Janan T Eppig

The Jackson Laboratory, BHB, Maine, United States

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Publications (155)1237.5 Total impact

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    Cynthia L Smith, Janan T Eppig
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    ABSTRACT: A vast array of data is about to emerge from the large scale high-throughput mouse knockout phenotyping projects worldwide. It is critical that this information is captured in a standardized manner, made accessible, and is fully integrated with other phenotype data sets for comprehensive querying and analysis across all phenotype data types. The volume of data generated by the high-throughput phenotyping screens is expected to grow exponentially, thus, automated methods and standards to exchange phenotype data are required. The IMPC (International Mouse Phenotyping Consortium) is using the Mammalian Phenotype (MP) ontology in the automated annotation of phenodeviant data from high throughput phenotyping screens. 287 new term additions with additional hierarchy revisions were made in multiple branches of the MP ontology to accurately describe the results generated by these high throughput screens. Because these large scale phenotyping data sets will be reported using the MP as the common data standard for annotation and data exchange, automated importation of these data to MGI (Mouse Genome Informatics) and other resources is possible without curatorial effort. Maximum biomedical value of these mutant mice will come from integrating primary high-throughput phenotyping data with secondary, comprehensive phenotypic analyses combined with published phenotype details on these and related mutants at MGI and other resources.
    Journal of Biomedical Semantics 12/2015; 6(1):11. DOI:10.1186/s13326-015-0009-1
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    ABSTRACT: The Gene Expression Database (GXD) is an extensive and freely available community resource of mouse developmental expression data. GXD curates and integrates expression data from the literature, via electronic data submissions, and by collaborations with large-scale projects. As an integral component of the Mouse Genome Informatics (MGI) Resource, GXD combines expression data with genetic, functional, phenotypic and disease-related data, and provides tools for the research community to search for and analyze expression data in this larger context. Recent enhancements include: an interactive browser to navigate the mouse developmental anatomy and find expression data for specific anatomical structures; the capability to search for expression data of genes located in specific genomic regions, supporting the identification of disease candidate genes; a summary displaying all the expression images that meet specified search criteria; interactive matrix views that provide overviews of spatio-temporal expression patterns (Tissue x Stage Matrix) and enable the comparison of expression patterns between genes (Tissue x Gene Matrix); data zoom and filter utilities to iteratively refine summary displays and data sets; and gene-based links to expression data from other model organisms, such as chicken, Xenopus and zebrafish, fostering comparative expression analysis for species that are highly relevant for developmental research. This article is protected by copyright. All rights reserved. © 2015 Wiley Periodicals, Inc.
    genesis 06/2015; DOI:10.1002/dvg.22864 · 2.04 Impact Factor
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    ABSTRACT: The Gene Expression Database (GXD) is an extensive, easily searchable, and freely available database of mouse gene expression information ( www.informatics.jax.org/expression.shtml ). GXD was developed to foster progress toward understanding the molecular basis of human development and disease. GXD contains information about when and where genes are expressed in different tissues in the mouse, especially during the embryonic period. GXD collects different types of expression data from wild-type and mutant mice, including RNA in situ hybridization, immunohistochemistry, RT-PCR, and northern and western blot results. The GXD curators read the scientific literature and enter the expression data from those papers into the database. GXD also acquires expression data directly from researchers, including groups doing large-scale expression studies. GXD currently contains nearly 1.5 million expression results for over 13,900 genes. In addition, it has over 265,000 images of expression data, allowing users to retrieve the primary data and interpret it themselves. By being an integral part of the larger Mouse Genome Informatics (MGI) resource, GXD's expression data are combined with other genetic, functional, phenotypic, and disease-oriented data. This allows GXD to provide tools for researchers to evaluate expression data in the larger context, search by a wide variety of biologically and biomedically relevant parameters, and discover new data connections to help in the design of new experiments. Thus, GXD can provide researchers with critical insights into the functions of genes and the molecular mechanisms of development, differentiation, and disease.
