Mouse Phenotype Database Integration Consortium: integration [corrected] of mouse phenome data resources

Reproducibility and replicability of rodent phenotyping in preclinical studies

The scientific community is increasingly concerned with the proportion of published “discoveries” that are not replicated in subsequent studies. The field of rodent behavioral phenotyping was one of the first to raise this concern, and to relate it to other methodological issues: the complex interaction between genotype and environment; the definitions of behavioral constructs; and the use of laboratory mice and rats as model species for investigating human health and disease mechanisms. In January 2015, researchers from various disciplines gathered at Tel Aviv University to discuss these issues. The general consensus was that the issue is prevalent and of concern, and should be addressed at the statistical, methodological and policy levels, but is not so severe as to call into question the validity and the usefulness of model organisms as a whole. Well-organized community efforts, coupled with improved data and metadata sharing, have a key role in identifying specific problems and promoting effective solutions. Replicability is closely related to validity, may affect generalizability and translation of findings, and has important ethical implications.

The digital revolution in phenotyping

Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application in numerous areas such as the discovery of disease genes and drug targets, phylogenetics and pharmacogenomics. Phenotypes, defined as observable characteristics of organisms, can be seen as one of the bridges that lead to a translation of experimental findings into clinical applications and thereby support 'bench to bedside' efforts. However, to build this translational bridge, a common and universal understanding of phenotypes is required that goes beyond domain-specific definitions. To achieve this ambitious goal, a digital revolution is ongoing that enables the encoding of data in computer-readable formats and the data storage in specialized repositories, ready for integration, enabling translational research. While phenome research is an ongoing endeavor, the true potential hidden in the currently available data still needs to be unlocked, offering exciting opportunities for the forthcoming years. Here, we provide insights into the state-of-the-art in digital phenotyping, by means of representing, acquiring and analyzing phenotype data. In addition, we provide visions of this field for future research work that could enable better applications of phenotype data.

De Novo Assembly of the Donkey White Blood Cell Transcriptome and a Comparative Analysis of Phenotype-Associated Genes between Donkeys and Horses

Prior to the mechanization of agriculture and labor-intensive tasks, humans used donkeys (Equus africanus asinus) for farm work and packing. However, as mechanization increased, donkeys have been increasingly raised for meat, milk, and fur in China. To maintain the development of the donkey industry, breeding programs should focus on traits related to these new uses. Compared to conventional marker-assisted breeding plans, genome- and transcriptome-based selection methods are more efficient and effective. To analyze the coding genes of the donkey genome, we assembled the transcriptome of donkey white blood cells de novo. Using transcriptomic deep-sequencing data, we identified 264,714 distinct donkey unigenes and predicted 38,949 protein fragments. We annotated the donkey unigenes by BLAST searches against the non-redundant (NR) protein database. We also compared the donkey protein sequences with those of the horse (E. caballus) and wild horse (E. przewalskii), and linked the donkey protein fragments with mammalian phenotypes. As the outer ear size of donkeys and horses are obviously different, we compared the outer ear size-associated proteins in donkeys and horses. We identified three ear size-associated proteins, HIC1, PRKRA, and KMT2A, with sequence differences among the donkey, horse, and wild horse loci. Since the donkey genome sequence has not been released, the de novo assembled donkey transcriptome is helpful for preliminary investigations of donkey cultivars and for genetic improvement.

Disruption of mouse Cenpj, a regulator of centriole biogenesis, phenocopies Seckel syndrome

