Biomedical subjects

Gary D Stormo

Publications and source records attributed to Gary D Stormo.

At least 19 recordsLinked to original sources

PubMed2005

Target selectivity of vertebrate notch proteins. Collaboration between discrete domains and CSL-binding site architecture determines activation probability.

All four mammalian Notch proteins interact with a single DNA-binding protein (RBP-jkappa), yet they are not equivalent in activating target genes. Parallel assays of three Notch-responsive promoters in several cell lines revealed that relative activation strength is dependent on protein module and promoter context more than the cellular context. Each Notch protein reads binding site orientation and distribution on the promoter differently; Notch1 performs extremely well on paired sites, and Notch3 prefers single sites in conjunction with a proximal zinc finger transcription factor. Although head-head sites can elicit a Notch response on their own, use of CBS (CSL binding site) in tail-tail orientation is context-dependent. Bias for specific DNA elements is achieved by interplay between the N-terminal RAM (RBP-jkappa-associated molecule/ankyrin region), which interprets CBS proximity and orientation, and the C-terminal transactivation domain that interacts specifically with the transcription machinery or nearby factors. To confirm the prediction that modular design underscores the evolution of functional divergence between Notch proteins, we generated a synthetic Notch protein (Notch1 ankyrin with Notch3 transactivation domain) that displayed superior signaling strength on the hes5 promoter. Consistent with the prediction that "preferred" targets (Hes1) should respond faster and at lower Notch concentration than other targets, we showed that Hes5-GFP was extinguished fast and recovered slowly, whereas Hes1-GFP was inhibited late and recovered quickly after a pulse of DAPT in metanephroi cultures.

Animals↗

PubMed2005

Identifying the conserved network of cis-regulatory sites of a eukaryotic genome.

A major focus of genome research has been to decipher the cis-regulatory code that governs complex transcriptional regulation. We report a computational approach for identifying conserved regulatory motifs of an organism directly from whole genome sequences of several related species without reliance on additional information. We first construct phylogenetic profiles for each promoter, then use a BLAST-like algorithm to efficiently search through the entire profile space of all of the promoters in the genome to identify conserved motifs and the promoters that contain them. Statistical significance is estimated by modified Karlin-Altschul statistics. We applied this approach to the analysis of 3,524 Saccharomyces cerevisiae promoters and identified a highly organized regulatory network involving 3,315 promoters and 296 motifs. This network includes nearly all of the currently known motifs and covers >90% of known transcription factor binding sites. Most of the predicted coregulated gene clusters in the network have additional supporting evidence. Theoretical analysis suggests that our algorithm should be applicable to much larger genomes, such as the human genome, without reaching its statistical limitation.

Algorithms↗

PubMed2005

Direct, androgen receptor-mediated regulation of the FKBP5 gene via a distal enhancer element.

Androgen signaling via the androgen receptor (AR) transcription factor is crucial to normal prostate homeostasis and prostate tumorigenesis. Current models of AR function are predominantly based on studies of prostate-specific antigen regulation in androgen-responsive cell lines. To expand on these in vitro paradigms, we used the mouse prostate to elucidate the mechanisms through which AR regulates another direct target, FKBP5, in vivo. FKBP5 encodes an immunophilin that has been previously implicated in glucocorticoid and progestin signaling pathways and that likely influences prostate physiology in the presence of androgens. In this work, we show that androgens directly regulate FKBP5 via an interaction between the AR and a distal enhancer located 65 kb downstream of the transcription start site in the fifth intron of the FKBP5 gene. We have found that AR selectively recruits cAMP response element-binding protein to this enhancer. These interactions, in turn, result in chromatin remodeling that affects the enhancer proper but not the FKBP5 locus as a whole. Furthermore, in contrast to prostate-specific antigen-regulatory mechanisms, we show that transactivation of the FKBP5 gene does not rely on a single looping complex to mediate communication between the distal enhancer and proximal promoter. Rather, the distal enhancer complex and basal transcription apparatus communicate indirectly with one another, implicating a regulatory mechanism that has not been previously appreciated for AR target genes.

Animals↗

PubMed2005

Combining SELEX with quantitative assays to rapidly obtain accurate models of protein-DNA interactions.

