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Wyeth W Wasserman

Publications and source records attributed to Wyeth W Wasserman.

At least 19 recordsLinked to original sources
PubMed2025

The cost and cost trajectory of genome sequencing and bioinformatics analysis for Indigenous children with suspected rare diseases.

PURPOSE: Indigenous peoples are underrepresented in reference genome libraries. Consequently, rare disease diagnosis may require bespoke bioinformatics analyses of genome sequences. Establishing diagnostic cost is crucial to support policy development for equitable diagnosis of rare diseases. We estimated the cost and cost trajectory of diagnostic genome sequencing and bioinformatics for Indigenous participants with suspected rare diseases. METHODS: We conducted a microcosting study of Indigenous children and their families receiving genome sequencing through Canada's Silent Genomes Project. Invoice data informed the costs of genome sequencing. We conducted a time-and-motion study for bioinformatics analyses, including labor, computing, and data storage costs. RESULTS: With standard bioinformatics, costs ranged from C$3645 (SD: 455) for singletons to C$7402 (SD: 566) for trios. With advanced, bespoke bioinformatics, costs ranged from C$5344 (SD: 634) for singletons to C$9760 (SD: 822) for trios. Genome sequencing was a primary cost driver; however, sequencing costs decreased by 61% over 4 years. Bioinformatics costs ranged from 21.3% to 58.3% of the total costs. The time required for bioinformatics ranged from 71 hours to 215 hours for standard and advanced analyses, respectively. CONCLUSION: Genome sequencing costs decreased over time. Bioinformatics is a significant cost driver, particularly for bespoke analyses arising from nonrepresentative reference libraries.

Humans↗
PubMed2005

oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes.

Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes.

Algorithms↗
PubMed2005

Complete functional rescue of the ABCA1-/- mouse by human BAC transgenesis.

Humanized mouse models are useful tools to explore the functional and regulatory differences between human and murine orthologous genes. We have combined a bioinformatics approach and an in vivo approach to assess the functional and regulatory differences between the human and mouse ABCA1 genes. Computational analysis identified significant differences in potential regulatory sites between the human and mouse genes. The effect of these differences was assessed in vivo, using a bacterial artificial chromosome transgenic humanized ABCA1 mouse model that expresses the human gene in the absence of mouse ABCA1. Humanized mice expressed human ABCA1 protein at levels similar to wild-type mice and fully compensated for cholesterol efflux activity and lipid levels seen in ABCA1-deficient mice. Liver X receptor agonist administration resulted in significant increases in HDL values associated with parallel increases in the hepatic ABCA1 protein and mRNA levels in the humanized ABCA1 mice, as seen in the wild-type animals. Our studies indicate that despite differences in potential regulatory regions, the human ABCA1 gene is able to functionally fully compensate for the mouse gene. Our humanized ABCA1 mice can serve as a useful model system for functional analysis of the human ABCA1 gene in vivo and can be used for the generation of potential new therapeutics that target HDL metabolism.

ATP Binding Cassette Transporter 1↗
PubMed2005

Identification of functional SNPs in the 5-prime flanking sequences of human genes.

BACKGROUND: Over 4 million single nucleotide polymorphisms (SNPs) are currently reported to exist within the human genome. Only a small fraction of these SNPs alter gene function or expression, and therefore might be associated with a cell phenotype. These functional SNPs are consequently important in understanding human health. Information related to functional SNPs in candidate disease genes is critical for cost effective genetic association studies, which attempt to understand the genetics of complex diseases like diabetes, Alzheimer's, etc. Robust methods for the identification of functional SNPs are therefore crucial. We report one such experimental approach. RESULTS: Sequence conserved between mouse and human genomes, within 5 kilobases of the 5-prime end of 176 GPCR genes, were screened for SNPs. Sequences flanking these SNPs were scored for transcription factor binding sites. Allelic pairs resulting in a significant score difference were predicted to influence the binding of transcription factors (TFs). Ten such SNPs were selected for mobility shift assays (EMSA), resulting in 7 of them exhibiting a reproducible shift. The full-length promoter regions with 4 of the 7 SNPs were cloned in a Luciferase based plasmid reporter system. Two out of the 4 SNPs exhibited differential promoter activity in several human cell lines. CONCLUSIONS: We propose a method for effective selection of functional, regulatory SNPs that are located in evolutionary conserved 5-prime flanking regions (5'-FR) regions of human genes and influence the activity of the transcriptional regulatory region. Some SNPs behave differently in different cell types.