Disruption of the centromere protein J gene, CENPJ (CPAP, MCPH6, SCKL4), which is a highly conserved and ubiquitiously expressed centrosomal protein, has been associated with primary microcephaly and the microcephalic primordial dwarfism disorder Seckel syndrome. The mechanism by which disruption of CENPJ causes the proportionate, primordial growth failure that is characteristic of Seckel syndrome is unknown. By generating a hypomorphic allele of Cenpj, we have developed a mouse (Cenpj(tm/tm)) that recapitulates many of the clinical features of Seckel syndrome, including intrauterine dwarfism, microcephaly with memory impairment, ossification defects, and ocular and skeletal abnormalities, thus providing clear confirmation that specific mutations of CENPJ can cause Seckel syndrome. Immunohistochemistry revealed increased levels of DNA damage and apoptosis throughout Cenpj(tm/tm) embryos and adult mice showed an elevated frequency of micronucleus induction, suggesting that Cenpj-deficiency results in genomic instability. Notably, however, genomic instability was not the result of defective ATR-dependent DNA damage signaling, as is the case for the majority of genes associated with Seckel syndrome. Instead, Cenpj(tm/tm) embryonic fibroblasts exhibited irregular centriole and centrosome numbers and mono- and multipolar spindles, and many were near-tetraploid with numerical and structural chromosomal abnormalities when compared to passage-matched wild-type cells. Increased cell death due to mitotic failure during embryonic development is likely to contribute to the proportionate dwarfism that is associated with CENPJ-Seckel syndrome.

Genome-wide association studies in mice

Genome-wide association studies (GWASs) have transformed the field of human genetics and have led to the discovery of hundreds of genes that are implicated in human disease. The technological advances that drove this revolution are now poised to transform genetic studies in model organisms, including mice. However, the design of GWASs in mouse strains is fundamentally different from the design of human GWASs, creating new challenges and opportunities. This Review gives an overview of the novel study designs for mouse GWASs, which dramatically improve both the statistical power and resolution compared to classical gene-mapping approaches.

Large-scale mouse knockouts and phenotypes

Standardized phenotypic analysis of mutant forms of every gene in the mouse genome will provide fundamental insights into mammalian gene function and advance human and animal health. The availability of the human and mouse genome sequences, the development of embryonic stem cell mutagenesis technology, the standardization of phenotypic analysis pipelines, and the paradigm-shifting industrialization of these processes have made this a realistic and achievable goal. The size of this enterprise will require global coordination to ensure economies of scale in both the generation and primary phenotypic analysis of the mutant strains, and to minimize unnecessary duplication of effort. To provide more depth to the functional annotation of the genome, effective mechanisms will also need to be developed to disseminate the information and resources produced to the wider community. Better models of disease, potential new drug targets with novel mechanisms of action, and completely unsuspected genotype-phenotype relationships covering broad aspects of biology will become apparent. To reach these goals, solutions to challenges in mouse production and distribution, as well as development of novel, ever more powerful phenotypic analysis modalities will be necessary. It is a challenging and exciting time to work in mouse genetics.

Roles and applications of biomedical ontologies in experimental animal science

A huge amount of experimental data from past studies has played a vital role in the development of new knowledge and technologies in biomedical science. The importance of computational technologies for the reuse of data, data integration, and knowledge discoveries has also increased, providing means of processing large amounts of data. In recent years, information technologies related to "ontologies" have played more significant roles in the standardization, integration, and knowledge representation of biomedical information. This review paper outlines the history of data integration in biomedical science and its recent trends in relation to the field of experimental animal science.

Three ontologies to define phenotype measurement data

BACKGROUND

There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol.

RESULTS

Three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository.

CONCLUSION

An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies.

Research resources: curating the new eagle-i discovery system

Development of biocuration processes and guidelines for new data types or projects is a challenging task. Each project finds its way toward defining annotation standards and ensuring data consistency with varying degrees of planning and different tools to support and/or report on consistency. Further, this process may be data type specific even within the context of a single project. This article describes our experiences with eagle-i, a 2-year pilot project to develop a federated network of data repositories in which unpublished, unshared or otherwise ‘invisible’ scientific resources could be inventoried and made accessible to the scientific community. During the course of eagle-i development, the main challenges we experienced related to the difficulty of collecting and curating data while the system and the data model were simultaneously built, and a deficiency and diversity of data management strategies in the laboratories from which the source data was obtained. We discuss our approach to biocuration and the importance of improving information management strategies to the research process, specifically with regard to the inventorying and usage of research resources. Finally, we highlight the commonalities and differences between eagle-i and similar efforts with the hope that our lessons learned will assist other biocuration endeavors.