Models for the specificity of DNA-binding transcription factors are often based on small amounts of qualitative data and therefore have limited accuracy. In this study we demonstrate a simple and efficient method of affinity chromatography-SELEX followed by a quantitative binding (QuMFRA) assay to rapidly collect the data necessary for more accurate models. Using the zinc finger protein EGR as an e.g. we show that many bindings sites can be obtained efficiently with affinity chromatography-SELEX, but those sequences alone provide a weight matrix model with limited accuracy. Using a QuMFRA assay to determine the quantitative relative affinity for only a subset of the sequences obtained by SELEX leads to a much more accurate model. Application of this method to variants of a transcription factor would allow us to generate a large collection of quantitative data for modeling protein-DNA interactions that could facilitate the determination of recognition codes for different transcription factor families.

Base Sequence↗

PubMed2005

Quantitative analysis of EGR proteins binding to DNA: assessing additivity in both the binding site and the protein.

BACKGROUND: Recognition codes for protein-DNA interactions typically assume that the interacting positions contribute additively to the binding energy. While this is known to not be precisely true, an additive model over the DNA positions can be a good approximation, at least for some proteins. Much less information is available about whether the protein positions contribute additively to the interaction. RESULTS: Using EGR zinc finger proteins, we measure the binding affinity of six different variants of the protein to each of six different variants of the consensus binding site. Both the protein and binding site variants include single and double mutations that allow us to assess how well additive models can account for the data. For each protein and DNA alone we find that additive models are good approximations, but over the combined set of data there are context effects that limit their accuracy. However, a small modification to the purely additive model, with only three additional parameters, improves the fit significantly. CONCLUSION: The additive model holds very well for every DNA site and every protein included in this study, but clear context dependence in the interactions was detected. A simple modification to the independent model provides a better fit to the complete data.

Algorithms↗

PubMed2005

enoLOGOS: a versatile web tool for energy normalized sequence logos.

enoLOGOS is a web-based tool that generates sequence logos from various input sources. Sequence logos have become a popular way to graphically represent DNA and amino acid sequence patterns from a set of aligned sequences. Each position of the alignment is represented by a column of stacked symbols with its total height reflecting the information content in this position. Currently, the available web servers are able to create logo images from a set of aligned sequences, but none of them generates weighted sequence logos directly from energy measurements or other sources. With the advent of high-throughput technologies for estimating the contact energy of different DNA sequences, tools that can create logos directly from binding affinity data are useful to researchers. enoLOGOS generates sequence logos from a variety of input data, including energy measurements, probability matrices, alignment matrices, count matrices and aligned sequences. Furthermore, enoLOGOS can represent the mutual information of different positions of the consensus sequence, a unique feature of this tool. Another web interface for our software, C2H2-enoLOGOS, generates logos for the DNA-binding preferences of the C2H2 zinc-finger transcription factor family members. enoLOGOS and C2H2-enoLOGOS are accessible over the web at http://biodev.hgen.pitt.edu/enologos/.

Amino Acids↗

PubMed2005

Computational technique for improvement of the position-weight matrices for the DNA/protein binding sites.

Position-weight matrices (PWMs) are broadly used to locate transcription factor binding sites in DNA sequences. The majority of existing PWMs provide a low level of both sensitivity and specificity. We present a new computational algorithm, a modification of the Staden-Bucher approach, that improves the PWM. We applied the proposed technique on the PWM of the GC-box, binding site for Sp1. The comparison of old and new PWMs shows that the latter increase both sensitivity and specificity. The statistical parameters of GC-box distribution in promoter regions and in the human genome, as well as in each chromosome, are presented. The majority of commonly used PWMs are the 4-row mononucleotide matrices, although 16-row dinucleotide matrices are known to be more informative. The algorithm efficiently determines the 16-row matrices and preliminary results show that such matrices provide better results than 4-row matrices.

Algorithms↗

PubMed2005

Pairwise local structural alignment of RNA sequences with sequence similarity less than 40%.

