Towards an encyclopaedia of mammalian gene function: the International Mouse Phenotyping Consortium

Delivering and phenotyping mouse models for the respiratory community: a report on the Biochemical Society Workshop

The IMPC (International Mouse Phenotyping Consortium) was launched recently, and its aim is to develop and phenotype mouse knockouts of 4000 genes over the next 5 years and, ultimately, of all 20000 or so genes in the mouse genome. As part of the IMPC, the MRC (Medical Research Council) also launched a call for MRC mouse networks, where groups of U.K.-based researchers could form a consortium based around a particular area of research. Members of the respiratory research community formed the RDDRC (Respiratory Development and Disease Research Consortium) to consolidate and develop respiratory phenotyping methods suitable for high-throughput screening. This paper, arising from a Biochemical Society workshop held in London in 2012, highlights the purposes of the RDDRC and the needs of the respiratory research community.

Bloomsbury report on mouse embryo phenotyping: recommendations from the IMPC workshop on embryonic lethal screening

Identifying genes that are important for embryo development is a crucial first step towards understanding their many functions in driving the ordered growth, differentiation and organogenesis of embryos. It can also shed light on the origins of developmental disease and congenital abnormalities. Current international efforts to examine gene function in the mouse provide a unique opportunity to pinpoint genes that are involved in embryogenesis, owing to the emergence of embryonic lethal knockout mutants. Through internationally coordinated efforts, the International Knockout Mouse Consortium (IKMC) has generated a public resource of mouse knockout strains and, in April 2012, the International Mouse Phenotyping Consortium (IMPC), supported by the EU InfraCoMP programme, convened a workshop to discuss developing a phenotyping pipeline for the investigation of embryonic lethal knockout lines. This workshop brought together over 100 scientists, from 13 countries, who are working in the academic and commercial research sectors, including experts and opinion leaders in the fields of embryology, animal imaging, data capture, quality control and annotation, high-throughput mouse production, phenotyping, and reporter gene analysis. This article summarises the outcome of the workshop, including (1) the vital scientific importance of phenotyping embryonic lethal mouse strains for basic and translational research; (2) a common framework to harmonise international efforts within this context; (3) the types of phenotyping that are likely to be most appropriate for systematic use, with a focus on 3D embryo imaging; (4) the importance of centralising data in a standardised form to facilitate data mining; and (5) the development of online tools to allow open access to and dissemination of the phenotyping data.

Controlling complexity: the clinical relevance of mouse complex genetics

Experimental animal models are essential to obtain basic knowledge of the underlying biological mechanisms in human diseases. Here, we review major contributions to biomedical research and discoveries that were obtained in the mouse model by using forward genetics approaches and that provided key insights into the biology of human diseases and paved the way for the development of novel therapeutic approaches.

Systematic analysis of experimental phenotype data reveals gene functions

High-throughput phenotyping projects in model organisms have the potential to improve our understanding of gene functions and their role in living organisms. We have developed a computational, knowledge-based approach to automatically infer gene functions from phenotypic manifestations and applied this approach to yeast (Saccharomyces cerevisiae), nematode worm (Caenorhabditis elegans), zebrafish (Danio rerio), fruitfly (Drosophila melanogaster) and mouse (Mus musculus) phenotypes. Our approach is based on the assumption that, if a mutation in a gene leads to a phenotypic abnormality in a process , then must have been involved in , either directly or indirectly. We systematically analyze recorded phenotypes in animal models using the formal definitions created for phenotype ontologies. We evaluate the validity of the inferred functions manually and by demonstrating a significant improvement in predicting genetic interactions and protein-protein interactions based on functional similarity. Our knowledge-based approach is generally applicable to phenotypes recorded in model organism databases, including phenotypes from large-scale, high throughput community projects whose primary mode of dissemination is direct publication on-line rather than in the literature.

