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Human Molecular Genetics Advance Access originally published online on December 8, 2004
Human Molecular Genetics 2005 14(3):373-384; doi:10.1093/hmg/ddi033
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Human Molecular Genetics, Vol. 14, No. 3 © Oxford University Press 2005; all rights reserved

The cerebellar transcriptome during postnatal development of the Ts1Cje mouse, a segmental trisomy model for Down syndrome

L. Dauphinot1, R. Lyle4, I. Rivals2, M. Tran Dang1, R.X. Moldrich1, G. Golfier1, L. Ettwiller1, K. Toyama3, J. Rossier1, L. Personnaz2, S.E. Antonarakis4, C.J. Epstein5, P.-M. Sinet3 and M.-C. Potier1,*

1Unité Mixte de Recherche 7637, Centre National de la Recherche Scientifique, 2Equipe de Statistique Appliquée, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France, 3Institut National de la Santé Et de la Recherche Médicale Unité 549, Institut Paul Broca, 2ter, rue d'Alésia, 75014 Paris, France, 4Department of Genetic Medicine and Development, University of Geneva Medical School, 1 rue Michel Servet, 1211 Geneva, Switzerland and 5Department of Pediatrics, UCSF, San Francisco, CA 94143-0748, USA

* To whom correspondence should be addressed. Email: marie-claude.potier{at}espci.fr

Received September 16, 2004; Revised November 15, 2004; Accepted November 26, 2004


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
The central nervous system of persons with Down syndrome presents cytoarchitectural abnormalities that likely result from gene-dosage effects affecting the expression of key developmental genes. To test this hypothesis, we have investigated the transcriptome of the cerebellum of the Ts1Cje mouse model of Down syndrome during postnatal development using microarrays and quantitative PCR (qPCR). Genes present in three copies were consistently overexpressed, with a mean ratio relative to euploid of 1.52 as determined by qPCR. Out of 63 three-copy genes tested, only five, nine and seven genes had ratios >2 or <1.2 at postnatal days 0 (P0), P15 and P30, respectively. This gene-dosage effect was associated with a dysregulation of the expression of some two-copy genes. Out of 8258 genes examined, the Ts1Cje/euploid ratios differed significantly from 1.0 for 406 (80 and 154 with ratios above 1.5 and below 0.7, respectively), 333 (11 above 1.5 and 55 below 0.7) and 246 genes (59 above 1.5 and 69 below 0.7) at P0, P15 and P30, respectively. Among the two-copy genes differentially expressed in the trisomic cerebellum, six homeobox genes, two belonging to the Notch pathway, were severely repressed. Overall, at P0, transcripts involved in cell differentiation and development were over-represented among the dysregulated genes, suggesting that cell differentiation and migration might be more altered than cell proliferation. Finally, global gene profiling revealed that transcription in Ts1Cje mice is more affected by the developmental changes than by the trisomic state, and that there is no apparent detectable delay in the postnatal development of the cerebellum of Ts1Cje mice.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Down syndrome results from trisomy of human chromosome 21 and is the most frequent genetic cause of mental retardation, occurring in ~1 in 800 newborns. Most cases are full trisomies, and about 300 genes are triplicated (1Go). This dosage imbalance causes dysfunction of developmental and physiological processes, but there is a puzzling variability among affected individuals in terms of the number of clinical features observed and their severity (2Go). Therefore, one of the most relevant questions in Down syndrome research concerns the identification of the genes (within or outside of chromosome 21) that contribute both to the phenotype and to the phenotypic variability. In addition, we believe that the identification of these genes is essential for the development of new therapeutic approaches. The search for gene targets that may be amenable to therapeutic approaches has accelerated in the past few years with the publication of the human genome sequence and the use of large-scale gene expression studies such as SAGE and microarrays (3Go–7Go).

Because of the prominence of mental retardation, brain has been the subject of particular interest in research on Down syndrome, but a systematic study of gene expression in brain during development, particularly at postnatal stages, is only possible in animal models. Mouse models for Down syndrome are trisomic for single gene, for several genes or for a large segment corresponding to the distal part of chromosome 16, orthologous to a large portion of human chromosome 21 (8Go). Two models of segmental trisomy 16 have been generated, the Ts65Dn mice and the Ts1Cje mice (9Go–11Go). These models have revealed previously unknown phenotypes that may be relevant to Down syndrome, such as a substantial loss of glutamatergic granule cells in the internal layer of the cerebellum in adult (12Go,13Go).

