New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models

Bridging mouse and human anatomies; a knowledge-based approach to comparative anatomy for disease model phenotyping

The laboratory mouse is the foremost mammalian model used for studying human diseases and is closely anatomically related to humans. Whilst knowledge about human anatomy has been collected throughout the history of mankind, the first comprehensive study of the mouse anatomy was published less than 60 years ago. This has been followed by the more recent publication of several books and resources on mouse anatomy. Nevertheless, to date, our understanding and knowledge of mouse anatomy is far from being at the same level as that of humans. In addition, the alignment between current mouse and human anatomy nomenclatures is far from being as developed as those existing between other species, such as domestic animals and humans. To close this gap, more in depth mouse anatomical research is needed and it will be necessary to extent and refine the current vocabulary of mouse anatomical terms.

PAX6 disease models for aniridia

Aniridia is a pan-ocular genetic developmental eye disorder characterized by complete or partial iris and foveal hypoplasia, for which there is no treatment currently. Progressive sight loss can arise from cataracts, glaucoma, and aniridia-related keratopathy, which can be managed conservatively or through surgical intervention. The vast majority of patients harbor heterozygous mutations involving the PAX6 gene, which is considered the master transcription factor of early eye development. Over the past decades, several disease models have been investigated to gain a better understanding of the molecular pathophysiology, including several mouse and zebrafish strains and, more recently, human-induced pluripotent stem cells (hiPSCs) derived from aniridia patients. The latter provides a more faithful cellular system to study early human eye development. This review outlines the main aniridia-related animal and cellular models used to study aniridia and highlights the key discoveries that are bringing us closer to a therapy for patients.

The anatomy of phenotype ontologies: principles, properties and applications

The past decade has seen an explosion in the collection of genotype data in domains as diverse as medicine, ecology, livestock and plant breeding. Along with this comes the challenge of dealing with the related phenotype data, which is not only large but also highly multidimensional. Computational analysis of phenotypes has therefore become critical for our ability to understand the biological meaning of genomic data in the biological sciences. At the heart of computational phenotype analysis are the phenotype ontologies. A large number of these ontologies have been developed across many domains, and we are now at a point where the knowledge captured in the structure of these ontologies can be used for the integration and analysis of large interrelated data sets. The Phenotype And Trait Ontology framework provides a method for formal definitions of phenotypes and associated data sets and has proved to be key to our ability to develop methods for the integration and analysis of phenotype data. Here, we describe the development and products of the ontological approach to phenotype capture, the formal content of phenotype ontologies and how their content can be used computationally.

Models in the Research Process of Psoriasis

Psoriasis is an ancient, universal chronic skin disease with a significant geographical variability, with the lowest incidence rate at the equator, increasing towards the poles. Insights into the mechanisms responsible for psoriasis have generated an increasing number of druggable targets and molecular drugs. The development of relevant in vitro and in vivo models of psoriasis is now a priority and an important step towards its cure. In this review, we summarize the current cellular and animal systems suited to the study of psoriasis. We discuss the strengths and limitations of the various models and the lessons learned. We conclude that, so far, there is no one model that can meet all of the research needs. Therefore, the choice model system will depend on the questions being addressed.

The Pathology of Aging 129S6/SvEvTac Mice

The 129 mouse strain is commonly used for the generation of genetically engineered mice. Genetic drift or accidental contamination during outcrossing has resulted in several 129 substrains. Comprehensive data on spontaneous age-related pathology exist for the 129S4/SvJae substrain, whereas only limited information is available for other 129 substrains. This longitudinal aging study describes the life span and spontaneous lesions of 44 male and 18 female mice of the 129S6/SvEvTac substrain. Median survival time was 778 and 770 days for males and females, respectively. Tumors of lung and Harderian gland were the most common neoplasms in both sexes. Hepatocellular tumors occurred mainly in males. Hematopoietic tumors were observed at low frequency. Suppurative and ulcerative blepharoconjunctivitis was the most common nonneoplastic condition in both sexes. Corynebacteria (primarily Corynebacterium urealyticum and C. pseudodiphtheriticum) were isolated from animals with blepharoconjunctivitis and in some cases from unaffected mice, although a clear causal association between corynebacterial infections and blepharoconjunctivitis could not be inferred. Polyarteritis occurred only in males and was identified as the most common nonneoplastic contributory cause of death. Eosinophilic crystalline pneumonia occurred in both sexes and was a relevant cause of death or comorbidity. Epithelial hyalinosis at extrapulmonary sites was noted at higher frequency in females. This study contributes important data on the spontaneous age-related pathology of the 129S6/SvEvTac mouse substrain and is a valuable reference for evaluation of the phenotype in genetically engineered mice obtained with this 129 substrain.