Algorithms↗
PubMed2004

Arrays of ultraconserved non-coding regions span the loci of key developmental genes in vertebrate genomes.

BACKGROUND: Evolutionarily conserved sequences within or adjoining orthologous genes often serve as critical cis-regulatory regions. Recent studies have identified long, non-coding genomic regions that are perfectly conserved between human and mouse, termed ultra-conserved regions (UCRs). Here, we focus on UCRs that cluster around genes involved in early vertebrate development; genes conserved over 450 million years of vertebrate evolution. RESULTS: Based on a high resolution detection procedure, our UCR set enables novel insights into vertebrate genome organization and regulation of developmentally important genes. We find that the genomic positions of deeply conserved UCRs are strongly associated with the locations of genes encoding key regulators of development, with particularly strong positional correlation to transcription factor-encoding genes. Of particular importance is the observation that most UCRs are clustered into arrays that span hundreds of kilobases around their presumptive target genes. Such a hallmark signature is present around several uncharacterized human genes predicted to encode developmentally important DNA-binding proteins. CONCLUSION: The genomic organization of UCRs, combined with previous findings, suggests that UCRs act as essential long-range modulators of gene expression. The exceptional sequence conservation and clustered structure suggests that UCR-mediated molecular events involve greater complexity than traditional DNA binding by transcription factors. The high-resolution UCR collection presented here provides a wealth of target sequences for future experimental studies to determine the nature of the biochemical mechanisms involved in the preservation of arrays of nearly identical non-coding sequences over the course of vertebrate evolution.

Animals↗
PubMed2004

Prediction of nuclear hormone receptor response elements.

The nuclear receptor (NR) class of transcription factors controls critical regulatory events in key developmental processes, homeostasis maintenance, and medically important diseases and conditions. Identification of the members of a regulon controlled by a NR could provide an accelerated understanding of development and disease. New bioinformatics methods for the analysis of regulatory sequences are required to address the complex properties associated with known regulatory elements targeted by the receptors because the standard methods for binding site prediction fail to reflect the diverse target site configurations. We have constructed a flexible Hidden Markov Model framework capable of predicting NHR binding sites. The model allows for variable spacing and orientation of half-sites. In a genome-scale analysis enabled by the model, we show that NRs in Fugu rubripes have a significant cross-regulatory potential. The model is implemented in a web interface, freely available for academic researchers, available at http://mordor.cgb.ki.se/NHR-scan.

Algorithms↗
PubMed2004

ConSite: web-based prediction of regulatory elements using cross-species comparison.

ConSite is a user-friendly, web-based tool for finding cis-regulatory elements in genomic sequences. Predictions are based on the integration of binding site prediction generated with high-quality transcription factor models and cross-species comparison filtering (phylogenetic footprinting). By incorporating evolutionary constraints, selectivity is increased by an order of magnitude as compared to single-sequence analysis. ConSite offers several unique features, including an interactive expert system for retrieving orthologous regulatory sequences. Programming modules and biological databases that form the foundation of the ConSite service are freely available to the research community. ConSite is available at http:/www.phylofoot.org/consite.

Animals↗
PubMed2004

MSCAN: identification of functional clusters of transcription factor binding sites.

Identification of functional transcription factor binding sites in genomic sequences is notoriously difficult. The critical problem is the low specificity of predictions, which directly reflects the low target specificity of DNA binding proteins. To overcome the noise produced in predictions of individual binding sites, a new generation of algorithms achieves better predictive specificity by focusing on locally dense clusters of binding sites. MSCAN is a leading method for binding site cluster detection that determines the significance of observed sites while correcting for local compositional bias of sequences. The algorithm is highly flexible, applying any set of input binding models to the analysis of a user-specified sequence. From the user's perspective, a key feature of the system is that no reference data sets of regulatory sequences from co-regulated genes are required to train the algorithm. The output from MSCAN consists of an ordered list of sequence segments that contain potential regulatory modules. We have chosen the features in MSCAN such that sequence and matrix retrieval is highly facilitated, resulting in a web server that is intuitive to use. MSCAN is available at http://mscan.cgb.ki.se/cgi-bin/MSCAN.

Algorithms↗
PubMed2004

Constrained binding site diversity within families of transcription factors enhances pattern discovery bioinformatics.

