Mapping of genetic traits in experimental models using databases

Funded Activity Summary

The project aims to detect genes that influence human traits. These traits could be a disease such as diabetes or they may be much less sinister, representing hearing range as an example. Many of these traits are difficult to detect because they are governed by many genes which may also interact with the environment to influence the trait. In order to detect genes in these traits we would like to simplify the complex interactions by eliminating the environment as a potential cause or concentrating on a particular population where the incidence appears to be much greater. In human populations we have no control over the environmental exposures and we cannot restrict their movements. For this reason many genetic studies have been conducted in mice. Many strains of mice have been generated. Their environment can be strictly controlled, enabling a much better identification of disease genes. Since mice and humans share much of their genome they also share many of their genes and are often afflicted by the same diseases. Thus if we identify genes in mice we have a very good chance of identifying the equivalent human genes. The completion of sequencing for the human genome is being closely followed by the completion of the mouse genome, precisely because mice have been used for over 100 years for genetic studies. The data generated from these sequencing efforts and prior genetic studies is now accumulating in vast databases. These databases of DNA information can be used to map genes for traits. The idea is to determine the trait measurement for many mice in different strains and compare these trait levels to the DNA state (genotype) of markers in the genome of the strains. If these are associated it indicates that the marker is situated close to a gene influencing the trait. This narrows the search considerably. Without this strategy we would have the daunting task of identifiying trait genes from many thousands of potential candidates.

Funded Activity Details

Start Date: 01-01-2003

End Date: 01-01-2005

Funding Scheme: NHMRC Project Grants

Funding Amount: $237,750.00

Funder: National Health and Medical Research Council

Research Topics

ANZSRC Field of Research (FoR)

Quantitative Genetics

ANZSRC Socio-Economic Objective (SEO)

There are no SEO codes available for this funding activity

Other Keywords

Bioinformatics | Computational approaches to LD mapping | Gene Mapping | Identification of cancer modifier genes | Identification of novel disease genes | Linkage disequilibrium mapping methods experimental models | Murine Models | Quantitative Genetics | Statistical Genetics | Usage of publicly available databases

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