    Mammalian Genome 05/2015; DOI:10.1007/s00335-015-9563-1 · 2.88 Impact Factor
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    ABSTRACT: Congenital heart disease (CHD) is the most prevalent birth defect, affecting nearly 1% of live births1; the incidence ofCHDis up to tenfold higher inhumanfetuses2,3.Agenetic contributionis stronglysuggested by the association of CHD with chromosome abnormalities and high recurrence risk4. Here we report findings from a recessive forward genetic screen in fetal mice, showing that cilia and ciliatransduced cell signalling have important roles in the pathogenesis ofCHD. The ciliumis an evolutionarily conserved organelle projecting fromthe cell surfacewith essential roles in diverse cellularprocesses. Using echocardiography, we ultrasound scanned 87,355 chemically mutagenized C57BL/6J fetal mice and recovered 218 CHD mouse models. Whole-exome sequencing identified 91 recessiveCHDmutations in 61 genes. This included 34 cilia-related genes, 16 genes involved in cilia-transduced cell signalling, and 10 genes regulating vesicular trafficking, a pathway important for ciliogenesis and cell signalling. Surprisingly, manyCHDgenes encoded interacting proteins, suggesting that an interactome protein network may provide a larger genomic context forCHDpathogenesis.These findings provide novel insights into the potentialMendelian genetic contribution toCHDin the fetal population, a segment of the human population not well studied. We note that the pathways identified show overlap with CHD candidate genes recovered in CHD patients5, suggesting that they may have relevance to the more complex genetics of CHD overall.TheseCHDmousemodels and.8,000 incidentalmutations have been spermarchived, creating a rich public resource forhuman disease modelling.
    Nature 03/2015; 521(7553). DOI:10.1038/nature14269 · 42.35 Impact Factor
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    ABSTRACT: 1 Congenital heart disease (CHD) is the most prevalent birth defect, affecting nearly 1% of live births 1 ; the incidence of CHD is up to tenfold higher in human fetuses 2,3. A genetic contribution is strongly suggested by the association of CHD with chromosome abnormalities and high recurrence risk 4. Here we report findings from a recessive forward genetic screen in fetal mice, showing that cilia and cilia-transduced cell signalling have important roles in the pathogenesis of CHD. The cilium is an evolutionarily conserved organelle projecting from the cell surface with essential roles in diverse cellular processes. Using echocardiography, we ultrasound scanned 87,355 chemically mutagenized C57BL/6J fetal mice and recovered 218 CHD mouse models. Whole-exome sequencing identified 91 recessive CHD mutations in 61 genes. This included 34 cilia-related genes, 16 genes involved in cilia-transduced cell signalling, and 10 genes regulating vesicular trafficking, a pathway important for ciliogenesis and cell signalling. Surprisingly, many CHD genes encoded interacting proteins , suggesting that an interactome protein network may provide a larger genomic context for CHD pathogenesis. These findings provide novel insights into the potential Mendelian genetic contribution to CHD in the fetal population, a segment of the human population not well studied. We note that the pathways identified show overlap with CHD candidate genes recovered in CHD patients 5 , suggesting that they may have relevance to the more complex genetics of CHD overall. These CHD mouse models and .8,000 incidental mutations have been sperm archived, creating a rich public resource for human disease modelling. Inbred C57BL/6J mice mutagenized with ethylnitrosourea (ENU) were bred to recover recessive coding mutations (Extended Data Fig. 1). Phenotyping was conducted using non-invasive fetal echocardiography, an ultrasound imaging modality also employed clinically for CHD diagnosis. This unbiased study design allows detection of even those CHD mutants inviable to term 6
    Nature 03/2015; · 42.35 Impact Factor
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    ABSTRACT: Congenital heart disease (CHD) is the most prevalent birth defect, affecting nearly 1% of live births; the incidence of CHD is up to tenfold higher in human fetuses. A genetic contribution is strongly suggested by the association of CHD with chromosome abnormalities and high recurrence risk. Here we report findings from a recessive forward genetic screen in fetal mice, showing that cilia and cilia-transduced cell signalling have important roles in the pathogenesis of CHD. The cilium is an evolutionarily conserved organelle projecting from the cell surface with essential roles in diverse cellular processes. Using echocardiography, we ultrasound scanned 87,355 chemically mutagenized C57BL/6J fetal mice and recovered 218 CHD mouse models. Whole-exome sequencing identified 91 recessive CHD mutations in 61 genes. This included 34 cilia-related genes, 16 genes involved in cilia-transduced cell signalling, and 10 genes regulating vesicular trafficking, a pathway important for ciliogenesis and cell signalling. Surprisingly, many CHD genes encoded interacting proteins, suggesting that an interactome protein network may provide a larger genomic context for CHD pathogenesis. These findings provide novel insights into the potential Mendelian genetic contribution to CHD in the fetal population, a segment of the human population not well studied. We note that the pathways identified show overlap with CHD candidate genes recovered in CHD patients, suggesting that they may have relevance to the more complex genetics of CHD overall. These CHD mouse models and >8,000 incidental mutations have been sperm archived, creating a rich public resource for human disease modelling.