We studied the transcriptome during postnatal development of the cerebellum for two reasons. First, there are massive developmental changes during the first 20 days after birth. During this period, granule cells, which represent ~40% of the total number of neurons of the mature cerebellum, proliferate, migrate and differentiate from the external to the internal layer, and Purkinje cells develop their dense dendritic trees making connections with other cells. Secondly, gene profiling during postnatal development of the cerebellum in mice is well documented (14Go,15Go), Furthermore, previously investigated mutants of the cerebellum could serve as a reference to our study (14Go).

The Ts1Cje Down syndrome model was used in the present study after backcrossing the mice onto a pure genetic background to reduce variability in gene expression. Ts1Cje mice carry a segmental duplication of the syntenic region orthologous to human chromosome 21 from Sod1 to Znf295, including about 95 genes (8Go,10Go,11Go). Differential gene expression was studied at postnatal days 0 (P0), P15 and P30 in the cerebellum using Affymetrix U74Av2 microarrays. Expression of genes was also measured in parallel by quantitative PCR (qPCR).

Two groups of genes have been characterized: one that contains the triplicated genes and shows a consistent gene-dosage effect (approximately 1.5 overexpression ratio in Ts1Cje mice when compared with euploid mice) during postnatal development, and the second that contains euploid genes that are significantly differentially expressed (over or under) and are mainly involved in cell differentiation and development.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Experimental data and analysis: validation
Using Affymetrix murine genome U74Av2 microarrays, we measured the expression levels of 12 488 genes (half known genes and half ESTs) in the cerebellum of Ts1Cje and euploid mice each at P0, P15 and P30 during postnatal development. The mean expression value for each gene was calculated from duplicate experiments performed on the six groups of three animals each. According to the Affymetrix algorithm, 8287 genes were found to be expressed at least at one time point (see Materials and Methods for details on the filtering step and Supplementary Material, Table S1 for a complete list of the 8287 genes). Two statistical analyses were applied to the data: variability analysis of microarray data (VARAN), a freely available web server performing a signal intensity-based analysis of the log 2 expression ratios variability deduced from DNA microarray raw data (16Go), and ANOVA. The parametrization chosen for the ANOVA allowed the selection of genes either involved in normal postnatal development of the cerebellum or differentially expressed in Ts1Cje mice when compared with euploid mice at one particular stage of development ({alpha}i and ßi parameters, respectively, in Table 1).


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  		Table 1. Parameters of gene expression levels
 
To validate our experimental data and analysis, we compared genes differentially expressed between P0 and P15 or between P15 and P30 ({alpha}i parameters) in either euploid mice or Ts1Cje mice with genes differentially expressed along normal postnatal development of the cerebellum as reported by Diaz et al. (14Go). Their experimental data, which were obtained on the mouse RIKEN 19-K microarray, were analyzed using ANOVA with the parametrization described in Table 1 ({alpha}i parameters). Many genes differentially expressed during postnatal development of the cerebellum, such as GABA-{alpha}6 and GABA-{delta}, myelin oligodendrocyte glycoprotein and parvalbumin (Supplemental Material, Table S2), belonged to the cell differentiation class B of Diaz et al. (14Go). Discordance between the two studies is, generally, the result of differences in the gene content of the two microarrays. We thus concluded that our data were as informative as those of Diaz et al. (14Go).

Gene expression in the Ts1Cje cerebellum: triplicated versus euploid genes from mouse chromosome 16
Of the 8287 expressed genes, 145 were from mouse chromosome 16, and among them 29 were triplicated in Ts1Cje mice. At P0, P15 and P30, mean expression ratios of triplicated genes between Ts1Cje and controls were 1.66, 1.32 and 1.32 at P0, P15 and P30, respectively, whereas with euploid genes the ratios were 1.08, 1.12 and 1.02 at P0, P15 and P30, respectively (Fig. 1). After ANOVA, 12, six and nine triplicated genes were found to be statistically overexpressed ({alpha}=1%) in Ts1Cje mice when compared with euploid mice at P0, P15 and P30, respectively (Table 2). Among these genes, four (Dscr3, HMGP14, Donson, C21orf4) were overexpressed at all three time points.



