and TSHZ3. We subsequently determined the methylation status of their gene promoters. The TSHZ3 gene promoter was found to be methylated in all the breast/prostate cancer cell lines and some of the breast cancer clinical specimens analyzed. The TSHZ2 gene promoter, on the other hand, was unmethylated except for the MDA-MB-231 breast cancer cell line. The TSHZ1 gene was always expressed, and its promoter was unmethylated in all cases.TSHZ2 and TSHZ3 genes turned out to be the most interesting candidates for novel tumor suppressor genes. Expression of both genes is downregulated. However, differential promoter methylation suggests the existence of distinctive mechanisms of transcriptional inactivation for these genes

Identification of a single nucleotide change in a mutant gene for hypoxanthine-guanine phosphoribosyltransferase (HPRT Ann Arbor)

HPRT Ann Arbor is a variant of hypoxanthine (guanine) phosphoribosyl-transferase (HPRT: EC 2.4.2.8), which was identified in two brothers with hyperuricemia and nephrolithiasis. In previous studies, this mutant enzyme was characterized by an increased K m for both substrates, a normal V max , a decreased intracellular concentration of enzyme protein, a normal subunit molecular weight and an acidic isoelectric point under native isoelectric focusing conditions. We have cloned a full-length cDNA for HPRT Ann Arbor and determined its complete nucleotide sequence. A single nucleotide change (T→G) at nucleotide position 396 has been identified. This transversion predicts an amino acid substitution from isoleucine (ATT) to methionine (ATG) in codon 132, which is located within the putative 5′-phosphoribosyl-1-pyrophosphate (PRPP)-binding site of HPRT.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47622/1/439_2004_Article_BF00291707.pd

A Conserved Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila

Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells

Alanine Zipper-Like Coiled-Coil Domains Are Necessary for Homotypic Dimerization of Plant GAGA-Factors in the Nucleus and Nucleolus

GAGA-motif binding proteins control transcriptional activation or repression of homeotic genes. Interestingly, there are no sequence similarities between animal and plant proteins. Plant BBR/BPC-proteins can be classified into two distinct groups: Previous studies have elaborated on group I members only and so little is known about group II proteins. Here, we focused on the initial characterization of AtBPC6, a group II protein from Arabidopsis thaliana. Comparison of orthologous BBR/BPC sequences disclosed two conserved signatures besides the DNA binding domain. A first peptide signature is essential and sufficient to target AtBPC6-GFP to the nucleus and nucleolus. A second domain is predicted to form a zipper-like coiled-coil structure. This novel type of domain is similar to Leucine zippers, but contains invariant alanine residues with a heptad spacing of 7 amino acids. By yeast-2-hybrid and BiFC-assays we could show that this Alanine zipper domain is essential for homotypic dimerization of group II proteins in vivo. Interhelical salt bridges and charge-stabilized hydrogen bonds between acidic and basic residues of the two monomers are predicted to form an interaction domain, which does not follow the classical knobs-into-holes zipper model. FRET-FLIM analysis of GFP/RFP-hybrid fusion proteins validates the formation of parallel dimers in planta. Sequence comparison uncovered that this type of domain is not restricted to BBR/BPC proteins, but is found in all kingdoms

Genomic organization, sequence analysis and expression of all five genes encoding the small subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase from tomato

We have cloned and sequenced all five members of the gene family for the small subunit (rbcS) of ribulose-1,5-bisphosphate carboxylase/oxygenase from tomato, Lycopersicon esculentum cv. VFNT LA 1221 cherry line. Two of the five genes, designated Rbcs-1 and Rbcs-2 , are present as single genes at individual loci. Three genes, designated Rbcs-3A, Rbcs-3B and Rbcs-3C , are organized in a tandem array within 10 kb at a third independent locus. The Rbcs-2 gene contains three introns; all the other members of the tomato gene family contain two introns. The coding sequence of Rbcs-1 differs by 14.0% from that of Rbcs-2 and by 13.3% from that of Rbcs-3 genes. Rbcs-2 shows 10.4% divergence from Rbcs-3 . The exon and intron sequences of Rbcs-3A are identical to those of Rbcs-3C , and differ by 1.9% from those of Rbcs-3B . Nucleotide sequence analysis suggests that the five rbcS genes encode four different precursors, and three different mature polypeptides. S 1 nuclease mapping of the 5′ end of rbcS mRNAs revealed that the mRNA leader sequences vary in length from 8 to 75 nucleotides. Northern analysis using gene-specific oligonucleotide probes from the 3′ non-coding region of each gene reveals a four to five-fold difference among the five genes in maximal steady-state mRNA levels in leaves.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47566/1/438_2004_Article_BF00329650.pd

Quantitative Models of the Mechanisms That Control Genome-Wide Patterns of Transcription Factor Binding during Early Drosophila Development

Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6–0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision

A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

Functional transcription factor target discovery via compendia of binding and expression profiles

Genome-wide experiments to map the DNA-binding locations of transcription-associated factors (TFs) have shown that the number of genes bound by a TF far exceeds the number of possible direct target genes. Distinguishing functional from non-functional binding is therefore a major challenge in the study of transcriptional regulation. We hypothesized that functional targets can be discovered by correlating binding and expression profiles across multiple experimental conditions. To test this hypothesis, we obtained ChIP-seq and RNA-seq data from matching cell types from the human ENCODE resource, considered promoter-proximal and distal cumulative regulatory models to map binding sites to genes, and used a combination of linear and non-linear measures to correlate binding and expression data. We found that a high degree of correlation between a gene's TF-binding and expression profiles was significantly more predictive of the gene being differentially expressed upon knockdown of that TF, compared to using binding sites in the cell type of interest only. Remarkably, TF targets predicted from correlation across a compendium of cell types were also predictive of functional targets in other cell types. Finally, correlation across a time course of ChIP-seq and RNA-seq experiments was also predictive of functional TF targets in that tissue.Comment: 15 pages + 8 pages supplementary material; 6 figures, 6 supplementary figures, 5 supplementary table