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Featured researches published by Marek Tutaj.


Nucleic Acids Research | 2015

The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease

Mary Shimoyama; Jeff De Pons; G. Thomas Hayman; Stanley J. F. Laulederkind; Weisong Liu; Rajni Nigam; Victoria Petri; Jennifer R. Smith; Marek Tutaj; Shur-Jen Wang; Elizabeth A. Worthey; Melinda R. Dwinell; Howard J. Jacob

The Rat Genome Database (RGD, http://rgd.mcw.edu) provides the most comprehensive data repository and informatics platform related to the laboratory rat, one of the most important model organisms for disease studies. RGD maintains and updates datasets for genomic elements such as genes, transcripts and increasingly in recent years, sequence variations, as well as map positions for multiple assemblies and sequence information. Functional annotations for genomic elements are curated from published literature, submitted by researchers and integrated from other public resources. Complementing the genomic data catalogs are those associated with phenotypes and disease, including strains, QTL and experimental phenotype measurements across hundreds of strains. Data are submitted by researchers, acquired through bulk data pipelines or curated from published literature. Innovative software tools provide users with an integrated platform to query, mine, display and analyze valuable genomic and phenomic datasets for discovery and enhancement of their own research. This update highlights recent developments that reflect an increasing focus on: (i) genomic variation, (ii) phenotypes and diseases, (iii) data related to the environment and experimental conditions and (iv) datasets and software tools that allow the user to explore and analyze the interactions among these and their impact on disease.


Journal of Biomedical Semantics | 2014

The pathway ontology - updates and applications

Victoria Petri; Pushkala Jayaraman; Marek Tutaj; G. Thomas Hayman; Jennifer R. Smith; Jeff De Pons; Stanley J. F. Laulederkind; T. F. Lowry; Rajni Nigam; Shur-Jen Wang; Mary Shimoyama; Melinda R. Dwinell; Diane H. Munzenmaier; Elizabeth A. Worthey; Howard J. Jacob

BackgroundThe Pathway Ontology (PW) developed at the Rat Genome Database (RGD), covers all types of biological pathways, including altered and disease pathways and captures the relationships between them within the hierarchical structure of a directed acyclic graph. The ontology allows for the standardized annotation of rat, and of human and mouse genes to pathway terms. It also constitutes a vehicle for easy navigation between gene and ontology report pages, between reports and interactive pathway diagrams, between pathways directly connected within a diagram and between those that are globally related in pathway suites and suite networks. Surveys of the literature and the development of the Pathway and Disease Portals are important sources for the ongoing development of the ontology. User requests and mapping of pathways in other databases to terms in the ontology further contribute to increasing its content. Recently built automated pipelines use the mapped terms to make available the annotations generated by other groups.ResultsThe two released pipelines – the Pathway Interaction Database (PID) Annotation Import Pipeline and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Annotation Import Pipeline, make available over 7,400 and 31,000 pathway gene annotations, respectively. Building the PID pipeline lead to the addition of new terms within the signaling node, also augmented by the release of the RGD “Immune and Inflammatory Disease Portal” at that time. Building the KEGG pipeline lead to a substantial increase in the number of disease pathway terms, such as those within the ‘infectious disease pathway’ parent term category. The ‘drug pathway’ node has also seen increases in the number of terms as well as a restructuring of the node. Literature surveys, disease portal deployments and user requests have contributed and continue to contribute additional new terms across the ontology. Since first presented, the content of PW has increased by over 75%.ConclusionsOngoing development of the Pathway Ontology and the implementation of pipelines promote an enriched provision of pathway data. The ontology is freely available for download and use from the RGD ftp site at ftp://rgd.mcw.edu/pub/ontology/pathway/ or from the National Center for Biomedical Ontology (NCBO) BioPortal website at http://bioportal.bioontology.org/ontologies/PW.


