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Gary D Stormo

Publications and source records attributed to Gary D Stormo.

At least 37 records · Page 2Linked to original sources
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↗
PubMed2004

Training the next generation of informaticians: the impact of "BISTI" and bioinformatics--a report from the American College of Medical Informatics.

In 2002-2003, the American College of Medical Informatics (ACMI) undertook a study of the future of informatics training. This project capitalized on the rapidly expanding interest in the role of computation in basic biological research, well characterized in the National Institutes of Health (NIH) Biomedical Information Science and Technology Initiative (BISTI) report. The defining activity of the project was the three-day 2002 Annual Symposium of the College. A committee, comprised of the authors of this report, subsequently carried out activities, including interviews with a broader informatics and biological sciences constituency, collation and categorization of observations, and generation of recommendations. The committee viewed biomedical informatics as an interdisciplinary field, combining basic informational and computational sciences with application domains, including health care, biological research, and education. Consequently, effective training in informatics, viewed from a national perspective, should encompass four key elements: (1). curricula that integrate experiences in the computational sciences and application domains rather than just concatenating them; (2). diversity among trainees, with individualized, interdisciplinary cross-training allowing each trainee to develop key competencies that he or she does not initially possess; (3). direct immersion in research and development activities; and (4). exposure across the wide range of basic informational and computational sciences. Informatics training programs that implement these features, irrespective of their funding sources, will meet and exceed the challenges raised by the BISTI report, and optimally prepare their trainees for careers in a field that continues to evolve.

Computational Biology↗
PubMed2004

An iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots.

MOTIVATION: Pseudoknots have generally been excluded from the prediction of RNA secondary structures due to its difficulty in modeling. Although, several dynamic programming algorithms exist for the prediction of pseudoknots using thermodynamic approaches, they are neither reliable nor efficient. On the other hand, comparative methods are more reliable, but are often done in an ad hoc manner and require expert intervention. Maximum weighted matching, an algorithm for pseudoknot prediction with comparative analysis, suffers from low-prediction accuracy in many cases. RESULTS: Here we present an algorithm, iterated loop matching, for reliably and efficiently predicting RNA secondary structures including pseudoknots. The method can utilize either thermodynamic or comparative information or both, thus is able to predict pseudoknots for both aligned and individual sequences. We have tested the algorithm on a number of RNA families. Using 8-12 homologous sequences, the algorithm correctly identifies more than 90% of base-pairs for short sequences and 80% overall. It correctly predicts nearly all pseudoknots and produces very few spurious base-pairs for sequences without pseudoknots. Comparisons show that our algorithm is both more sensitive and more specific than the maximum weighted matching method. In addition, our algorithm has high-prediction accuracy on individual sequences, comparable with the PKNOTS algorithm, while using much less computational resources. AVAILABILITY: The program has been implemented in ANSI C and is freely available for academic use at http://www.cse.wustl.edu/~zhang/projects/rna/ilm/ SUPPLEMENTARY INFORMATION: http://www.cse.wustl.edu/~zhang/projects/rna/ilm/

Algorithms↗
PubMed2004

PromoLign: a database for upstream region analysis and SNPs.

The study of transcriptional regulation at the genomic level has been hindered by the lack of functional annotation in the putative regulatory regions. Phylogenetic footprinting, in which cross-species sequence alignment among orthologous genes is applied to locate conserved sequence blocks, is an effective strategy to attack this problem. Single nucleotide polymorphisms (SNPs) in transcription factor (TF) binding sites contribute to the heterogeneity of TF binding sites and might disrupt or enhance their regulatory activity. The correlation of SNPs with the TF sites will not only help in functional evaluation of SNPs, but will also help in the study of transcription regulation by focusing attention on specific TF sites. PromoLign (http://polly.wustl.edu/promolign/main.html) is an online database application that presents SNPs and TF binding profiles in the context of human-mouse orthologous sequence alignment with a hyperlinked graphical interface. PromoLign could be applied to a variety of SNPs and transcription related studies, including association genetics, population genetics, and pharmacogenetics.

Animals↗
PubMed2004

Expression profiling using random genomic DNA microarrays identifies differentially expressed genes associated with three major developmental stages of the protozoan parasite Leishmania major.

To complete its life cycle, protozoan parasites of the genus Leishmania undergo at least three major developmental transitions. However, previous efforts to identify genes showing stage regulated changes in transcript abundance have yielded relatively few. Here we used expression profiling to assess changes in transcript abundance in three stages: replicating promastigotes and infective non-replicating metacyclics, which occur in the sand fly vector, and in the amastigote stage residing with macrophage phagolysosomes in mammals. Microarrays were developed containing 11,484 PCR products that included a number of known genes and 10,464 random 1 kb genomic DNA fragments. Arrays were hybridized in triplicate and genes showing two-fold or greater changes in 2/3 experiments were scored as differentially expressed. Remarkably, only about one percent of the DNAs expression varied by this criteria, in either stage comparison. Northern blot analysis confirmed the predicted change in mRNA abundance for most of these (68%). This set of genes included most of those previously identified in the literature as differentially regulated as well as a number of novel genes. Notably, Leishmania maxicircle transcripts showed strong up-regulation in metacyclic and amastigote parasites, probably associated with changes in parasite energy metabolism. However, current data suggest that expression profiling using shotgun DNA libraries significantly underestimates the extent of regulated transcripts.

