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Oral Presentation
Wednesday 20 November
09:15 - 09:30 HRS
MOUSEEXPRESS: IN SILICO ANALYSIS OF EXPRESSION PATTERNS IN MOUSE MUTANTS
J Beckers
GSF - National
Research Centre for Environment & Health
Co-Authors: 1)
Seltmann M, 1) Horsch M, 1) Drobyshev A, 1) Mader M, 1) Tornow S,
2) Frohme M, 2) Korica T,
3) Vingron M, 1) Mewes W,
2) Hoheisel J, 1) Hrabe de Angelis M
Institutions:
1) GSF - National Research Centre for Environment & Health2)
DKFZ - German Cancer Research Centre3) MPI for Molecular Genetics
We have implemented a platform for the functional analysis of mouse mutant lines using RNA expression profiling technology on a large scale and high throughput basis. The routine analysis of RNA expression patterns from organs supports the understanding of the underlying molecular biology of such mouse mutants and provides new insights in mammalian gene function. To achieve this goal SOPs from mouse husbandry and tissue sampling to the molecular techniques of DNA-chip hybridisations were implemented. We generate comprehensive high quality DNA glass chips with 20.000 and 48.000 3’UTRs and ESTs, respectively. Genes differentially expressed in mouse mutant lines have been identified and were confirmed by alternative methods. The detection of affected pathways has become an integral part of the molecular phenotypic analysis of mouse mutant resources and, together with mapping data, supports the identification of candidates for mutated genes in critical regions. Data generated in this project have successfully been used to identify new mouse models for human genetic diseases based on the differential expression of known marker genes. In addition, new and functionally not annotated genes have been associated with specific mouse mutant models. One of the largest European resources of mouse models (over 400 mutant lines) from the Munich ENU mutagenesis screen is directly accessible. The MouseExpress Consortium combines the power of mouse genetics, expression profile technology, and bioinformatics. Such comprehensive transcriptome analyses will lead to the identification of new gene functions and co-regulated synexpression groups of genes, which are the basis for the description of regulatory networks.
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