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The Mammalian Phenotype Ontology (MP) is a structured vocabulary for describing mammalian phenotypes and serves as a critical tool for efficient annotation and comprehensive retrieval of phenotype data. Importantly, the ontology contains broad and specific terms, facilitating annotation of data from initial observations or screens and detailed data from subsequent experimental research. Using the ontology structure, data are retrieved inclusively, i.e., data annotated to chosen terms and to terms subordinate in the hierarchy. Thus, searching for “abnormal craniofacial morphology” also returns annotations to “megacephaly” and “microcephaly,” more specific terms in the hierarchy path. The development and refinement of the MP is ongoing, with new terms and modifications to its organization undergoing continuous assessment as users and expert reviewers propose expansions and revisions. A wealth of phenotype data on mouse mutations and variants annotated to the MP already exists in the Mouse Genome Informatics database. These data, along with data curated to the MP by many mouse mutagenesis programs and mouse repositories, provide a platform for comparative analyses and correlative discoveries. The MP provides a standard underpinning to mouse phenotype descriptions for existing and future experimental and large-scale phenotyping projects. In this review we describe the MP as it presently exists, its application to phenotype annotations, the relationship of the MP to other ontologies, and the integration of the MP within large-scale phenotyping projects. Finally we discuss future application of the MP in providing standard descriptors of the phenotype pipeline test results from the International Mouse Phenotype Consortium projects.

A forward genetic screen in fetal mice to identify genes involved in congenital heart disease (CHD) reveals that a large proportion of genes associated with CHD are related to cilia and cilia-transduced cell signalling, with potential implications for the human disease. Cilia defects in congenital heart disease The identification of genes causing congenital heart disease (CHD) has been challenging, in part because of the difficulty of distinguishing pathogenic mutations from random sequence genetic variability. Cecilia Lo and colleagues have therefore used a large-scale mouse forward genetic screen with chemical mutagenesis to recover mutations causing congenital heart disease. They identify 218 mouse models of the condition and, using whole-exome sequencing, 91 recessive mutations in 61 genes. A larger than expected proportion of these genes was found to be related to cilia and cilia-transduced cell signalling. 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.

Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD's and RGD's disease term annotations identified new terms that enhance DO's representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO's domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO's usability across human data, MGD, RGD and the rest of the model organism database community.

Background 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. Results 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. Conclusions 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.

With the effort of the International Phenotyping Consortium to produce thousands of strains with conditional potential gathering steam, there is growing recognition that it must be supported by a rich toolbox of cre driver strains. The approaches to build cre strains have evolved in both sophistication and reliability, replacing first-generation strains with tools that can target individual cell populations with incredible precision and specificity. The modest set of cre drivers generated by individual labs over the past 15+ years is now growing rapidly, thanks to a number of large-scale projects to produce new cre strains for the community. The power of this growing resource, however, depends upon the proper deep characterization of strain function, as even the best designed strain can display a variety of undesirable features that must be considered in experimental design. This must be coupled with the parallel development of informatics tools to provide functional data to the user and facilitated access to the strains through public repositories. We discuss the current progress on all of these fronts and the challenges that remain to ensure the scientific community can capitalize on the tremendous number of mouse resources at their disposal.

Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web ( http://www.geneontology.org ) are being constructed: biological process, molecular function and cellular component.

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. The cre- loxP system is widely used for the generation of conditional gene knockouts. Here Heffner et al. systematically characterize cre recombinase activity in tissues of embryonic and adult cre-driver mouse strains and provide an online resource for scientists.

Background Inferring gene-to-phenotype and gene-to-human disease model relationships from annotated mouse phenotypes and disease associations is critical when researching gene function and identifying candidate disease genes. Filtering the various kinds of genotypes to determine which phenotypes are caused by a mutation in a particular gene can be a laborious and time-consuming process. Methods At Mouse Genome Informatics (MGI, www.informatics.jax.org ), we have developed a gene annotation derivation algorithm that computes gene-to-phenotype and gene-to-disease annotations from our existing corpus of annotations to genotypes. This algorithm differentiates between simple genotypes with causative mutations in a single gene and more complex genotypes where mutations in multiple genes may contribute to the phenotype. As part of the process, alleles functioning as tools (e.g., reporters, recombinases) are filtered out. Results Using this algorithm derived gene-to-phenotype and gene-to-disease annotations were created for 16,000 and 2100 mouse markers, respectively, starting from over 57,900 and 4800 genotypes with at least one phenotype and disease annotation, respectively. Conclusions Implementation of this algorithm provides consistent and accurate gene annotations across MGI and provides a vital time-savings relative to manual annotation by curators.

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.

Technological advances have made possible the development of high-resolution genetic linkage maps for the mouse. These maps in turn offer exciting prospects for understanding mammalian genome evolution through comparative mapping, for developing mouse models of human disease, and for identifying the function of all genes in the organism.