Database URL:www.eagle-i.net

Strategies and methods to study sex differences in cardiovascular structure and function: a guide for basic scientists

Background

Cardiovascular disease remains the primary cause of death worldwide. In the US, deaths due to cardiovascular disease for women exceed those of men. While cultural and psychosocial factors such as education, economic status, marital status and access to healthcare contribute to sex differences in adverse outcomes, physiological and molecular bases of differences between women and men that contribute to development of cardiovascular disease and response to therapy remain underexplored.

Methods

This article describes concepts, methods and procedures to assist in the design of animal and tissue/cell based studies of sex differences in cardiovascular structure, function and models of disease.

Results

To address knowledge gaps, study designs must incorporate appropriate experimental material including species/strain characteristics, sex and hormonal status. Determining whether a sex difference exists in a trait must take into account the reproductive status and history of the animal including those used for tissue (cell) harvest, such as the presence of gonadal steroids at the time of testing, during development or number of pregnancies. When selecting the type of experimental animal, additional consideration should be given to diet requirements (soy or plant based influencing consumption of phytoestrogen), lifespan, frequency of estrous cycle in females, and ability to investigate developmental or environmental components of disease modulation. Stress imposed by disruption of sleep/wake cycles, patterns of social interaction (or degree of social isolation), or handling may influence adrenal hormones that interact with pathways activated by the sex steroid hormones. Care must be given to selection of hormonal treatment and route of administration.

Conclusions

Accounting for sex in the design and interpretation of studies including pharmacological effects of drugs is essential to increase the foundation of basic knowledge upon which to build translational approaches to prevent, diagnose and treat cardiovascular diseases in humans.

Experimental models for anxiolytic drug discovery in the era of omes and omics

INTRODUCTION

Animal behavioral models have become an indispensable tool for studying anxiety disorders and testing anxiety-modulating drugs. However, significant methodological and conceptual challenges affect the translational validity and accurate behavioral dissection in such models. They are also often limited to individual behavioral domains and fail to target the disorder's real clinical picture (its spectrum or overlap with other disorders), which hinder screening and development of novel anxiolytic drugs.

AREAS COVERED

In this article, the authors discuss and emphasize the importance of high-throughput multi-domain neurophenotyping based on the latest developments in video-tracking and bioinformatics. Additionally, the authors also explain how bioinformatics can provide new insight into the neural substrates of brain disorders and its benefit for drug discovery.

EXPERT OPINION

The throughput and utility of animal models of anxiety and other brain disorders can be markedly increased by a number of ways: i) analyzing systems of several domains and their interplay in a wider spectrum of model species; ii) using a larger number of end points generated by video-tracking tools; iii) correlating behavioral data with genomic, proteomic and other physiologically relevant markers using online databases and iv) creating molecular network-based models of anxiety to identify new targets for drug design and discovery. Experimental models utilizing bioinformatics tools and online databases will not only improve our understanding of both gene-behavior interactions and complex trait interconnectivity but also highlight new targets for novel anxiolytic drugs.

Establishing a knowledge trail from molecular experiments to clinical trials

During the development cycle of a new antibody therapy, the therapeutic agent will be tested on subsequently more biologically complex models. New experiments' designs are based upon data gathered from prior models. New researchers who inherit the data and researchers from groups with different cultures or expertise are often called upon to interpret these data. Experiments which are not recorded consistently or employ ambiguous terminology can make interpreting these results difficult. The researcher who had originally collected the data may not be at hand to correct any misunderstanding or offer clarification and data can be unknowingly misused. This introduces an element of risk into the therapy development process. We have developed a reporting guideline for recording therapy experiments. This guideline consists of a checklist of data to be recorded from antibody therapy experiments performed in molecular, cellular, animal and clinical model.