Deciphering the Mechanisms of Developmental Disorders (DMDD): a new programme for phenotyping embryonic lethal mice

International efforts to test gene function in the mouse by the systematic knockout of each gene are creating many lines in which embryonic development is compromised. These homozygous lethal mutants represent a potential treasure trove for the biomedical community. Developmental biologists could exploit them in their studies of tissue differentiation and organogenesis; for clinical researchers they offer a powerful resource for investigating the origins of developmental diseases that affect newborns. Here, we outline a new programme of research in the UK aiming to kick-start research with embryonic lethal mouse lines. The ‘Deciphering the Mechanisms of Developmental Disorders’ (DMDD) programme has the ambitious goal of identifying all embryonic lethal knockout lines made in the UK over the next 5 years, and will use a combination of comprehensive imaging and transcriptomics to identify abnormalities in embryo structure and development. All data will be made freely available, enabling individual researchers to identify lines relevant to their research. The DMDD programme will coordinate its work with similar international efforts through the umbrella of the International Mouse Phenotyping Consortium [see accompanying Special Article (Adams et al., 2013)] and, together, these programmes will provide a novel database for embryonic development, linking gene identity with molecular profiles and morphology phenotypes.

Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research

Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species. We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases. This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.

Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research

Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species.

We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases.

This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.

Robust and sensitive analysis of mouse knockout phenotypes

A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student’s t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene’s function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained.

Differentiating inbred mouse strains from each other and those with single gene mutations using hair proteomics

Mutant laboratory mice with distinctive hair phenotypes are useful for identifying genes responsible for hair diseases. The work presented here demonstrates that shotgun proteomic profiling can distinguish hair shafts from different inbred mouse strains. For this purpose, analyzing the total hair shaft provided better discrimination than analyzing the isolated solubilized and particulate (cross-linked) fractions. Over 100 proteins exhibited significant differences among the 11 strains and 5 mutant stocks across the wide spectrum of strains surveyed. Effects on the profile of single gene mutations causing hair shaft defects were profound. Since the hair shaft provides a discrete sampling of the species proteome, with constituents serving important functions in epidermal appendages and throughout the body, this work provides a foundation for non-invasive diagnosis of genetic diseases of hair and perhaps other tissues.

From mice to humans

The genomes of many species have now been completely sequenced including human and mouse. Great progress has been made in understanding the complex genetics that underlie diabetes and obesity in human populations. One of the current challenges is the functional identification and characterization of the genes within loci that are being mapped. There are many approaches to this problem and this review outlines the valuable role that the mouse can play. We outline the mouse resources that are available to the research community, including knockouts with conditional potential for every gene, and the efforts of the International Mouse Phenotyping Consortium to attach phenotype information to these genes. We also briefly consider the potential of TALEN technology to tailor-make new mouse models of specific mutations discovered in humans. Finally, we consider the recent progress in characterizing the GWAS genes FTO, TCF7L2, CDKAL1, and SLC30A8 in engineered mouse models.

The mouse genome database: genotypes, phenotypes, and models of human disease

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.

Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish

Numerous disease syndromes are associated with regions of copy number variation (CNV) in the human genome and, in most cases, the pathogenicity of the CNV is thought to be related to altered dosage of the genes contained within the affected segment. However, establishing the contribution of individual genes to the overall pathogenicity of CNV syndromes is difficult and often relies on the identification of potential candidates through manual searches of the literature and online resources. We describe here the development of a computational framework to comprehensively search phenotypic information from model organisms and single-gene human hereditary disorders, and thus speed the interpretation of the complex phenotypes of CNV disorders. There are currently more than 5000 human genes about which nothing is known phenotypically but for which detailed phenotypic information for the mouse and/or zebrafish orthologs is available. Here, we present an ontology-based approach to identify similarities between human disease manifestations and the mutational phenotypes in characterized model organism genes; this approach can therefore be used even in cases where there is little or no information about the function of the human genes. We applied this algorithm to detect candidate genes for 27 recurrent CNV disorders and identified 802 gene-phenotype associations, approximately half of which involved genes that were previously reported to be associated with individual phenotypic features and half of which were novel candidates. A total of 431 associations were made solely on the basis of model organism phenotype data. Additionally, we observed a striking, statistically significant tendency for individual disease phenotypes to be associated with multiple genes located within a single CNV region, a phenomenon that we denote as pheno-clustering. Many of the clusters also display statistically significant similarities in protein function or vicinity within the protein-protein interaction network. Our results provide a basis for understanding previously un-interpretable genotype-phenotype correlations in pathogenic CNVs and for mobilizing the large amount of model organism phenotype data to provide insights into human genetic disorders.