Physiological Genomics | 2013

Rat Genome Database: a unique resource for rat, human, and mouse quantitative trait locus data

Rajni Nigam; Stanley J. F. Laulederkind; G. Thomas Hayman; Jennifer R. Smith; Shur-Jen Wang; T. F. Lowry; Victoria Petri; Jeff De Pons; Marek Tutaj; Weisong Liu; Pushkala Jayaraman; Diane H. Munzenmaier; Elizabeth A. Worthey; Melinda R. Dwinell; Mary Shimoyama; Howard J. Jacob

The rat has been widely used as a disease model in a laboratory setting, resulting in an abundance of genetic and phenotype data from a wide variety of studies. These data can be found at the Rat Genome Database (RGD, http://rgd.mcw.edu/), which provides a platform for researchers interested in linking genomic variations to phenotypes. Quantitative trait loci (QTLs) form one of the earliest and core datasets, allowing researchers to identify loci harboring genes associated with disease. These QTLs are not only important for those using the rat to identify genes and regions associated with disease, but also for cross-organism analyses of syntenic regions on the mouse and the human genomes to identify potential regions for study in these organisms. Currently, RGD has data on >1,900 rat QTLs that include details about the methods and animals used to determine the respective QTL along with the genomic positions and markers that define the region. RGD also curates human QTLs (>1,900) and houses>4,000 mouse QTLs (imported from Mouse Genome Informatics). Multiple ontologies are used to standardize traits, phenotypes, diseases, and experimental methods to facilitate queries, analyses, and cross-organism comparisons. QTLs are visualized in tools such as GBrowse and GViewer, with additional tools for analysis of gene sets within QTL regions. The QTL data at RGD provide valuable information for the study of mapped phenotypes and identification of candidate genes for disease associations.


Database | 2012

Ontology searching and browsing at the Rat Genome Database

Stanley J. F. Laulederkind; Marek Tutaj; Mary Shimoyama; G. Thomas Hayman; T. F. Lowry; Rajni Nigam; Victoria Petri; Jennifer R. Smith; Shur-Jen Wang; Jeff De Pons; Melinda R. Dwinell; Howard J. Jacob

The Rat Genome Database (RGD) is the premier repository of rat genomic and genetic data and currently houses over 40 000 rat gene records, as well as human and mouse orthologs, 1857 rat and 1912 human quantitative trait loci (QTLs) and 2347 rat strains. Biological information curated for these data objects includes disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components. RGD uses more than a dozen different ontologies to standardize annotation information for genes, QTLs and strains. That means a lot of time can be spent searching and browsing ontologies for the appropriate terms needed both for curating and mining the data. RGD has upgraded its ontology term search to make it more versatile and more robust. A term search result is connected to a term browser so the user can fine-tune the search by viewing parent and children terms. Most publicly available term browsers display a hierarchical organization of terms in an expandable tree format. RGD has replaced its old tree browser format with a ‘driller’ type of browser that allows quicker drilling up and down through the term branches, which has been confirmed by testing. The RGD ontology report pages have also been upgraded. Expanded functionality allows more choice in how annotations are displayed and what subsets of annotations are displayed. The new ontology search, browser and report features have been designed to enhance both manual data curation and manual data extraction. Database URL: http://rgd.mcw.edu/rgdweb/ontology/search.html


Database | 2011

The Rat Genome Database Pathway Portal

Victoria Petri; Mary Shimoyama; G. Thomas Hayman; Jennifer R. Smith; Marek Tutaj; Jeff De Pons; Melinda R. Dwinell; Diane H. Munzenmaier; Simon N. Twigger; Howard J. Jacob; Rgd Team

The set of interacting molecules collectively referred to as a pathway or network represents a fundamental structural unit, the building block of the larger, highly integrated networks of biological systems. The scientific communitys interest in understanding the fine details of how pathways work, communicate with each other and synergize, and how alterations in one or several pathways may converge into a disease phenotype, places heightened demands on pathway data and information providers. To meet such demands, the Rat Genome Database [(RGD) http://rgd.mcw.edu] has adopted a multitiered approach to pathway data acquisition and presentation. Resources and tools are continuously added or expanded to offer more comprehensive pathway data sets as well as enhanced pathway data manipulation, exploration and visualization capabilities. At RGD, users can easily identify genes in pathways, see how pathways relate to each other and visualize pathways in a dynamic and integrated manner. They can access these and other components from several entry points and effortlessly navigate between them and they can download the data of interest. The Pathway Portal resources at RGD are presented, and future directions are discussed. Database URL: http://rgd.mcw.edu