Disruption of mouse Slx4, a regulator of structure-specific nucleases, phenocopies Fanconi anemia

The evolutionarily conserved SLX4 protein, a key regulator of nucleases, is critical for DNA damage response. SLX4 nuclease complexes mediate repair during replication and can also resolve Holliday junctions formed during homologous recombination. Here we describe the phenotype of the Btbd12 knockout mouse, the mouse ortholog of SLX4, which recapitulates many key features of the human genetic illness Fanconi anemia. Btbd12-deficient animals are born at sub-Mendelian ratios, have greatly reduced fertility, are developmentally compromised and are prone to blood cytopenias. Btbd12(-/-) cells prematurely senesce, spontaneously accumulate damaged chromosomes and are particularly sensitive to DNA crosslinking agents. Genetic complementation reveals a crucial requirement for Btbd12 (also known as Slx4) to interact with the structure-specific endonuclease Xpf-Ercc1 to promote crosslink repair. The Btbd12 knockout mouse therefore establishes a disease model for Fanconi anemia and genetically links a regulator of nuclease incision complexes to the Fanconi anemia DNA crosslink repair pathway.

Meeting Report from the Second "Minimum Information for Biological and Biomedical Investigations" (MIBBI) workshop

This report summarizes the proceedings of the second workshop of the 'Minimum Information for Biological and Biomedical Investigations' (MIBBI) consortium held on Dec 1-2, 2010 in Rüdesheim, Germany through the sponsorship of the Beilstein-Institute. MIBBI is an umbrella organization uniting communities developing Minimum Information (MI) checklists to standardize the description of data sets, the workflows by which they were generated and the scientific context for the work. This workshop brought together representatives of more than twenty communities to present the status of their MI checklists and plans for future development. Shared challenges and solutions were identified and the role of MIBBI in MI checklist development was discussed. The meeting featured some thirty presentations, wide-ranging discussions and breakout groups. The top outcomes of the two-day workshop as defined by the participants were: 1) the chance to share best practices and to identify areas of synergy; 2) defining a series of tasks for updating the MIBBI Portal; 3) reemphasizing the need to maintain independent MI checklists for various communities while leveraging common terms and workflow elements contained in multiple checklists; and 4) revision of the concept of the MIBBI Foundry to focus on the creation of a core set of MIBBI modules intended for reuse by individual MI checklist projects while maintaining the integrity of each MI project. Further information about MIBBI and its range of activities can be found at http://mibbi.org/.

High-throughput mouse phenotyping

Comprehensive phenotyping will be required to reveal the pleiotropic functions of a gene and to uncover the wider role of genetic loci within diverse biological systems. The challenge will be to devise phenotyping approaches to characterise the thousands of mutants that are being generated as part of international efforts to acquire a mutant for every gene in the mouse genome. In order to acquire robust datasets of broad based phenotypes from mouse mutants it is necessary to design and implement pipelines that incorporate standardised phenotyping platforms that are validated across diverse mouse genetics centres or mouse clinics. We describe here the rationale and methodology behind one phenotyping pipeline, EMPReSSslim, that was designed as part of the work of the EUMORPHIA and EUMODIC consortia, and which exemplifies some of the challenges facing large-scale phenotyping. EMPReSSslim captures a broad range of data on diverse biological systems, from biochemical to physiological amongst others. Data capture and dissemination is pivotal to the operation of large-scale phenotyping pipelines, including the definition of parameters integral to each phenotyping test and the associated ontological descriptions. EMPReSSslim data is displayed within the EuroPhenome database, where a variety of tools are available to allow the user to search for interesting biological or clinical phenotypes.

The RIKEN integrated database of mammals

The RIKEN integrated database of mammals (http://scinets.org/db/mammal) is the official undertaking to integrate its mammalian databases produced from multiple large-scale programs that have been promoted by the institute. The database integrates not only RIKEN's original databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists' Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information.