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  		Figure 1. Distribution of gene expression ratios between Ts1Cje and euploid mice in the cerebellum at postnatal days 0 (P0), P15 and P30 using mouse genome U74Av2 Affymetrix microarray data. Genes are subdivided as euploid genes from or outside mouse chromosome 16 (MMU16) and trisomic genes from MMU16.

 

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  		Table 2. List of triplicated genes found to be differentially expressed by ANOVA of microarray data
 
qPCR on 78 genes from chromosome 16 (15 euploid and 63 triplicated) showed overexpression of the triplicated genes with mean ratios of 1.56, 1.43 and 1.55 at P0, P15 and P30, respectively, whereas the euploid genes from chromosome 16 had ratios very close to 1.0 (1.04, 1.00 and 1.01 at P0, P15 and P30, respectively) (Fig. 2; Supplementary Material, Table S3). The 18 control genes mapping to chromosomes other than 16 and described previously (17Go) showed ratios of 1.02, 1.08 and 1.03 at P0, P15 and P30, respectively. Gene expression of the 33 euploid genes from chromosome 16 and other chromosomes did not reveal any significant correlations between stages. Interestingly, for the triplicated genes, there was a highly significant correlation (P<0.01) between the P15 and P30 time points. Only a few genes had ratios above 2 (three, two and five genes at P0, P15 and P30, respectively) or below 1.2 (two, seven and five genes at P0, P15 and P30, respectively).



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  		Figure 2. Differences in the expression of 78 genes from mouse chromosome 16 (MMU16) and 18 control genes outside MMU16 between Ts1Cje and euploid mice in the cerebellum at P0, P15 and P30 by real-time qPCR. Genes are ordered according to their chromosomal location (MMU16 or non-MMU16, for the MMU16 genes the order along the chromosome is respected) and their copy number (euploid or trisomic). Mean expression ratios (n=5) are indicated at the bottom.

 
qPCR and microarray measurements were highly correlated (P<0.01) for 45 transcripts tested that were present in both microarray and qPCR studies. A single and expected exception was the Sod1 transcript. The wild-type Sod1 gene is composed of five exons, but in Ts1Cje mice a neomycin cassette is inserted into exon 3, thereby generating a shorter transcript with only exons 1, 2 and 5 (18Go). DNA probes on microarrays detected this new transcript, but qPCR did not, because the primers span exons 3 and 4 (17Go).

Gene expression in the Ts1Cje cerebellum: euploid genes from all chromosomes (statistical analysis and validation by qPCR)
In addition to the triplicated genes from chromosome 16 that were found to be consistently overexpressed in Ts1Cje mice when compared with euploid mice, euploid genes from chromosomes other than 16 were also found to be differentially expressed at P0, P15 and P30. A first statistical analysis of the data using VARAN selected a total of 95 genes with ratios between Ts1Cje and euploid ranging from 0.1 to 0.8 and from 1.2 to 70.7, respectively. Five genes were from the triplicated segment of chromosome 16, and 90 were euploid genes. Table 3 displays the number of genes differentially expressed deduced from the four independent analysis at each time point (see Data Analysis in Materials and Methods). Overlaps between the four analyses gave the final number of differentially expressed genes: 13, 57 and 25 at P0, P15 and P30, respectively (Table 3). These genes are listed in Table 4. No differentially expressed genes were in common for all three developmental stages studied. However, three genes were in common between P0 and P15 and three other genes between P15 and P30 (bold in Table 4).


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  		Table 3. Number of differentially expressed genes among the 8287 genes detected on U774Av2 Affymetrix microarray according to VARAN (1% threshold)
 

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  		Table 4. List of genes whose expression is changed in Ts1Cje mice when compared with euploids according to both VARAN and ANOVA
 