After GWAS: mice to the rescue?

The genetic basis of human autoimmune diseases remains incompletely understood, despite significant progress from genome-wide association studies (GWAS). In this review we outline how studies in mice may help filling these knowledge gaps. Forward genetic approaches including mutagenesis screens and quantitative trait locus (QTL) mapping studies can identify candidate genes for in depth analysis in human patient populations. Reverse genetic approaches utilize genetically engineered mice to analyze the function of disease-associated genes and their variants. Inbred strains are a distinctive feature of mouse genetics and we discuss their history, advantages and disadvantages. Three factors need to be considered when comparing experimental results from studies in mice and humans: In addition to species-specific differences, phenotypes are affected by the genetic background of the mouse strain being analyzed, and by microbial factors. Despite of these complexities, mice are essential discovery tools in the post GWAS era.

Accessing data from the International Mouse Phenotyping Consortium: state of the art and future plans

The International Mouse Phenotyping Consortium (IMPC) (http://www.mousephenotype.org) will reveal the pleiotropic functions of every gene in the mouse genome and uncover the wider role of genetic loci within diverse biological systems. Comprehensive informatics solutions are vital to ensuring that this vast array of data is captured in a standardised manner and made accessible to the scientific community for interrogation and analysis. Here we review the existing EuroPhenome and WTSI phenotype informatics systems and the IKMC portal, and present plans for extending these systems and lessons learned to the development of a robust IMPC informatics infrastructure.

Immunization with live virus vaccine protects highly susceptible DBA/2J mice from lethal influenza A H1N1 infection

BACKGROUND

The mouse represents an important model system to study the host response to influenza A infections and to evaluate new prevention or treatment strategies. We and others reported that the susceptibility to influenza A virus infections strongly varies among different inbred mouse strains. In particular, DBA/2J mice are highly susceptible to several influenza A subtypes, including human isolates and exhibit severe symptoms after infection with clinical isolates.

FINDINGS

Upon intra-muscular immunization with live H1N1 influenza A virus (mouse-adapted PR8M, and 2009 pandemic human HA04), DBA/2J mice mounted virus-specific IgG responses and were protected against a subsequent lethal challenge. The immune response and rescue from death after immunization in DBA/2J was similar to those observed for C57BL/6J mice.

CONCLUSIONS

DBA/2J mice represent a suitable mouse model to evaluate virulence and pathogenicity as well as immunization regimes against existing and newly emerging human influenza strains without the need for prior adaptation of the virus to the mouse.

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.

Computational tools for comparative phenomics: the role and promise of ontologies

A major aim of the biological sciences is to gain an understanding of human physiology and disease. One important step towards such a goal is the discovery of the function of genes that will lead to a better understanding of the physiology and pathophysiology of organisms, which will ultimately lead to better diagnosis and therapy. Our increasing ability to phenotypically characterise genetic variants of model organisms coupled with systematic and hypothesis-driven mutagenesis is resulting in a wealth of information that could potentially provide insight into the functions of all genes in an organism. The challenge we are now facing is to develop computational methods that can integrate and analyse such data. The introduction of formal ontologies that make their semantics explicit and accessible to automated reasoning provides the tantalizing possibility of standardizing biomedical knowledge allowing for novel, powerful queries that bridge multiple domains, disciplines, species, and levels of granularity. We review recent computational approaches that facilitate the integration of experimental data from model organisms with clinical observations in humans. These methods foster novel cross-species analysis approaches, thereby enabling comparative phenomics and leading to the potential of translating basic discoveries from the model systems into diagnostic and therapeutic advances at the clinical level.