Journal of Biomedical Semantics | 2013

The clinical measurement, measurement method and experimental condition ontologies: expansion, improvements and new applications

Jennifer R. Smith; Carissa A. Park; Rajni Nigam; Stanley J. F. Laulederkind; G. Thomas Hayman; Shur-Jen Wang; T. F. Lowry; Victoria Petri; Jeff De Pons; Marek Tutaj; Weisong Liu; Elizabeth A. Worthey; Mary Shimoyama; Melinda R. Dwinell

BackgroundThe Clinical Measurement Ontology (CMO), Measurement Method Ontology (MMO), and Experimental Condition Ontology (XCO) were originally developed at the Rat Genome Database (RGD) to standardize quantitative rat phenotype data in order to integrate results from multiple studies into the PhenoMiner database and data mining tool. These ontologies provide the framework for presenting what was measured, how it was measured, and under what conditions it was measured.ResultsThere has been a continuing expansion of subdomains in each ontology with a parallel 2–3 fold increase in the total number of terms, substantially increasing the size and improving the scope of the ontologies. The proportion of terms with textual definitions has increased from ~60% to over 80% with greater synchronization of format and content throughout the three ontologies. Representation of definition source Uniform Resource Identifiers (URI) has been standardized, including the removal of all non-URI characters, and systematic versioning of all ontology files has been implemented. The continued expansion and success of these ontologies has facilitated the integration of more than 60,000 records into the RGD PhenoMiner database. In addition, new applications of these ontologies, such as annotation of Quantitative Trait Loci (QTL), have been added at the sites actively using them, including RGD and the Animal QTL Database.ConclusionsThe improvements to these three ontologies have been substantial, and development is ongoing. New terms and expansions to the ontologies continue to be added as a result of active curation efforts at RGD and the Animal QTL database. Use of these vocabularies to standardize data representation for quantitative phenotypes and quantitative trait loci across databases for multiple species has demonstrated their utility for integrating diverse data types from multiple sources. These ontologies are freely available for download and use from the NCBO BioPortal website at http://bioportal.bioontology.org/ontologies/1583 (CMO), http://bioportal.bioontology.org/ontologies/1584 (MMO), and http://bioportal.bioontology.org/ontologies/1585 (XCO), or from the RGD ftp site at ftp://rgd.mcw.edu/pub/ontology/.


Database | 2016

The Chinchilla Research Resource Database: resource for an otolaryngology disease model

Mary Shimoyama; Jennifer R. Smith; Jeff De Pons; Marek Tutaj; Pawjai Khampang; Wenzhou Hong; Christy B. Erbe; Garth D. Ehrlich; Lauren O. Bakaletz; Joseph E. Kerschner

The long-tailed chinchilla (Chinchilla lanigera) is an established animal model for diseases of the inner and middle ear, among others. In particular, chinchilla is commonly used to study diseases involving viral and bacterial pathogens and polymicrobial infections of the upper respiratory tract and the ear, such as otitis media. The value of the chinchilla as a model for human diseases prompted the sequencing of its genome in 2012 and the more recent development of the Chinchilla Research Resource Database (http://crrd.mcw.edu) to provide investigators with easy access to relevant datasets and software tools to enhance their research. The Chinchilla Research Resource Database contains a complete catalog of genes for chinchilla and, for comparative purposes, human. Chinchilla genes can be viewed in the context of their genomic scaffold positions using the JBrowse genome browser. In contrast to the corresponding records at NCBI, individual gene reports at CRRD include functional annotations for Disease, Gene Ontology (GO) Biological Process, GO Molecular Function, GO Cellular Component and Pathway assigned to chinchilla genes based on annotations from the corresponding human orthologs. Data can be retrieved via keyword and gene-specific searches. Lists of genes with similar functional attributes can be assembled by leveraging the hierarchical structure of the Disease, GO and Pathway vocabularies through the Ontology Search and Browser tool. Such lists can then be further analyzed for commonalities using the Gene Annotator (GA) Tool. All data in the Chinchilla Research Resource Database is freely accessible and downloadable via the CRRD FTP site or using the download functions available in the search and analysis tools. The Chinchilla Research Resource Database is a rich resource for researchers using, or considering the use of, chinchilla as a model for human disease. Database URL: http://crrd.mcw.edu


Human Genomics | 2013

The updated RGD Pathway Portal utilizes increased curation efficiency and provides expanded pathway information.

