Gene expression variation between mouse inbred strains
Rolf Turk, Peter A.C. ’t Hoen, Ellen Sterrenburg, Renée X. de Menezes, Emile J. de Meijer, Judith M. Boer, Gert‐Jan B. van Ommen, Johan T. den Dunnen
Abstract
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Rolf Turk, Peter A.C. ’t Hoen, Ellen Sterrenburg, Renée X. de Menezes, Emile J. de Meijer, Judith M. Boer, Gert‐Jan B. van Ommen, Johan T. den Dunnen
Abstract
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BACKGROUND: In this study, we investigated the effect of genetic background on expression profiles. We analysed the transcriptome of mouse hindlimb muscle of five frequently used mouse inbred strains using spotted oligonucleotide microarrays. RESULTS: Through ANOVA analysis with a false discovery rate of 10%, we show that 1.4% of the analysed genes is significantly differentially expressed between these mouse strains. Differential expression of several of these genes has been confirmed by quantitative RT-PCR. The number of genes affected by genetic background is approximately ten-fold lower than the number of differentially expressed genes caused by a dystrophic genetic defect. CONCLUSIONS: We conclude that evaluation of the effect of background on gene expression profiles in the tissue under study is an effective and sensible approach when comparing expression patterns in animal models with heterogeneous genetic backgrounds. Genes affected by the genetic background can be excluded in subsequent analyses of the disease-related changes in expression profiles. This is often a more effective strategy than backcrossing and inbreeding to obtain isogenic backgrounds.
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BACKGROUND: In this study, we investigated the effect of genetic background on expression profiles. We analysed the transcriptome of mouse hindlimb muscle of five frequently used mouse inbred strains using spotted oligonucleotide microarrays. RESULTS: Through ANOVA analysis with a false discovery rate of 10%, we show that 1.4% of the analysed genes is significantly differentially expressed between these mouse strains. Differential expression of several of these genes has been confirmed by quantitative RT-PCR. The number of genes affected by genetic background is approximately ten-fold lower than the number of differentially expressed genes caused by a dystrophic genetic defect. CONCLUSIONS: We conclude that evaluation of the effect of background on gene expression profiles in the tissue under study is an effective and sensible approach when comparing expression patterns in animal models with heterogeneous genetic backgrounds. Genes affected by the genetic background can be excluded in subsequent analyses of the disease-related changes in expression profiles. This is often a more effective strategy than backcrossing and inbreeding to obtain isogenic backgrounds.
Key concepts: Biology, Genetics, Gene, Transcriptome, DNA microarray, Inbreeding, Gene expression, Inbred strain