MOTIVATION: Searching for non-coding RNA (ncRNA) genes and structural RNA elements (eleRNA) are major challenges in gene finding today as these often are conserved in structure rather than in sequence. Even though the number of available methods is growing, it is still of interest to pairwise detect two genes with low sequence similarity, where the genes are part of a larger genomic region. RESULTS: Here we present such an approach for pairwise local alignment which is based on foldalign and the Sankoff algorithm for simultaneous structural alignment of multiple sequences. We include the ability to conduct mutual scans of two sequences of arbitrary length while searching for common local structural motifs of some maximum length. This drastically reduces the complexity of the algorithm. The scoring scheme includes structural parameters corresponding to those available for free energy as well as for substitution matrices similar to RIBOSUM. The new foldalign implementation is tested on a dataset where the ncRNAs and eleRNAs have sequence similarity <40% and where the ncRNAs and eleRNAs are energetically indistinguishable from the surrounding genomic sequence context. The method is tested in two ways: (1) its ability to find the common structure between the genes only and (2) its ability to locate ncRNAs and eleRNAs in a genomic context. In case (1), it makes sense to compare with methods like Dynalign, and the performances are very similar, but foldalign is substantially faster. The structure prediction performance for a family is typically around 0.7 using Matthews correlation coefficient. In case (2), the algorithm is successful at locating RNA families with an average sensitivity of 0.8 and a positive predictive value of 0.9 using a BLAST-like hit selection scheme. AVAILABILITY: The program is available online at http://foldalign.kvl.dk/

Algorithms↗

PubMed2005

Making connections between novel transcription factors and their DNA motifs.

The key components of a transcriptional regulatory network are the connections between trans-acting transcription factors and cis-acting DNA-binding sites. In spite of several decades of intense research, only a fraction of the estimated approximately 300 transcription factors in Escherichia coli have been linked to some of their binding sites in the genome. In this paper, we present a computational method to connect novel transcription factors and DNA motifs in E. coli. Our method uses three types of mutually independent information, two of which are gleaned by comparative analysis of multiple genomes and the third one derived from similarities of transcription-factor-DNA-binding-site interactions. The different types of information are combined to calculate the probability of a given transcription-factor-DNA-motif pair being a true pair. Tested on a study set of transcription factors and their DNA motifs, our method has a prediction accuracy of 59% for the top predictions and 85% for the top three predictions. When applied to 99 novel transcription factors and 70 novel DNA motifs, our method predicted 64 transcription-factor-DNA-motif pairs. Supporting evidence for some of the predicted pairs is presented. Functional annotations are made for 23 novel transcription factors based on the predicted transcription-factor-DNA-motif connections.

Algorithms↗

PubMed2005

PolyMAPr: programs for polymorphism database mining, annotation, and functional analysis.

Pharmacogenomic and disease-association studies rely on identifying a comprehensive set of polymorphisms within candidate genes. Public SNP databases are a rich source of polymorphism data, but mining them effectively requires overcoming at least four challenges: ensuring accurate annotations for genes and polymorphisms, eliminating both inter- and intra-database redundancy, integrating data from multiple public sources with data generated locally, and prioritizing the variants for further study. PolyMAPr (Polymorphism Mining and Annotation Programs)' was developed to overcome these challenges and to improve the efficiency of database mining and polymorphism annotation. PolyMAPr takes as input a file containing a list of genes to be processed and files containing each annotated gene sequence. Polymorphic sequences obtained from public databases (dbSNP, CGAP, and JSNP) or through local SNP discovery efforts, as well as oligonucleotide sequences (e.g., PCR primers), are mapped to the annotated gene sequences and named according to suggested nomenclature guidelines. The functional effects of nonsynonymous coding-region SNPs (cSNPs) and any variants that might alter exon splicing enhancer (ESE) sites, putative transcription factor binding sites, or intron-exon splice sites are predicted. The output files are accessible though a browser interface. In addition, the results are also provided in Extensible Markup Language (XML) format to facilitate uploading them into a local relational database. PolyMAPr increases the efficiency of mining public databases for genetic variants within candidate genes and provides a mechanism by which data from multiple sources (both public and private) can be uniformly integrated, thereby significantly reducing the effort required to obtain a comprehensive set of polymorphisms for pharmacogenomic and disease-association studies. PolyMAPr can be obtained from http://pharmacogenomics.wustl.edu.