A second statistical analysis, ANOVA, was applied to the data. Table 5 gives the number of genes that are differentially expressed (over or under) and the test of the nullity of each parameter for several values of the risk of type I error (1, 0.1 and 0.01%). For a 1% risk, the number of genes differentially expressed is much higher between the stages of development (24.6 and 27.5% between P0 and P15 and between P15 and P30, respectively) than between the trisomic versus euploid state (5.1, 4.1 and 3.1% at P0, P15 and P30, respectively). A complete list of genes is included in Supplementary Material, Table S4. All genes differentially expressed from VARAN were also detected by ANOVA and corresponded to the short list in Table 4, indicating that analysis with VARAN is more stringent than with ANOVA. At P0, 86 and 154 genes had ratios above 1.5 and below 0.7, respectively. At P15, more genes had ratios below 0.7 than above 1.5 (154 and 86 genes, respectively). At P30, 63 and 69 genes had ratios above 1.5 and below 0.7, respectively. Thirty-one genes were in common between all three stages (Supplementary Material, Table S4). Figure 3 represents gene expression ratios between Ts1Cje and euploid mice with respect to the value of their statistic (Fisher), and shows that variations are more significant (higher Fisher) at P0 and P15 than at P30. Differentially expressed genes are either up- or down-regulated, and nearly all triplicated genes belong to the up-regulated genes.


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  		Table 5. Number of differentially expressed genes among the 8287 at P0, P15 and P30 according to ANOVA (rejection rate of H0, see Materials and Methods)
 


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  		Figure 3. Statistical analysis of genes from microarray data differentially expressed between Ts1Cje mice and euploid mice at P0 (A), P15 (B) and P30 (C). Asterisks, crosses and open circles correspond to MMU16 trisomic genes, MMU16 euploid genes and non-MMU16 euploid genes, respectively. ANOVA: {alpha}=1%, n=6, N=12 (see Materials and Methods).

 
Classification of the differentially expressed genes from ANOVA according to gene ontology showed a significant enrichment only at P0 for GO categories GO : 0007275 (P=0.00079) and GO : 0030154 (P=0.00051), corresponding to genes involved in cell development and differentiation, respectively. Among the 419 differentially expressed genes at P0 (Table 5, Ts1Cje/euploid at P0 with {alpha}=1%), there were 297 genes with annotated ontology of which six and 17 were involved in cell differentiation and development, respectively.

To confirm the reliability of microarray data, seven differentially expressed genes from the short list of 95 genes selected by VARAN and ANOVA were analyzed by qPCR at P0, P15 or P30 (Table 6). From a total of eight experiments conducted across three developmental stages, six variations were confirmed. Differential expression of Glutamine synthase was found to be different when measured by qPCR compared with microarray, thus suggesting a lack of specificity of the microarray probe set.


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  		Table 6. Comparison between Ts1Cje/euploid expression ratios of genes selected by VARAN (16Go) obtained either by qPCR or from the Affymetrix U74Av2 microarray data
 
Principal component analysis
For gene profiling across all conditions, trisomic and euploid at P0, P15 and P30, we performed PCA. With the 8287 genes detected on the Affymetrix U74Av2 microarray, the projection onto the subspace spanned by the two first principal components clearly grouped the animals according to their stage of development, thus demonstrating that the effect of development on gene expression is more important than the trisomic effect (Fig. 4A). PCA was then performed on subsets of genes of increasing size, the genes being ranked according to their discriminatory power for trisomy using Student statistic on data from either euploid mice or trisomic mice whatever their stage of development (see Materials and Methods). For the first 100 genes, PCA grouped the animals according to the trisomic versus euploid state (Fig. 4D). However on larger subsets (3000 genes), animals were grouped according to their developmental stage (Fig. 4B). With 3000 genes, within each stage of development, Ts1Cje animals could be distinguished from the euploids. The use of 2000 genes resulted in an intermediate situation where the most likely separation was made according to the trisomic versus euploid state, although one could also still get a separation according to the stage of development (Fig. 4C).



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  		Figure 4. PCA on 8287 expressed genes from mouse genome U74Av2 Affymetrix microarrays at P0, P15 and P30 (A) and on subsets of genes ranked according to trisomic versus euploid state using a t-test: the first 3000 genes (B), 2000 genes (C) and 100 genes (D), Open and filled symbols correspond to euploid and trisomic mice respectively. Circles, triangles and lozenges correspond to P0, P15 and P30 respectively.

