Open Access Research

Gene expression variation in Down's syndrome mice allows prioritization of candidate genes

Marc Sultan1*, Ilaria Piccini1, Daniela Balzereit1, Ralf Herwig1, Nidhi G Saran2, Hans Lehrach1, Roger H Reeves23 and Marie-Laure Yaspo1

Author Affiliations

1 Max Planck Institute for Molecular Genetics, Ihnestr.63/73, 14195, Berlin, Germany

2 Department of Physiology, Johns Hopkins University School of Medicine, 725 N. Wolfe St., Baltimore, Maryland 21205, USA

3 McKusick-Nathans Institute of Genetic Medicine, 733 Nth. Broadway, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA

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Genome Biology 2007, 8:R91  doi:10.1186/gb-2007-8-5-r91

Published: 25 May 2007

Abstract

Background

Down's syndrome (DS), or trisomy 21, is a complex developmental disorder that exhibits many clinical signs that vary in occurrence and severity among patients. The molecular mechanisms responsible for DS have thus far remained elusive. We argue here that normal variation in gene expression in the population contributes to the heterogeneous clinical picture of DS, and we estimated the amplitude of this variation in 50 mouse orthologs of chromosome 21 genes in brain regions of Ts65Dn (a mouse model of DS). We analyzed the RNAs of eight Ts65Dn and eight euploid mice by real-time polymerase chain reaction.

Results

In pooled RNAs, we confirmed that trisomic/euploid gene expression ratios were close to 1.5. However, we observed that inter-individual gene expression levels spanned a broad range of values. We identified three categories of genes: genes with expression levels consistently higher in Ts65Dn than in euploids (9, 17, and 7 genes in cerebellum, cortex, and midbrain, respectively); genes whose expression levels partially overlap between the two groups (10, 9, and 14 genes); and genes with intermingled expression, which cannot be used to differentiate trisomics from euploids (12, 5 and 9 genes). Of the genes in the first category, App, Cbr1, and Mrps6 exhibited tight regulation in the three tissues and are therefore attractive candidates for further research.

Conclusion

This is the first analysis addressing inter-individual gene expression levels as a function of trisomy. We propose a strategy allowing discrimination between candidates for the constant features of DS and those genes that may contribute to the partially penetrant signs of DS.