Mouse models in male fertility research

Limited knowledge of the genetic causes of male infertility has resulted in few treatment and targeted therapeutic options. Although the ideal approach to identify infertility causing mutations is to conduct studies in the human population, this approach has progressed slowly due to the limitations described herein. Given the complexity of male fertility, the entire process cannot be modeled in vitro. As such, animal models, in particular mouse models, provide a valuable alternative for gene identification and experimentation. Since the introduction of molecular biology and recent advances in animal model production, there has been a substantial acceleration in the identification and characterization of genes associated with many diseases, including infertility. Three major types of mouse models are commonly used in biomedical research, including knockout/knockin/gene-trapped, transgenic and chemical-induced point mutant mice. Using these mouse models, over 400 genes essential for male fertility have been revealed. It has, however, been estimated that thousands of genes are involved in the regulation of the complex process of male fertility, as many such genes remain to be characterized. The current review is by no means a comprehensive list of these mouse models, rather it contains examples of how mouse models have advanced our knowledge of post-natal germ cell development and male fertility regulation.

Mouse phenogenomics, toolbox for functional annotation of human genome

Mouse models are crucial for the functional annotation of human genome. Gene modification techniques including gene targeting and gene trap in mouse have provided powerful tools in the form of genetically engineered mice (GEM) for understanding the molecular pathogenesis of human diseases. Several international consortium and programs are under way to deliver mutations in every gene in mouse genome. The information from studying these GEM can be shared through international collaboration. However, there are many limitations in utility because not all human genes are knocked out in mouse and they are not yet phenotypically characterized by standardized ways which is required for sharing and evaluating data from GEM. The recent improvement in mouse genetics has now moved the bottleneck in mouse functional genomics from the production of GEM to the systematic mouse phenotype analysis of GEM. Enhanced, reproducible and comprehensive mouse phenotype analysis has thus emerged as a prerequisite for effectively engaging the phenotyping bottleneck. In this review, current information on systematic mouse phenotype analysis and an issue-oriented perspective will be provided.

A MOD(ern) perspective on literature curation

Curation of biological data is a multi-faceted task whose goal is to create a structured, comprehensive, integrated, and accurate resource of current biological knowledge. These structured data facilitate the work of the scientific community by providing knowledge about genes or genomes and by generating validated connections between the data that yield new information and stimulate new research approaches. For the model organism databases (MODs), an important source of data is research publications. Every published paper containing experimental information about a particular model organism is a candidate for curation. All such papers are examined carefully by curators for relevant information. Here, four curators from different MODs describe the literature curation process and highlight approaches taken by the four MODs to address: (1) the decision process by which papers are selected, and (2) the identification and prioritization of the data contained in the paper. We will highlight some of the challenges that MOD biocurators face, and point to ways in which researchers and publishers can support the work of biocurators and the value of such support.

Towards better mouse models: enhanced genotypes, systemic phenotyping and envirotype modelling

The mouse is the leading mammalian model organism for basic genetic research and for studying human diseases. Coordinated international projects are currently in progress to generate a comprehensive map of mouse gene functions - the first for any mammalian genome. There are still many challenges ahead to maximize the value of the mouse as a model, particularly for human disease. These involve generating mice that are better models of human diseases at the genotypic level, systemic (assessing all organ systems) and systematic (analysing all mouse lines) phenotyping of existing and new mouse mutant resources, and assessing the effects of the environment on phenotypes.

SDOP-DB: a comparative standardized-protocol database for mouse phenotypic analyses

Summary: This article reports the development of SDOP-DB, which can provide definite, detailed and easy comparison of experimental protocols used in mouse phenotypic analyses among institutes or laboratories. Because SDOP-DB is fully compliant with international standards, it can act as a practical foundation for international sharing and integration of mouse phenotypic information.

Availability: SDOP-DB (http://www.brc.riken.jp/lab/bpmp/SDOP/)

Contact:hmasuya@brc.riken.jp

Supplementary information:Supplementary data are available at Bioinformatics online.

