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

Abstract

Understanding the functions encoded in the mouse genome will be central to an understanding of the genetic basis of human disease. To achieve this it will be essential to be able to characterize the phenotypic consequences of variation and alterations in individual genes. Data on the phenotypes of mouse strains are currently held in a number of different forms (detailed descriptions of mouse lines, first-line phenotyping data on novel mutations, data on the normal features of inbred lines) at many sites worldwide. For the most efficient use of these data sets, we have initiated a process to develop standards for the description of phenotypes (using ontologies) and file formats for the description of phenotyping protocols and phenotype data sets. This process is ongoing and needs to be supported by the wider mouse genetics and phenotyping communities to succeed. We invite interested parties to contact us as we develop this process further.

Figure 1. Phenotype data resources.

We can distinguish a variety of types of resource holding data on mouse phenotypes. These range from the detailed descriptions held by the Mouse Genome Informatics group through quantitative data on the normal phenotypes of inbred lines held at the Mouse Phenome Database and in Europhenome, through to descriptions of high throughput phenotyping studies such as EUMODIC and summary descriptions of individual mutant lines held at a number of sites. Knowledge of the protocol used to derive data is also essential. To unify this data we will require a common description vocabulary, in the form of ontologies, and common means of representing the data itself and the underlying protocols for transfer between databases and between databases and analysis applications.

Figure 2. The ideal mouse.

For any given inbred line or mouse strain of defined genotype, data might be collected from various online sources to provide a summary of the phenotype of that line or strain in the form of a central tendency and a measure of variation. This would allow meta-analysis of phenotyping analyses carried out at different sites, and the integration of similar data relating to different genetic backgrounds, facilitating mining of genotype/phenotype datasets for novel patterns of association. By collecting data from different sites, information on the reproducibility of particular measurements could also be gathered. The information could be updated continuously to maintain up-to-date information