The mouse pathology ontology, MPATH; structure and applications

BACKGROUND

The capture and use of disease-related anatomic pathology data for both model organism phenotyping and human clinical practice requires a relatively simple nomenclature and coding system that can be integrated into data collection platforms (such as computerized medical record-keeping systems) to enable the pathologist to rapidly screen and accurately record observations. The MPATH ontology was originally constructed in 2,000 by a committee of pathologists for the annotation of rodent histopathology images, but is now widely used for coding and analysis of disease and phenotype data for rodents, humans and zebrafish.

CONSTRUCTION AND CONTENT

MPATH is divided into two main branches describing pathological processes and structures based on traditional histopathological principles. It does not aim to include definitive diagnoses, which would generally be regarded as disease concepts. It contains 888 core pathology terms in an almost exclusively is_a hierarchy nine layers deep. Currently, 86% of the terms have textual definitions and contain relationships as well as logical axioms to other ontologies such the Gene Ontology.

APPLICATION AND UTILITY

MPATH was originally devised for the annotation of histopathological images from mice but is now being used much more widely in the recording of diagnostic and phenotypic data from both mice and humans, and in the construction of logical definitions for phenotype and disease ontologies. We discuss the use of MPATH to generate cross-products with qualifiers derived from a subset of the Phenotype and Trait Ontology (PATO) and its application to large-scale high-throughput phenotyping studies. MPATH provides a largely species-agnostic ontology for the descriptions of anatomic pathology, which can be applied to most amniotes and is now finding extensive use in species other than mice. It enables investigators to interrogate large datasets at a variety of depths, use semantic analysis to identify the relations between diseases in different species and integrate pathology data with other data types, such as pharmacogenomics.

A cross-species analysis method to analyze animal models' similarity to human's disease state

Background

Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism.

Results

We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery.

We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning.

Conclusions

We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology.

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.

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.

Mouse genetic and phenotypic resources for human genetics

The use of model organisms to provide information on gene function has proved to be a powerful approach to our understanding of both human disease and fundamental mammalian biology. Large-scale community projects using mice, based on forward and reverse genetics, and now the pan-genomic phenotyping efforts of the International Mouse Phenotyping Consortium, are generating resources on an unprecedented scale, which will be extremely valuable to human genetics and medicine. We discuss the nature and availability of data, mice and embryonic stem cells from these large-scale programmes, the use of these resources to help prioritize and validate candidate genes in human genetic association studies, and how they can improve our understanding of the underlying pathobiology of human disease.

Semantic integration of physiology phenotypes with an application to the Cellular Phenotype Ontology

MOTIVATION

The systematic observation of phenotypes has become a crucial tool of functional genomics, and several large international projects are currently underway to identify and characterize the phenotypes that are associated with genotypes in several species. To integrate phenotype descriptions within and across species, phenotype ontologies have been developed. Applying ontologies to unify phenotype descriptions in the domain of physiology has been a particular challenge due to the high complexity of the underlying domain.

RESULTS

In this study, we present the outline of a theory and its implementation for an ontology of physiology-related phenotypes. We provide a formal description of process attributes and relate them to the attributes of their temporal parts and participants. We apply our theory to create the Cellular Phenotype Ontology (CPO). The CPO is an ontology of morphological and physiological phenotypic characteristics of cells, cell components and cellular processes. Its prime application is to provide terms and uniform definition patterns for the annotation of cellular phenotypes. The CPO can be used for the annotation of observed abnormalities in domains, such as systems microscopy, in which cellular abnormalities are observed and for which no phenotype ontology has been created.

AVAILABILITY AND IMPLEMENTATION

The CPO and the source code we generated to create the CPO are freely available on http://cell-phenotype.googlecode.com.

The neurobehavior ontology: an ontology for annotation and integration of behavior and behavioral phenotypes

In recent years, considerable advances have been made toward our understanding of the genetic architecture of behavior and the physical, mental, and environmental influences that underpin behavioral processes. The provision of a method for recording behavior-related phenomena is necessary to enable integrative and comparative analyses of data and knowledge about behavior. The neurobehavior ontology facilitates the systematic representation of behavior and behavioral phenotypes, thereby improving the unification and integration behavioral data in neuroscience research.