Brain distribution of genes related to changes in locomotor activity

The relationship between genes and behavior, and particularly the hyperactive behavior, is clearly not linear nor monotonic. To address this problem, a database of the locomotor behavior obtained from thousands of mutant mice has been previously retrieved from the literature. Data showed that the percent of genes in the genome related to locomotor hyperactivity is probably more than 1.56%. These genes do not belong to a single neurotransmitter system or biochemical pathway. Indeed, they are probably required for the correct development of a specific neuronal network necessary to decrease locomotor activity. The present paper analyzes the brain expression pattern of the genes whose deletion is accompanied by changes in locomotor behavior. Using literature data concerning knockout mice, 46 genes whose deletion was accompanied by increased locomotor behavior, 24 genes related to decreased locomotor behavior and 23 genes not involved in locomotor behavior (but important for other brain functions) have been identified. These three groups of genes belonged to overlapping neurotransmitter systems or cellular functions. Therefore, we postulated that a better predictor of the locomotor behavior resulting from gene deletion might be the brain expression pattern. To this aim we correlated the brain expression of the genes and the locomotor activity resulting from the deletion of the same genes, using two databases (Allen Brain Atlas and SymAtlas). The results showed that the deletion of genes with higher expression level in the brain had higher probability to be accompanied by increased behavioral activity. Moreover the genes that were accompanied by locomotor hyperactivity when deleted, were more expressed in the cerebral cortex, amygdala and hippocampus compared to the genes unrelated to locomotor activity. Therefore, the prediction of the behavioral effect of a gene should take into consideration its brain distribution. Moreover, data confirmed that genes highly expressed in the brain are more likely to induce hyperactivity when deleted. Finally, it is suggested that gene mutations linked to specific behavioral abnormalities (e.g. inattention) might probably be associated to hyperactivity if the same gene has elevated brain expression.

Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information

Background

The genetic contributions to human common disorders and mouse genetic models of disease are complex and often overlapping. In common human diseases, unlike classical Mendelian disorders, genetic factors generally have small effect sizes, are multifactorial, and are highly pleiotropic. Likewise, mouse genetic models of disease often have pleiotropic and overlapping phenotypes. Moreover, phenotypic descriptions in the literature in both human and mouse are often poorly characterized and difficult to compare directly.

Methods

In this report, human genetic association results from the literature are summarized with regard to replication, disease phenotype, and gene specific results; and organized in the context of a systematic disease ontology. Similarly summarized mouse genetic disease models are organized within the Mammalian Phenotype ontology. Human and mouse disease and phenotype based gene sets are identified. These disease gene sets are then compared individually and in large groups through dendrogram analysis and hierarchical clustering analysis.

Results

Human disease and mouse phenotype gene sets are shown to group into disease and phenotypically relevant groups at both a coarse and fine level based on gene sharing.

Conclusion

This analysis provides a systematic and global perspective on the genetics of common human disease as compared to itself and in the context of mouse genetic models of disease.

The functional annotation of mammalian genomes: the challenge of phenotyping

The mouse is central to the goal of establishing a comprehensive functional annotation of the mammalian genome that will help elucidate various human disease genes and pathways. The mouse offers a unique combination of attributes, including an extensive genetic toolkit that underpins the creation and analysis of models of human disease. An international effort to generate mutations for every gene in the mouse genome is a first and essential step in this endeavor. However, the greater challenge will be the determination of the phenotype of every mutant. Large-scale phenotyping for genome-wide functional annotation presents numerous scientific, infrastructural, logistical, and informatics challenges. These include the use of standardized approaches to phenotyping procedures for the population of unified databases with comparable data sets. The ultimate goal is a comprehensive database of molecular interventions that allows us to create a framework for biological systems analysis in the mouse on which human biology and disease networks can be revealed.

MouseBook: an integrated portal of mouse resources

The MouseBook (http://www.mousebook.org) databases and web portal provide access to information about mutant mouse lines held as live or cryopreserved stocks at MRC Harwell. The MouseBook portal integrates curated information from the MRC Harwell stock resource, and other Harwell databases, with information from external data resources to provide value-added information above and beyond what is available through other routes such as International Mouse Stain Resource (IMSR). MouseBook can be searched either using an intuitive Google style free text search or using the Mammalian Phenotype (MP) ontology tree structure. Text searches can be on gene, allele, strain identifier (e.g. MGI ID) or phenotype term and are assisted by automatic recognition of term types and autocompletion of gene and allele names covered by the database. Results are returned in a tabbed format providing categorized results identified from each of the catalogs in MouseBook. Individual result lines from each catalog include information on gene, allele, chromosomal location and phenotype, and provide a simple click-through link to further information as well as ordering the strain. The infrastructure underlying MouseBook has been designed to be extensible, allowing additional data sources to be added and enabling other sites to make their data directly available through MouseBook.

