Biomedical subjects

Peter M Haverty

Publications and source records attributed to Peter M Haverty.

7 recordsLinked to original sources

PubMed2005

Genetic and pharmacological inactivation of adenosine A2A receptor reveals an Egr-2-mediated transcriptional regulatory network in the mouse striatum.

The adenosine A2A receptor (A2AR) is highly expressed in the striatum, where it modulates motor and emotional behaviors. We used both microarray and bioinformatics analyses to compare gene expression profiles by genetic and pharmacological inactivation of A2AR and inferred an A2AR-controlled transcription network in the mouse striatum. A comparison between vehicle (VEH)-treated A2AR knockout (KO) mice (A2AR KO-VEH) and wild-type (WT) mice (WT-VEH) revealed 36 upregulated genes that were partially mimicked by treatment with SCH-58261 (SCH; an A2AR antagonist) and 54 downregulated genes that were not mimicked by SCH treatment. We validated the A2AR as a specific drug target for SCH by comparing A2AR KO-SCH and A2AR KO-VEH groups. The unique downregulation effect of A2AR KO was confirmed by comparing A2AR KO-SCH with WT-SCH gene groups. The distinct striatal gene expression profiles induced by A2AR KO and SCH should provide clues to the molecular mechanisms underlying the different phenotypes observed after genetic and pharmacological inactivation of A2AR. Furthermore, bioinformatics analysis discovered that Egr-2 binding sites were statistically overrepresented in the proximal promoters of A2AR KO-affected genes relative to the unaffected genes. This finding was further substantiated by the demonstration that the Egr-2 mRNA level increased in the striatum of both A2AR KO and SCH-treated mice and that striatal Egr-2 binding activity in the promoters of two A2AR KO-affected genes was enhanced in A2AR KO mice as assayed by chromatin immunoprecipitation. Taken together, these results strongly support the existence of an Egr-2-directed transcriptional regulatory network controlled by striatal A2ARs.

Animals↗

PubMed2004

Limited agreement among three global gene expression methods highlights the requirement for non-global validation.

MOTIVATION: DNA microarrays have revolutionized biological research, but their reliability and accuracy have not been extensively evaluated. Thorough testing of microarrays through comparison to dissimilar gene expression methods is necessary in order to determine their accuracy. RESULTS: We have systematically compared three global gene expression methods on all available histologically normal samples from five human organ types. The data included 25 Affymetrix high-density oligonucleotide array experiments, 23 expressed sequence tag based expression (EBE) experiments and 5 SAGE experiments. The reported gene-by-gene expression patterns showed a wide range of correlations between pairs of methods. This level of agreement was sufficient for accurate clustering of datasets from the same tissue and dissimilar methods, but highlights the need for thorough validation of individual gene expression measurements by alternate, non-global methods. Furthermore, analyses of mRNA abundance distributions indicate limitations in the EBE and SAGE methods at both high- and low-expression levels.

Algorithms↗

PubMed2004

CARRIE web service: automated transcriptional regulatory network inference and interactive analysis.

We present an intuitive and interactive web service for CARRIE (Computational Ascertainment of Regulatory Relationships Inferred from Expression). CARRIE is a computational method that analyzes microarray and promoter sequence data to infer a transcriptional regulatory network from the response to a specific stimulus. This service displays an interactive graph of the inferred network and provides easy access to the evidence for the involvement of each gene in the network. We provide functionality to include network data in KEGG XML (KGML) format in this graph. Our service also provides Gene Ontology annotation to aid the user in forming hypotheses about the role of each gene in the cellular response. The CARRIE web service is freely available at http://zlab.bu.edu/CARRIE-web.

Binding Sites↗

PubMed2004

MotifViz: an analysis and visualization tool for motif discovery.

Detecting overrepresented known transcription factor binding motifs in a set of promoter sequences of co-regulated genes has become an important approach to deciphering transcriptional regulatory mechanisms. In this paper, we present an interactive web server, MotifViz, for three motif discovery programs, Clover, Rover and Motifish, covering most available flavors of algorithms for achieving this goal. For comparison, we have also implemented the simple motif-matching program Possum. MotifViz provides uniform and intuitive input and output formats for all four programs. It can be accessed at http://biowulf.bu.edu/MotifViz.

Algorithms↗

PubMed2004

CisML: an XML-based format for sequence motif detection software.

SUMMARY: CisML is an XML-based format for sequence motif detection software. This proposed standard is applicable to many types of sequence motif detection programs. It is intended to facilitate the integration of data and the comparison of results from different software packages, and to simplify the development of downstream tools. XSL stylesheets are provided for easy generation of text, html and graphical reports from CisML-formatted data. AVAILABILITY: http://zlab.bu.edu/CisML/ SUPPLEMENTARY INFORMATION: Example CisML-formatted data and XSL stylesheets for report generation are available along with the sample output.

Amino Acid Motifs↗

PubMed2004

Computational inference of transcriptional regulatory networks from expression profiling and transcription factor binding site identification.

We have developed a computational method for transcriptional regulatory network inference, CARRIE (Computational Ascertainment of Regu latory Relationships Inferred from Expression), which combines microarray and promoter sequence analysis. CARRIE uses sources of data to identify the transcription factors (TFs) that regulate gene expression changes in response to a stimulus and generates testable hypotheses about the regulatory network connecting these TFs to the genes they regulate. The promoter analysis component of CARRIE, ROVER (Relative OVER-abundance of cis-elements), is highly accurate at detecting the TFs that regulate the response to a stimulus. ROVER also predicts which genes are regulated by each of these TFs. CARRIE uses these transcriptional interactions to infer a regulatory network. To demonstrate our method, we applied CARRIE to six sets of publicly available DNA microarray experiments on Saccharomyces cerevisiae. The predicted networks were validated with comparisons to literature sources, experimental TF binding data, and gene ontology biological process information.

Binding Sites↗

PubMed2002

HugeIndex: a database with visualization tools for high-density oligonucleotide array data from normal human tissues.

High-density oligonucleotide arrays are a powerful tool for uncovering changes in global gene expression in various disease states. To this end, it is essential to first characterize the variations of gene expression in normal physiological processes. We established the Human Gene Expression (HuGE) Index database (www.HugeIndex.org) to serve as a public repository for gene expression data on normal human tissues using high-density oligonucleotide arrays. This resource currently contains the results of 59 gene expression experiments on 19 human tissues. We provide interactive tools for researchers to query and visualize our data over the Internet. To facilitate data analysis, we cross-reference each gene on the array with its annotation in the LocusLink database at NCBI.

Computer Graphics↗