G. Thomas Hayman; Pushkala Jayaraman; Victoria Petri; Marek Tutaj; Weisong Liu; Jeff De Pons; Melinda R. Dwinell; Mary Shimoyama

The RGD Pathway Portal provides pathway annotations for rat, human and mouse genes and pathway diagrams and suites, all interconnected via the pathway ontology. Diagram pages present the diagram and description, with diagram objects linked to additional resources. A newly-developed dual-functionality web application composes the diagram page. Curators input the description, diagram, references and additional pathway objects. The application combines these with tables of rat, human and mouse pathway genes, including genetic information, analysis tool and reference links, and disease, phenotype and other pathway annotations to pathway genes. The application increases the information content of diagram pages while expediting publication.


Disease Models & Mechanisms | 2016

Exploring human disease using the Rat Genome Database

Mary Shimoyama; Stanley J. F. Laulederkind; Jeff De Pons; Rajni Nigam; Jennifer R. Smith; Marek Tutaj; Victoria Petri; G. Thomas Hayman; Shur-Jen Wang; Omid Ghiasvand; Jyothi Thota; Melinda R. Dwinell

ABSTRACT Rattus norvegicus, the laboratory rat, has been a crucial model for studies of the environmental and genetic factors associated with human diseases for over 150 years. It is the primary model organism for toxicology and pharmacology studies, and has features that make it the model of choice in many complex-disease studies. Since 1999, the Rat Genome Database (RGD; http://rgd.mcw.edu) has been the premier resource for genomic, genetic, phenotype and strain data for the laboratory rat. The primary role of RGD is to curate rat data and validate orthologous relationships with human and mouse genes, and make these data available for incorporation into other major databases such as NCBI, Ensembl and UniProt. RGD also provides official nomenclature for rat genes, quantitative trait loci, strains and genetic markers, as well as unique identifiers. The RGD team adds enormous value to these basic data elements through functional and disease annotations, the analysis and visual presentation of pathways, and the integration of phenotype measurement data for strains used as disease models. Because much of the rat research community focuses on understanding human diseases, RGD provides a number of datasets and software tools that allow users to easily explore and make disease-related connections among these datasets. RGD also provides comprehensive human and mouse data for comparative purposes, illustrating the value of the rat in translational research. This article introduces RGD and its suite of tools and datasets to researchers – within and beyond the rat community – who are particularly interested in leveraging rat-based insights to understand human diseases. Summary: The Rat Genome Database (RGD) is the most comprehensive site for genetic, genomic and phenotype data for Rattus norvegicus, a leading animal model for disease-, drug- and toxicity-related research.


Database | 2016

The Disease Portals, disease–gene annotation and the RGD disease ontology at the Rat Genome Database

G. Thomas Hayman; Stanley J. F. Laulederkind; Jennifer R. Smith; Shur-Jen Wang; Victoria Petri; Rajni Nigam; Marek Tutaj; Jeff De Pons; Melinda R. Dwinell; Mary Shimoyama

The Rat Genome Database (RGD; http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene–disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL: http://rgd.mcw.edu

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Mary Shimoyama

Medical College of Wisconsin

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Melinda R. Dwinell

Medical College of Wisconsin

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Jeff De Pons

Medical College of Wisconsin

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Victoria Petri

Medical College of Wisconsin

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G. Thomas Hayman

Medical College of Wisconsin

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Jennifer R. Smith

University of Massachusetts Medical School

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Rajni Nigam

Medical College of Wisconsin

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Shur-Jen Wang

Medical College of Wisconsin

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Howard J. Jacob

Medical College of Wisconsin

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