Diverse computational and experimental efforts are required to elucidate the control circuitry regulating the transcription of human genes. The fusion of gene-specific promoter analyses with large microarray studies and bioinformatics advances has produced optimism that significant progress can be made in unravelling this complex network. Within bioinformatics, past emphasis for improved pattern discovery has been placed upon "phylogenetic footprinting", the identification of sequences conserved over moderate periods of evolution (e.g. human and mouse comparisons). We introduce a new direction in bioinformatics based on the constraints imposed by the structures of DNA-binding proteins. For most structurally related families of transcription factors, there are clear similarities in the sequences of the sites to which they bind. On the basis of this observation, we construct familial binding profiles for well-characterized transcription factor families. The profiles are shown to classify correctly the structural class of mediating transcription factors for novel motifs in 88% of cases. By incorporating the familial profiles into pattern discovery procedures, we demonstrate that functional binding sites can be found in genomic sequences of dramatically greater length than is possible otherwise. Thus, incorporating familial models can overcome the signal-to-noise challenge that has hindered the transition from microarray data to regulatory control sequences for human genes. Biochemically motivated constraints upon sequence diversity of binding sites will complement the genetically motivated constraints imposed in "phylogenetic footprinting" algorithms.

Algorithms↗
PubMed2004

JASPAR: an open-access database for eukaryotic transcription factor binding profiles.

The analysis of regulatory regions in genome sequences is strongly based on the detection of potential transcription factor binding sites. The preferred models for representation of transcription factor binding specificity have been termed position-specific scoring matrices. JASPAR is an open-access database of annotated, high-quality, matrix-based transcription factor binding site profiles for multicellular eukaryotes. The profiles were derived exclusively from sets of nucleotide sequences experimentally demonstrated to bind transcription factors. The database is complemented by a web interface for browsing, searching and subset selection, an online sequence analysis utility and a suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. JASPAR is available at http://jaspar. cgb.ki.se.

Animals↗
PubMed2004

Regulog analysis: detection of conserved regulatory networks across bacteria: application to Staphylococcus aureus.

A transcriptional regulatory network encompasses sets of genes (regulons) whose expression states are directly altered in response to an activating signal, mediated by trans-acting regulatory proteins and cis-acting regulatory sequences. Enumeration of these network components is an essential step toward the creation of a framework for systems-based analysis of biological processes. Profile-based methods for the detection of cis-regulatory elements are often applied to predict regulon members, but they suffer from poor specificity. In this report we describe Regulogger, a novel computational method that uses comparative genomics to eliminate spurious members of predicted gene regulons. Regulogger produces regulogs, sets of coregulated genes for which the regulatory sequence has been conserved across multiple organisms. The quantitative method assigns a confidence score to each predicted regulog member on the basis of the degree of conservation of protein sequence and regulatory mechanisms. When applied to a reference collection of regulons from Escherichia coli, Regulogger increased the specificity of predictions up to 25-fold over methods that use cis-element detection in isolation. The enhanced specificity was observed across a wide range of biologically meaningful parameter combinations, indicating a robust and broad utility for the method. The power of computational pattern discovery methods coupled with Regulogger to unravel transcriptional networks was demonstrated in an analysis of the genome of Staphylococcus aureus. A total of 125 regulogs were found in this organism, including both well-defined functional groups and a subset with unknown functions.

Bacillus subtilis↗
PubMed2004

Decoding human regulatory circuits.

Clusters of transcription factor binding sites (TFBSs) which direct gene expression constitute cis-regulatory modules (CRMs). We present a novel algorithm, based on Gibbs sampling, which locates, de novo, the cis features of these CRMs, their component TFBSs, and the properties of their spatial distribution. The algorithm finds 69% of experimentally reported TFBSs and 85% of the CRMs in a reference data set of regions upstream of genes differentially expressed in skeletal muscle cells. A discriminant procedure based on the output of the model specifically discriminated regulatory sequences in muscle-specific genes in an independent test set. Application of the method to the analysis of 2710 10-kb fragments upstream of annotated human genes identified 17 novel candidate modules with a false discovery rate </=0.05, demonstrating the applicability of the method to genome-scale data.

Algorithms↗
PubMed2003

Integrated analysis of yeast regulatory sequences for biologically linked clusters of genes.

