18th International Mouse Genome Conference
17-22 October 2004, Seattle, USA
Plenary Presentations * Oral
Presentations * Poster
Abstracts * Photos
Verne Chapman Memorial Lecture * Table
of Contents * Attendees * Awards
ORAL PRESENTATION
MONDAY OCTOBER 18
3.15pm – 3.30pm
IDENTIFICATION OF CO-EXPRESSED GENE CLUSTERS IN A COMPARATIVE ANALYSIS OF TRANSCRIPTOME AND PROTEOME IN MOUSE TISSUES
Mijalski T1, Harder A2, Halder T2, Kersten M2, Horsch M1, Drobyshev A1, Lottspeich F3, Hrabe de Angelis M1, Beckers J1
1 Institute of Experimental Genetics, GSF – National Research Centre for Environment and Health, Neuherberg, Germany, 2 TopLab GmbH, Proteomics-Division, Martinsried, Germany, 3 Max-Planck-Institute for Biochemistry, Martinsried, Germany
A major advantage of the mouse model system lies in the increasingly complete information on its genome, transcriptome and proteome, as well as in the availability of a fast growing number of mutant and genetically engineered alleles. However, little is known about the relationship between the transcriptional and post-transcriptional regulation of gene expression. Data from comparative transcriptome and proteome analyses in the mouse as mammalian model organism is very limited. We use DNA-chip based RNA expression profiling and 2D-gelelectrophoresis combined with mass spectrometry of mouse liver and kidney extracts to explore the general feasibility of such comprehensive gene expression analyses. Whereas protein analyses mostly identify known metabolic enzymes and structural proteins in these tissues, transcriptome analyses reveal the differential expression of functionally diverse genes and, in addition, a significant number of genes that are not functionally described. The comparative analysis of proteins and their corresponding transcripts suggests a positive correlation between transcriptional and translational expression for the majority of genes and a few significant exceptions. Based on RNA expression data from the two hundred most differentially expressed liver or kidney specific genes, we identify chromosomal co-localization of known as well as not yet described gene clusters. The spatial organization and evolutionary conservation of such gene clusters may suggest common gene regulatory functions.