    Nature 03/2015; · 42.35 Impact Factor
  • Molecular Cancer Research 11/2014; 12(11 Supplement):A05-A05. DOI:10.1158/1557-3125.MODORG-A05 · 4.50 Impact Factor
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    ABSTRACT: The Mouse Genome Database (MGD, http://www.informatics.jax.org) serves the international biomedical research community as the central resource for integrated genomic, genetic and biological data on the laboratory mouse. To facilitate use of mouse as a model in translational studies, MGD maintains a core of high-quality curated data and integrates experimentally and computationally generated data sets. MGD maintains a unified catalog of genes and genome features, including functional RNAs, QTL and phenotypic loci. MGD curates and provides functional and phenotype annotations for mouse genes using the Gene Ontology and Mammalian Phenotype Ontology. MGD integrates phenotype data and associates mouse genotypes to human diseases, providing critical mouse–human relationships and access to repositories holding mouse models. MGD is the authoritative source of nomenclature for genes, genome features, alleles and strains following guidelines of the International Committee on Standardized Genetic Nomenclature for Mice. A new addition to MGD, the Human–Mouse: Disease Connection, allows users to explore gene–phenotype–disease relationships between human and mouse. MGD has also updated search paradigms for phenotypic allele attributes, incorporated incidental mutation data, added a module for display and exploration of genes and microRNA interactions and adopted the JBrowse genome browser. MGD resources are freely available to the scientific community.
    Nucleic Acids Research 10/2014; 43(D1). DOI:10.1093/nar/gku967 · 9.11 Impact Factor
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    ABSTRACT: The Mouse Tumor Biology (MTB; http://tumor.informatics.jax.org) database is a unique online compendium of mouse models for human cancer. MTB provides online access to expertly curated information on diverse mouse models for human cancer and interfaces for searching and visualizing data associated with these models. The information in MTB is designed to facilitate the selection of strains for cancer research and is a platform for mining data on tumor development and patterns of metastases. MTB curators acquire data through manual curation of peer-reviewed scientific literature and from direct submissions by researchers. Data in MTB are also obtained from other bioinformatics resources including PathBase, the Gene Expression Omnibus and ArrayExpress. Recent enhancements to MTB improve the association between mouse models and human genes commonly mutated in a variety of cancers as identified in large-scale cancer genomics studies, provide new interfaces for exploring regions of the mouse genome associated with cancer phenotypes and incorporate data and information related to Patient-Derived Xenograft models of human cancers.
    Nucleic Acids Research 10/2014; 43(D1). DOI:10.1093/nar/gku987 · 9.11 Impact Factor
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    ABSTRACT: In recent years the scientific community has generated an ever-increasing amount of data from a growing number of animal models of human cancers. Much of these data come from genetically engineered mouse models. Identifying appropriate models for skin cancer and related relevant genetic data sets from an expanding pool of widely disseminated data can be a daunting task. The Mouse Tumor Biology Database (MTB) provides an electronic archive, search, and analysis system that can be used to identify dermatological mouse models of cancer, retrieve model-specific data, and analyze these data. In this report we detail MTB's contents and capabilities, together with instructions on how to use MTB to search for skin-related tumor models and associated data.This article is protected by copyright. All rights reserved.