Animals↗
PubMed2004

Novel transcription regulatory elements in Caenorhabditis elegans muscle genes.

We report the identification of three new transcription regulatory elements that are associated with muscle gene expression in the nematode Caenorhabditis elegans. Starting from a subset of well-characterized nematode muscle genes, we identified conserved DNA motifs in the promoter regions using computational DNA pattern-recognition algorithms. These were considered to be putative muscle transcription regulatory motifs. Using the green-fluorescent protein (GFP) as a reporter, experiments were done to determine the biological activity of these motifs in driving muscle gene expression. Prediction accuracy of muscle expression based on the presence of these three motifs was encouraging; nine of 10 previously uncharacterized genes that were predicted to have muscle expression were shown to be expressed either specifically or selectively in the muscle tissues, whereas only one of the nine that scored low for these motifs expressed in muscle. Knockouts of putative regulatory elements in the promoter of the mlc-2 and unc-89 genes show that they significantly contribute to muscle expression and act in a synergistic manner. We find that these DNA motifs are also present in the muscle promoters of C. briggsae, indicating that they are functionally conserved in the nematodes.

Animals↗
PubMed2003

Combining phylogenetic data with co-regulated genes to identify regulatory motifs.

MOTIVATION: Discovery of regulatory motifs in unaligned DNA sequences remains a fundamental problem in computational biology. Two categories of algorithms have been developed to identify common motifs from a set of DNA sequences. The first can be called a 'multiple genes, single species' approach. It proposes that a degenerate motif is embedded in some or all of the otherwise unrelated input sequences and tries to describe a consensus motif and identify its occurrences. It is often used for co-regulated genes identified through experimental approaches. The second approach can be called 'single gene, multiple species'. It requires orthologous input sequences and tries to identify unusually well conserved regions by phylogenetic footprinting. Both approaches perform well, but each has some limitations. It is tempting to combine the knowledge of co-regulation among different genes and conservation among orthologous genes to improve our ability to identify motifs. RESULTS: Based on the Consensus algorithm previously established by our group, we introduce a new algorithm called PhyloCon (Phylogenetic Consensus) that takes into account both conservation among orthologous genes and co-regulation of genes within a species. This algorithm first aligns conserved regions of orthologous sequences into multiple sequence alignments, or profiles, then compares profiles representing non-orthologous sequences. Motifs emerge as common regions in these profiles. Here we present a novel statistic to compare profiles of DNA sequences and a greedy approach to search for common subprofiles. We demonstrate that PhyloCon performs well on both synthetic and biological data. AVAILABILITY: Software available upon request from the authors. http://ural.wustl.edu/softwares.html

Algorithms↗
PubMed2003

Computational identification of the Spo0A-phosphate regulon that is essential for the cellular differentiation and development in Gram-positive spore-forming bacteria.

Spo0A-phosphate is essential for the initiation of cellular differentiation and developmental processes in Gram-positive spore-forming bacteria. Here we combined comparative genomics with analyses of microarray expression profiles to identify the Spo0A-phosphate regulon in Bacillus subtilis. The consensus Spo0A-phosphate DNA-binding motif identified from the training set based on different computational algorithms is an 8 bp sequence, TTGTCGAA. The same motif was identified by aligning the upstream regulatory sequences of spo0A-dependent genes obtained from the expression profile of Sad67 (a constitutively active form of Spo0A) and their orthologs. After the transcription units (TUs) having putative Spo0A-phosphate binding sites were obtained, conservation of regulons among the genomes of B.subtilis, Bacillus halodurans and Bacillus anthracis, and expression profiles were employed to identify the most confident predictions. Besides genes already known to be directly under the control of Spo0A-phosphate, 276 novel members (organized in 109 TUs) of the Spo0A-phosphate regulon in B.subtilis are predicted in this study. The sensitivity and specificity of our predictions are estimated based on known sites and combinations of different types of evidence. Further characterization of the novel candidates will provide information towards understanding the role of Spo0A-phosphate in the sporulation process, as well as the entire genetic network governing cellular differentiation and developmental processes in B.subtilis.

Algorithms↗
PubMed2003

New tricks for an old dogma: riboswitches as cis-only regulatory systems.

Riboswitches are mRNAs that can act as direct sensors of small molecules to control their own expression. In the May 30, 2003, issue of Cell, Mandal et al. show that cis elements in mRNAs involved in purine metabolism measure the effector molecule concentration with sensitivity and specificity, and control expression of adjacent genes. Analysis of several recently discovered riboswitches suggests that this may be a common, efficient mechanism for regulating the synthesis of proteins required for the production of important metabolites.

5' Untranslated Regions↗
PubMed2002

Specificity of Mnt 'master residue' obtained from in vivo and in vitro selections.

