Literature DB >> 18252803

Quantitative gene expression profiling of mouse brain regions reveals differential transcripts conserved in human and affected in disease models.

Camille Brochier1, Marie-Claude Gaillard, Elsa Diguet, Nicolas Caudy, Carole Dossat, Béatrice Ségurens, Patrick Wincker, Emmanuel Roze, Jocelyne Caboche, Philippe Hantraye, Emmanuel Brouillet, Jean-Marc Elalouf, Michel de Chaldée.   

Abstract

Using serial analysis of gene expression, we collected quantitative transcriptome data in 11 regions of the adult wild-type mouse brain: the orbital, prelimbic, cingulate, motor, somatosensory, and entorhinal cortices, the caudate-putamen, the nucleus accumbens, the thalamus, the substantia nigra, and the ventral tegmental area. With >1.2 million cDNA tags sequenced, this database is a powerful resource to explore brain functions and disorders. As an illustration, we performed interregional comparisons and found 315 differential transcripts. Most of them are poorly characterized and 20% lack functional annotation. For 78 differential transcripts, we provide independent expression level measurements in mouse brain regions by real-time quantitative RT-PCR. We also show examples where we used in situ hybridization to achieve infrastructural resolution. For 30 transcripts, we next demonstrated that regional enrichment is conserved in the human brain. We then quantified the expression levels of region-enriched transcripts in the R6/2 mouse model of Huntington disease and the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of Parkinson disease and observed significant alterations in the striatum, cerebral cortex, thalamus and substantia nigra of R6/2 mice and in the striatum of MPTP-treated mice. These results show that the gene expression data provided here for the mouse brain can be used to explore pathophysiological models and disclose transcripts differentially expressed in human brain regions.

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Year:  2008        PMID: 18252803     DOI: 10.1152/physiolgenomics.00125.2007

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  18 in total

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