    Experimental Dermatology 07/2014; 23(10). DOI:10.1111/exd.12512 · 4.12 Impact Factor
  • Cancer Research 05/2014; 73(19 Supplement):C18-C18. DOI:10.1158/1538-7445.FBCR13-C18 · 9.28 Impact Factor
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    ABSTRACT: The Gene Expression Database (GXD; http://www.informatics.jax.org/expression.shtml) is an extensive and well-curated community resource of mouse developmental expression information. GXD collects different types of expression data from studies of wild-type and mutant mice, covering all developmental stages and including data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments. The data are acquired from the scientific literature and from researchers, including groups doing large-scale expression studies. Integration with the other data in Mouse Genome Informatics (MGI) and interconnections with other databases places GXD’s gene expression information in the larger biological and biomedical context. Since the last report, the utility of GXD has been greatly enhanced by the addition of new data and by the implementation of more powerful and versatile search and display features. Web interface enhancements include the capability to search for expression data for genes associated with specific phenotypes and/or human diseases; new, more interactive data summaries; easy downloading of data; direct searches of expression images via associated metadata; and new displays that combine image data and their associated annotations. At present, GXD includes >1.4 million expression results and 250 000 images that are accessible to our search tools.
    Nucleic Acids Research 12/2013; 42(D1):D818-D824. DOI:10.1093/nar/gkt954 · 9.11 Impact Factor
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    ABSTRACT: The Mouse Genome Database (MGD) (http://www.informatics.jax.org) is the community model organism database resource for the laboratory mouse, a premier animal model for the study of genetic and genomic systems relevant to human biology and disease. MGD maintains a comprehensive catalog of genes, functional RNAs and other genome features as well as heritable phenotypes and quantitative trait loci. The genome feature catalog is generated by the integration of computational and manual genome annotations generated by NCBI, Ensembl and Vega/HAVANA. MGD curates and maintains the comprehensive listing of functional annotations for mouse genes using the Gene Ontology, and MGD curates and integrates comprehensive phenotype annotations including associations of mouse models with human diseases. Recent improvements include integration of the latest mouse genome build (GRCm38), improved access to comparative and functional annotations for mouse genes with expanded representation of comparative vertebrate genomes and new loads of phenotype data from high-throughput phenotyping projects. All MGD resources are freely available to the research community.
    Nucleic Acids Research 11/2013; 42(D1). DOI:10.1093/nar/gkt1225 · 9.11 Impact Factor
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    ABSTRACT: The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.
    Nucleic Acids Research 11/2013; 42(Database issue). DOI:10.1093/nar/gkt1026 · 9.11 Impact Factor
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    ABSTRACT: The use of ontologies to standardize biological data and facilitate comparisons among datasets has steadily grown as the complexity and amount of available data have increased. Despite the numerous ontologies available, one area currently lacking a robust ontology is the description of vertebrate traits. A trait is defined as any measurable or observable characteristic pertaining to an organism or any of its substructures. While there are several ontologies to describe entities and processes in phenotypes, diseases, and clinical measurements, one has not been developed for vertebrate traits; the Vertebrate Trait Ontology (VT) was created to fill this void.Description: Significant inconsistencies in trait nomenclature exist in the literature, and additional difficulties arise when trait data are compared across species. The VT is a unified trait vocabulary created to aid in the transfer of data within and between species and to facilitate investigation of the genetic basis of traits. Trait information provides a valuable link between the measurements that are used to assess the trait, the phenotypes related to the traits, and the diseases associated with one or more phenotypes. Because multiple clinical and morphological measurements are often used to assess a single trait, and a single measurement can be used to assess multiple physiological processes, providing investigators with standardized annotations for trait data will allow them to investigate connections among these data types. The annotation of genomic data with ontology terms provides unique opportunities for data mining and analysis. Links between data in disparate databases can be identified and explored, a strategy that is particularly useful for cross-species comparisons or in situations involving inconsistent terminology. The VT provides a common basis for the description of traits in multiple vertebrate species. It is being used in the Rat Genome Database and Animal QTL Database for annotation of QTL data for rat, cattle, chicken, swine, sheep, and rainbow trout, and in the Mouse Phenome Database to annotate strain characterization data. In these databases, data are also cross-referenced to applicable terms from other ontologies, providing additional avenues for data mining and analysis. The ontology is available at http://bioportal.bioontology.org/ontologies/50138.