Databases, Nucleic Acid↗

PubMed2005

Editing efficiency of a Drosophila gene correlates with a distant splice site selection.

RNA editing and alternative splicing are two processes that increase protein diversity. The relationship between the two processes is not well understood. There are a few examples of correlations between editing and alternative splicing, but these are all nearby effects. A search for alternative splicing among 16 edited genes in Drosophila reveals two novel instances of alternative splicing. In one example where alternative splicing occurs downstream of editing, a strong correlation between editing efficiency and splice site selection is observed. In contrast, when editing occurs downstream of alternative splicing, no correlation is seen. These results suggest some models for the coupling of editing and splicing processes.

Alternative Splicing↗

PubMed2004

Procom: a web-based tool to compare multiple eukaryotic proteomes.

UNLABELLED: Each organism has traits that are shared with some, but not all, organisms. Identification of genes needed for a particular trait can be accomplished by a comparative genomics approach using three or more organisms. Genes that occur in organisms without the trait are removed from the set of genes in common among organisms with the trait. To facilitate these comparisons, a web-based server, Procom, was developed to identify the subset of genes that may be needed for a trait. AVAILABILITY: The Procom program is freely available with documentation and examples at http://ural.wustl.edu/~billy/Procom/ CONTACT: billy@ural.wustl.edu.

Animals↗

PubMed2004

The neuropeptide pigment-dispersing factor coordinates pacemaker interactions in the Drosophila circadian system.

In Drosophila, the neuropeptide pigment-dispersing factor (PDF) is required to maintain behavioral rhythms under constant conditions. To understand how PDF exerts its influence, we performed time-series immunostainings for the PERIOD protein in normal and pdf mutant flies over 9 d of constant conditions. Without pdf, pacemaker neurons that normally express PDF maintained two markers of rhythms: that of PERIOD nuclear translocation and its protein staining intensity. As a group, however, they displayed a gradual dispersion in their phasing of nuclear translocation. A separate group of non-PDF circadian pacemakers also maintained PERIOD nuclear translocation rhythms without pdf but exhibited altered phase and amplitude of PERIOD staining intensity. Therefore, pdf is not required to maintain circadian protein oscillations under constant conditions; however, it is required to coordinate the phase and amplitude of such rhythms among the diverse pacemakers. These observations begin to outline the hierarchy of circadian pacemaker circuitry in the Drosophila brain.

Animals↗

PubMed2004

Quantitative modeling of DNA-protein interactions: effects of amino acid substitutions on binding specificity of the Mnt repressor.

Understanding DNA-protein recognition quantitatively is essential to developing computational algorithms for accurate transcriptional binding site prediction. Using a quantitative, multiple fluorescence, relative affinity (QuMFRA) assay, we determine the binding specificity of 11 different position 6 variants of the Mnt repressor for operators containing all 16 possible dinucleotides at operator positions 16 and 17. We show that the wild-type and all variant proteins interact with the two positions in a non-independent manner, but that a simple independent model provides a close approximation to the true binding affinities. The wild-type His at amino acid 6 is the only protein to prefer the AC sequence of the wild-type operator, whereas most of the variant proteins prefer TA. H6R is unique in having a strong preference for C at position 16. A comparison of the quantitative binding data for all of the protein variants with a model for recognition of the early growth response (EGR) zinc finger family suggests that interactions of Mnt with positions 16 and 17 are similar to interactions of EGR with positions 1 and 2, respectively. This information leads to an augmented model for the interaction of Mnt with its operator.

Amino Acid Substitution↗

PubMed2004

ILM: a web server for predicting RNA secondary structures with pseudoknots.

The ILM web server provides a web interface to two algorithms, iterated loop matching and maximum weighted matching, for efficiently predicting RNA secondary structures with pseudoknots. The algorithms can utilize either thermodynamic or comparative information or both, and thus can work on both aligned and individual sequences. Predicted secondary structures are presented in several formats compatible with a variety of existing visualization tools. The service can be accessed at http://cic.cs.wustl.edu/RNA/.