Mouse, man, and meaning: bridging the semantics of mouse phenotype and human disease

Now that the laboratory mouse genome is sequenced and the annotation of its gene content is improving, the next major challenge is the annotation of the phenotypic associations of mouse genes. This requires the development of systematic phenotyping pipelines that use standardized phenotyping procedures which allow comparison across laboratories. It also requires the development of a sophisticated informatics infrastructure for the description and interchange of phenotype data. Here we focus on the current state of the art in the description of data produced by systematic phenotyping approaches using ontologies, in particular, the EQ (Entity-Quality) approach, and what developments are required to facilitate the linking of phenotypic descriptions of mutant mice to human diseases.

Solutions for data integration in functional genomics: a critical assessment and case study

The torrent of data emerging from the application of new technologies to functional genomics and systems biology can no longer be contained within the traditional modes of data sharing and publication with the consequence that data is being deposited in, distributed across and disseminated through an increasing number of databases. The resulting fragmentation poses serious problems for the model organism community which increasingly rely on data mining and computational approaches that require gathering of data from a range of sources. In the light of these problems, the European Commission has funded a coordination action, CASIMIR (coordination and sustainability of international mouse informatics resources), with a remit to assess the technical and social aspects of database interoperability that currently prevent the full realization of the potential of data integration in mouse functional genomics. In this article, we assess the current problems with interoperability, with particular reference to mouse functional genomics, and critically review the technologies that can be deployed to overcome them. We describe a typical use-case where an investigator wishes to gather data on variation, genomic context and metabolic pathway involvement for genes discovered in a genome-wide screen. We go on to develop an automated approach involving an in silico experimental workflow tool, Taverna, using web services, BioMart and MOLGENIS technologies for data retrieval. Finally, we focus on the current impediments to adopting such an approach in a wider context, and strategies to overcome them.

Systemic first-line phenotyping

With the completion of the mouse genome sequence an essential task for biomedical sciences in the twenty-first century will be the generation and functional analysis of mouse models for every gene in the mammalian genome. More than 30,000 mutations in ES cells will be engineered and thousands of mouse disease models will become available over the coming years by the collaborative effort of the International Mouse Knockout Consortium. In order to realize the full value of the mouse models proper characterization, archiving and dissemination of mouse disease models to the research community have to be performed. Phenotyping centers (mouse clinics) provide the necessary capacity, broad expertise, equipment, and infrastructure to carry out large-scale systemic first-line phenotyping. Using the example of the German Mouse Clinic (GMC) we will introduce the reader to the different aspects of the organization of a mouse clinic and present selected methods used in first-line phenotyping.

Mouse phenome database

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is an open source, web-based repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice and their derivatives. MPD is also a facility for query, analysis and in silico hypothesis testing. Currently MPD contains about 1400 phenotypic measurements contributed by research teams worldwide, including phenotypes relevant to human health such as cancer susceptibility, aging, obesity, susceptibility to infectious diseases, atherosclerosis, blood disorders and neurosensory disorders. Electronic access to centralized strain data enables investigators to select optimal strains for many systems-based research applications, including physiological studies, drug and toxicology testing, modeling disease processes and complex trait analysis. The ability to select strains for specific research applications by accessing existing phenotype data can bypass the need to (re)characterize strains, precluding major investments of time and resources. This functionality, in turn, accelerates research and leverages existing community resources. Since our last NAR reporting in 2007, MPD has added more community-contributed data covering more phenotypic domains and implemented several new tools and features, including a new interactive Tool Demo available through the MPD homepage (quick link: http://phenome.jax.org/phenome/trytools).