    Journal of Biomedical Semantics 08/2013; 4(1):13. DOI:10.1186/2041-1480-4-13
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    ABSTRACT: The laboratory mouse is the premier animal model for studying human biology because all life stages can be accessed experimentally, a completely sequenced reference genome is publicly available and there exists a myriad of genomic tools for comparative and experimental research. In the current era of genome scale, data-driven biomedical research, the integration of genetic, genomic and biological data are essential for realizing the full potential of the mouse as an experimental model. The Mouse Genome Database (MGD; http://www.informatics.jax.org), the community model organism database for the laboratory mouse, is designed to facilitate the use of the laboratory mouse as a model system for understanding human biology and disease. To achieve this goal, MGD integrates genetic and genomic data related to the functional and phenotypic characterization of mouse genes and alleles and serves as a comprehensive catalog for mouse models of human disease. Recent enhancements to MGD include the addition of human ortholog details to mouse Gene Detail pages, the inclusion of microRNA knockouts to MGD's catalog of alleles and phenotypes, the addition of video clips to phenotype images, providing access to genotype and phenotype data associated with quantitative trait loci (QTL) and improvements to the layout and display of Gene Ontology annotations.
    Nucleic Acids Research 11/2012; DOI:10.1093/nar/gks1115 · 9.11 Impact Factor
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    ABSTRACT: Full realization of the value of the loxP-flanked alleles generated by the International Knockout Mouse Consortium will require a large set of well-characterized cre-driver lines. However, many cre driver lines display excision activity beyond the intended tissue or cell type, and these data are frequently unavailable to the potential user. Here we describe a high-throughput pipeline to extend characterization of cre driver lines to document excision activity in a wide range of tissues at multiple time points and disseminate these data to the scientific community. Our results show that the majority of cre strains exhibit some degree of unreported recombinase activity. In addition, we observe frequent mosaicism, inconsistent activity and parent-of-origin effects. Together, these results highlight the importance of deep characterization of cre strains, and provide the scientific community with a critical resource for cre strain information.
    Nature Communications 11/2012; 3:1218. DOI:10.1038/ncomms2186 · 10.74 Impact Factor
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    ABSTRACT: In 2007, the International Knockout Mouse Consortium (IKMC) made the ambitious promise to generate mutations in virtually every protein-coding gene of the mouse genome in a concerted worldwide action. Now, 5 years later, the IKMC members have developed high-throughput gene trapping and, in particular, gene-targeting pipelines and generated more than 17,400 mutant murine embryonic stem (ES) cell clones and more than 1,700 mutant mouse strains, most of them conditional. A common IKMC web portal ( www.knockoutmouse.org ) has been established, allowing easy access to this unparalleled biological resource. The IKMC materials considerably enhance functional gene annotation of the mammalian genome and will have a major impact on future biomedical research.
    Mammalian Genome 09/2012; 23(9-10):580-6. DOI:10.1007/s00335-012-9422-2 · 2.88 Impact Factor

Publication Stats

22k Citations
1,237.50 Total Impact Points

Institutions

  • 1998–2015
    • The Jackson Laboratory
      • Mouse Genome Informatics
      BHB, Maine, United States
  • 2012
    • Wellcome Trust Sanger Institute
      Cambridge, England, United Kingdom
  • 2004
    • The Ohio State University
      • Department of Veterinary Biosciences
      Columbus, Ohio, United States
  • 2000
    • Stanford Medicine
      • Department of Genetics
      Stanford, California, United States
  • 1997
    • University College London
      Londinium, England, United Kingdom
  • 1991
    • The Rockefeller University
      • Laboratory of Molecular Biology
      New York, New York, United States