Algorithms↗

PubMed2004

Comparative genomics identifies a flagellar and basal body proteome that includes the BBS5 human disease gene.

Cilia and flagella are microtubule-based structures nucleated by modified centrioles termed basal bodies. These biochemically complex organelles have more than 250 and 150 polypeptides, respectively. To identify the proteins involved in ciliary and basal body biogenesis and function, we undertook a comparative genomics approach that subtracted the nonflagellated proteome of Arabidopsis from the shared proteome of the ciliated/flagellated organisms Chlamydomonas and human. We identified 688 genes that are present exclusively in organisms with flagella and basal bodies and validated these data through a series of in silico, in vitro, and in vivo studies. We then applied this resource to the study of human ciliation disorders and have identified BBS5, a novel gene for Bardet-Biedl syndrome. We show that this novel protein localizes to basal bodies in mouse and C. elegans, is under the regulatory control of daf-19, and is necessary for the generation of both cilia and flagella.

Animals↗

PubMed2004

RNA interference of achaete-scute homolog 1 in mouse prostate neuroendocrine cells reveals its gene targets and DNA binding sites.

We have previously characterized a transgenic mouse model (CR2-TAg) of metastatic prostate cancer arising in the neuroendocrine (NE) cell lineage. Biomarkers of NE differentiation in this model are expressed in conventional adenocarcinoma of the prostate with NE features. To further characterize the pathways that control NE proliferation, differentiation, and survival, we established prostate NE cancer (PNEC) cell lines from CR2-TAg prostate tumors and metastases. GeneChip analyses of cell lines harvested at different passages, and as xenografted tumors, indicated that PNECs express consistent features ex vivo and in vivo and share a remarkable degree of similarity with primary CR2-TAg prostate NE tumors. PNECs express mAsh1, a basic helix-loop-helix (bHLH) transcription factor essential for NE cell differentiation in other tissues. RNA interference knockdown of mAsh1, GeneChip comparisons of treated and control cell populations, and a computational analysis of down-regulated genes identified 12 transcriptional motifs enriched in the gene set. Affected genes, including Adcy9, Hes6, Iapp1, Ndrg4, c-Myb, and Mesdc2, are enriched for a palindromic E-box motif, CAGCTG, indicating that it is a physiologically relevant mAsh1 binding site. The enrichment of a c-Myb binding site and the finding that c-Myb is down-regulated by mAsh1 RNA interference suggest that mAsh1 and c-Myb are in the same signaling pathway. Our data indicate that mAsh1 negatively regulates the cell cycle (e.g., via enhanced Cdkn2d, Bub1 expression), promotes differentiation (e.g., through effects on cAMP), and enhances survival by inhibiting apoptosis. PNEC cell lines should be generally useful for genetic and/or pharmacologic studies of the regulation of NE cell proliferation, differentiation, and tumorigenesis.

Animals↗

PubMed2004

A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences.

MOTIVATION: RNA structure motifs contained in mRNAs have been found to play important roles in regulating gene expression. However, identification of novel RNA regulatory motifs using computational methods has not been widely explored. Effective tools for predicting novel RNA regulatory motifs based on genomic sequences are needed. RESULTS: We present a new method for predicting common RNA secondary structure motifs in a set of functionally or evolutionarily related RNA sequences. This method is based on comparison of stems (palindromic helices) between sequences and is implemented by applying graph-theoretical approaches. It first finds all possible stable stems in each sequence and compares stems pairwise between sequences by some defined features to find stems conserved across any two sequences. Then by applying a maximum clique finding algorithm, it finds all significant stems conserved across at least k sequences. Finally, it assembles in topological order all possible compatible conserved stems shared by at least k sequences and reports a number of the best assembled stem sets as the best candidate common structure motifs. This method does not require prior structural alignment of the sequences and is able to detect pseudoknot structures. We have tested this approach on some RNA sequences with known secondary structures, in which it is capable of detecting the real structures completely or partially correctly and outperforms other existing programs for similar purposes. AVAILABILITY: The algorithm has been implemented in C++ in a program called comRNA, which is available at http://ural.wustl.edu/softwares.html

Algorithms↗