Mnt is a repressor from phage P22 that belongs to the ribbon-helix-helix family of DNA binding factors. Four amino acids from the N-terminus of the protein, Arg2, His6, Asn8 and Arg10, interact with the base pairs of the DNA to provide the sequence specificity. Raumann et al. (Nature Struct. Biol., 2, 1115-1122) identified position 6 as a 'master residue' that controls the specificity of the protein. Models for the interaction have residue 6 of Mnt interacting directly with position 5 of the operator. In vivo selections demonstrated that protein variants at residue 6 bound specifically to operator mutations at that position. Operators in which the wild-type G at position 5 was replaced by T specifically bound to several different protein variants, primarily hydrophobic residues. The obtained protein variants, plus some others, were used in in vitro selections to determine their preferred binding sites. The results showed that the residue at position 6 influenced the preference for binding site bases predominantly at position 5, but that the effects of altering it can extend over longer distances, consistent with its designation as a 'master residue'. The similarities of binding sites for different residues do not correlate strongly with common measures of amino acid similarities.

Base Sequence↗
PubMed2002

Probabilistic code for DNA recognition by proteins of the EGR family.

A recognition code for protein-DNA interactions would allow for the prediction of binding sites based on protein sequence, and the identification of binding proteins for specific DNA targets. Crystallographic studies of protein-DNA complexes showed that a simple, deterministic recognition code does not exist. Here, we present a probabilistic recognition code (P-code) that assigns energies to all possible base-pair-amino acid interactions for the early growth response factor (EGR) family of zinc-finger transcription factors. The specific energy values are determined by a maximum likelihood method using examples from in vitro randomisation experiments (namely, SELEX and phage display) reported in the literature. The accuracy of the model is tested in several ways, including the ability to predict in vivo binding sites of EGR proteins and other non-EGR zinc-finger proteins, and the correlation between predicted and measured binding affinities of various EGR proteins to several different DNA sites. We also show that this model improves significantly upon the prediction capabilities of previous qualitative and quantitative models. The probabilistic code we develop uses information about the interacting positions between the protein and DNA, but we show that such information is not necessary, although it reduces the number of parameters to be determined. We also employ the assumption that the total binding energy is the sum of the energies of the individual contacts, but we describe how that assumption can be relaxed at the cost of additional parameters.

Algorithms↗
PubMed2002

Additivity in protein-DNA interactions: how good an approximation is it?

Man and Stormo and Bulyk et al. recently presented their results on the study of the DNA binding affinity of proteins. In both of these studies the main conclusion is that the additivity assumption, usually applied in methods to search for binding sites, is not true. In the first study, the analysis of binding affinity data from the Mnt repressor protein bound to all possible DNA (sub)targets at positions 16 and 17 of the binding site, showed that those positions are not independent. In the second study, the authors analysed DNA binding affinity data of the wild-type mouse EGR1 protein and four variants differing on the middle finger. The binding affinity of these proteins was measured to all 64 possible trinucleotide (sub)targets of the middle finger using microarray technology. The analysis of the measurements also showed interdependence among the positions in the DNA target. In the present report, we review the data of both studies and we re- analyse them using various statistical methods, including a comparison with a multiple regression approach. We conclude that despite the fact that the additivity assumption does not fit the data perfectly, in most cases it provides a very good approximation of the true nature of the specific protein-DNA interactions. Therefore, additive models can be very useful for the discovery and prediction of binding sites in genomic DNA.

Animals↗
PubMed2002

Influence of the period-dependent circadian clock on diurnal, circadian, and aperiodic gene expression in Drosophila melanogaster.

We measured daily gene expression in heads of control and period mutant Drosophila by using oligonucleotide microarrays. In control flies, 72 genes showed diurnal rhythms in light-dark cycles; 22 of these also oscillated in free-running conditions. The period gene significantly influenced the expression levels of over 600 nonoscillating transcripts. Expression levels of several hundred genes also differed significantly between control flies kept in light-dark versus constant darkness but differed minimally between per(01) flies kept in the same two conditions. Thus, the period-dependent circadian clock regulates only a limited set of rhythmically expressed transcripts. Unexpectedly, period regulates basal and light-regulated gene expression to a very broad extent.

Animals↗
PubMed2002

Putting the Leishmania genome to work: functional genomics by transposon trapping and expression profiling.

Leishmania are important protozoan pathogens of humans in temperate and tropical regions. The study of gene expression during the infectious cycle, in mutants or after environmental or chemical stimuli, is a powerful approach towards understanding parasite virulence and the development of control measures. Like other trypanosomatids, Leishmania gene expression is mediated by a polycistronic transcriptional process that places increased emphasis on post-transcriptional regulatory mechanisms including RNA processing and protein translation. With the impending completion of the Leishmania genome, global approaches surveying mRNA and protein expression are now feasible. Our laboratory has developed the Drosophila transposon mariner as a tool for trapping Leishmania genes and studying their regulation in the form of protein fusions; a classic approach in other microbes that can be termed 'proteogenomics'. Similarly, we have developed reagents and approaches for the creation of DNA microarrays, which permit the measurement of RNA abundance across the parasite genome. Progress in these areas promises to greatly increase our understanding of global mechanisms of gene regulation at both mRNA and protein levels, and to lead to the identification of many candidate genes involved in virulence.

Animals↗