Integrating mouse anatomy and pathology ontologies into a phenotyping database: tools for data capture and training

The Mouse Disease Information System (MoDIS) is a data capture system for pathology data from laboratory mice designed to support phenotyping studies. The system integrates the mouse anatomy (MA) and mouse pathology (MPATH) ontologies into a Microsoft Access database facilitating the coding of organ, tissue, and disease process to recognized semantic standards. Grading of disease severity provides scores for all lesions that can then be used for quantitative trait locus (QTL) analyses and haplotype association gene mapping. Direct linkage to the Pathbase online database provides reference definitions for disease terms and access to photomicrographic images of similar diagnoses in other mutant mice. MoDIS is an open source and freely available program (http://research.jax.org/faculty/sundberg/index.html). This provides a valuable tool for setting up a mouse pathology phenotyping program.

Phenosite: a web database integrating the mouse phenotyping platform and the experimental procedures in mice

Recently, a number of collaborative large-scale mouse mutagenesis programs have been launched. These programs aim for a better understanding of the roles of all individual coding genes and the biological systems in which these genes participate. In international efforts to share phenotypic data among facilities/institutes, it is desirable to integrate information obtained from different phenotypic platforms reliably. Since the definitions of specific phenotypes often depend on a tacit understanding of concepts that tends to vary among different facilities, it is necessary to define phenotypes based on the explicit evidence of assay results. We have developed a website termed PhenoSITE (Phenome Semantics Information with Terminology of Experiments: http://www.gsc.riken.jp/Mouse/), in which we are trying to integrate phenotype-related information using an experimental-evidence-based approach. The site's features include (1) a baseline database for our phenotyping platform; (2) an ontology associating international phenotypic definitions with experimental terminologies used in our phenotyping platform; (3) a database for standardized operation procedures of the phenotyping platform; and (4) a database for mouse mutants using data produced from the large-scale mutagenesis program at RIKEN GSC. We have developed two types of integrated viewers to enhance the accessibility to mutant resource information. One viewer depicts a matrix view of the ontology-based classification and chromosomal location of each gene; the other depicts ontology-mediated integration of experimental protocols, baseline data, and mutant information. These approaches rely entirely upon experiment-based evidence, ensuring the reliability of the integrated data from different phenotyping platforms.

EuroPhenome and EMPReSS: online mouse phenotyping resource

EuroPhenome (http://www.europhenome.org) and EMPReSS (http://empress.har.mrc.ac.uk/) form an integrated resource to provide access to data and procedures for mouse phenotyping. EMPReSS describes 96 Standard Operating Procedures for mouse phenotyping. EuroPhenome contains data resulting from carrying out EMPReSS protocols on four inbred laboratory mouse strains. As well as web interfaces, both resources support web services to enable integration with other mouse phenotyping and functional genetics resources, and are committed to initiatives to improve integration of mouse phenotype databases. EuroPhenome will be the repository for a recently initiated effort to carry out large-scale phenotyping on a large number of knockout mouse lines (EUMODIC).

Phenostat: visualization and statistical tool for analysis of phenotyping data

The effective extraction of information from multidimensional data sets derived from phenotyping experiments is a growing challenge in biology. Data visualization tools are important resources that can aid in exploratory data analysis of complex data sets. Phenotyping experiments of model organisms produce data sets in which a large number of phenotypic measures are collected for each individual in a group. A critical initial step in the analysis of such multidimensional data sets is the exploratory analysis of data distribution and correlation. To facilitate the rapid visualization and exploratory analysis of multidimensional complex trait data, we have developed a user-friendly, web-based software tool called Phenostat. Phenostat is composed of a dynamic graphical environment that allows the user to inspect the distribution of multiple variables in a data set simultaneously. Individuals can be selected by directly clicking on the graphs and thus displaying their identity, highlighting corresponding values in all graphs, allowing their inclusion or exclusion from the analysis. Statistical analysis is provided by R package functions. Phenostat is particularly suited for rapid distribution and correlation analysis of subsets of data. An analysis of behavioral and physiologic data stemming from a large mouse phenotyping experiment using Phenostat reveals previously unsuspected correlations. Phenostat is freely available to academic institutions and nonprofit organizations and can be used from our website at: (http://www.bioinfo.embl.it/phenostat/).