Dramatic progress in deciphering the regulatory controls in Saccharomyces cerevisiae has been enabled by the fusion of high-throughput genomics technologies with advanced sequence analysis algorithms. Sets of genes likely to function together and with similar expression profiles have been identified in diverse studies. By fusing an advanced pattern recognition algorithm for identification of transcription factor binding sites with a new method for the quantitative comparison of binding properties of transcription factors, we provide an integrated means to move from expression data to biological insights. The Yeast Regulatory Sequence Analysis system, YRSA, combines standard functions with a novel pattern characterization procedure in an intuitive interface designed for use by a broad range of scientists. The features of the system include automated retrieval of user-defined promoter sequences, binding site discovery by pattern recognition, graphical displays of the observed pattern and positions of similar sequences in the specified genes, and comparison of the new pattern against a collection of binding patterns for characterized transcription factors. The comprehensive YRSA system was used to study the regulatory mechanisms of yeast regulons. Analysis of the regulatory controls of a battery of genes induced by DNA damaging agents supports a putative mediating role for the cell-cycle checkpoint regulatory element MCB. YRSA is available at http://yrsa.cgb.ki.se. [YRSA: ancient Scandinavian name meaning old she-bear (Latin Ursus arctos = brown bear/grizzly).]

Algorithms↗
PubMed2003

Identification of conserved regulatory elements by comparative genome analysis.

BACKGROUND: For genes that have been successfully delineated within the human genome sequence, most regulatory sequences remain to be elucidated. The annotation and interpretation process requires additional data resources and significant improvements in computational methods for the detection of regulatory regions. One approach of growing popularity is based on the preferential conservation of functional sequences over the course of evolution by selective pressure, termed 'phylogenetic footprinting'. Mutations are more likely to be disruptive if they appear in functional sites, resulting in a measurable difference in evolution rates between functional and non-functional genomic segments. RESULTS: We have devised a flexible suite of methods for the identification and visualization of conserved transcription-factor-binding sites. The system reports those putative transcription-factor-binding sites that are both situated in conserved regions and located as pairs of sites in equivalent positions in alignments between two orthologous sequences. An underlying collection of metazoan transcription-factor-binding profiles was assembled to facilitate the study. This approach results in a significant improvement in the detection of transcription-factor-binding sites because of an increased signal-to-noise ratio, as demonstrated with two sets of promoter sequences. The method is implemented as a graphical web application, ConSite, which is at the disposal of the scientific community at http://www.phylofoot.org/. CONCLUSIONS: Phylogenetic footprinting dramatically improves the predictive selectivity of bioinformatic approaches to the analysis of promoter sequences. ConSite delivers unparalleled performance using a novel database of high-quality binding models for metazoan transcription factors. With a dynamic interface, this bioinformatics tool provides broad access to promoter analysis with phylogenetic footprinting.

Algorithms↗
PubMed2003

In silico identification of metazoan transcriptional regulatory regions.

Transcriptional regulation remains one of the most intriguing and challenging subjects in biomedical research. The catalysis of transcription is a clear example of multiple proteins interacting to orchestrate a biological process, offering a starting point for the study of biological systems. Transcriptional regulation is viewed as one of the principal mechanisms governing the spatial and temporal distribution of gene expression, thus the field of transcriptional regulation provides a natural stage for quantitative studies of multiple gene systems. Building on the body of focused experimental studies and new genomics-driven data, computational biologists are making significant strides in accelerating our understanding of the transcriptional regulatory process in metazoan cells. Recent advances in the computational analysis of the interplay between factors have been fueled by well-defined computational methods for the modeling of the binding of individual transcription factors. We present here an overview of advances in the analysis of regulatory systems and the fundamental methods that underlie the recent developments.

Animals↗
PubMed2003

GeneLynx mouse: integrated portal to the mouse genome.

GeneLynx Mouse is a meta-database providing an extensive collection of hyperlinks to mouse gene-specific information in diverse databases available via the Internet. The GeneLynx project is based on the simple notion that given any gene-specific identifier (e.g., accession number, gene name, text, or sequence), scientists should be able to access a single location that provides a set of links to all the publicly available information pertinent to the specified gene. The recent climax in the mouse genome and RIKEN cDNA sequencing projects provided the data necessary for the development of a gene-centric mouse information portal based on the GeneLynx ideals. Clusters of RIKEN cDNA sequences were used to define the initial set of mouse genes. Like its human counterpart, GeneLynx Mouse is designed as an extensible relational database with an intuitive and user-friendly Web interface. Data is automatically extracted from diverse resources, using appropriate approaches to maximize the coverage. To promote cross-database interoperability, an indexing utility is provided to facilitate the establishment of hyperlinks in external databases. As a result of the integration of the human and mouse systems, GeneLynx now serves as a powerful comparative genomics data mining resource. GeneLynx Mouse can be freely accessed at http://mouse.genelynx.org.

Animals↗