 
Comparison of microarray data from the literature
Our data set was compared to those of two microarray studies published recently: that of Saran et al. (6Go) performed on adult (3–4 months) cerebellum from Ts65Dn mice, another mouse segmental trisomy 16 with a larger trisomic fragment (App to Znf295), and that of Amano et al. (7Go) performed on whole brains from Ts1Cje mice at P0. To compare all three studies, the data sets were represented the same way, namely the value of the statistic (t-test) with respect to the expression ratio of trisomic versus euploid (Fig. 5). For the study of Saran et al. (6Go), only the pools were analyzed. For our study, trisomic and euploid animals were grouped together whatever their stage of development, and a t-test was applied. During postnatal development of the cerebellum in Ts1Cje mice (our study), there were genes differentially expressed (up and down), some from the triplicated region (seven over 29 detected on microarray) and some from the euploid region (44 over 8258) (Fig. 5A). In whole brain at P0 in Ts1Cje mice, most of the differentially expressed genes were up-regulated, with mainly genes from the triplicated region (25 over 45 and 76 over 10557 for the triplicated and euploid genes, respectively) (Fig. 5B). Finally, in the cerebellum of adult Ts65Dn mice (3–4 months), there were genes up- and down-regulated, with a large proportion from the triplicated region (10 over 20 and 337 over 6581 for the triplicated and euploid genes, respectively) (Fig. 5C). This comparative analysis revealed that the percentage of differentially expressed genes varies among studies, from 0.61 (our study when pooling the three time points) to 0.95% in Amano et al. (7Go), 5.35% in Saran et al. (6Go) and 5.1, 4.1 and 3.1% (our study at P0, P15 and P30, respectively, Table 5 and Fig. 3) with a constant higher proportion of triplicated up-regulated genes when compared with euploid up-regulated genes.



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  		Figure 5. Comparison of differentially expressed genes in three studies. (A) in Ts1Cje cerebellum at P0, P15 and P30: our study, (B) in whole brain Ts1Cje at P0: Amano et al. (7Go) and (C), in Ts65Dn cerebellum at 3–4 months: Saran et al. (6Go). For comparing the three studies, a t-test was applied to all three sets of data.

 
Using the same statistical analysis of microarray data (VARAN), three genes/ESTs from the euploid genomic region were found to be differentially expressed in the cerebellum of both Ts1Cje mice at P30 (our study) and Ts65Dn mice at 3–4 months (6Go): one repressed (MGI 96021 corresponding to hemoglobin ß1 major chain) and two overexpressed (Riken cDNA 1810007M14 and probe set Affymetrix 98525 corresponding to C21orf66 and to erythroid differentiation regulator 1 Erdr1, respectively).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 
Gene-dosage effect of the triplicated genes from mouse chromosome 16 (MMU16) during postnatal development of the cerebellum in Ts1Cje mice
Study of the cerebellar transcriptome during postnatal development in the Ts1Cje model of Down syndrome clearly shows an overexpression of the three copy-genes, with mean ratios over postnatal development of 1.43 and 1.52 as determined by microarray and qPCR experiments, respectively. These results are in agreement with other studies published recently (6Go,7Go,17Go,19Go), thus demonstrating that there is a consistent modification in the number of transcripts throughout development resulting from a gene-dosage effect. From qPCR, not all genes had a 1.5 expression ratio between Ts1Cje and euploid, thus suggesting that there might be subtle compensatory mechanisms to the gene-dosage effect as discussed previously (17Go,19Go). Gene-dosage effects on the genome and transcriptome have been described in tumors (20Go,21Go), but there are genes for which the level of expression is not strictly dependent on the gene copy number, again suggesting the existence of compensatory mechanisms (22Go).

Development has a greater effect than trisomy on global gene expression
Global gene expression profiling during postnatal development of the cerebellum enables mice to be classified according to their stage of development rather than to their trisomic versus eusomic status. This indicates that development has more impact on the expression profile than does gene-dosage (Fig. 4A). Furthermore, gene expression profiles of the Ts1Cje cerebellum at P15 and P30 were not closer to the euploid animals at P0 and P15, respectively, thus indicating that there was no developmental delay in Ts1Cje mice (Fig. 4A). Figure 3 showed that there were more genes differentially expressed with significant statistical values at P0 and P15 than at P30. In addition, qPCR on triplicated genes indicated that there was a highly significant correlation (P<0.01) between the P15 and P30 time points, but not between P0 and P15 or P30, suggesting that the developmental changes occurred between P0 and P15, and then stabilized.

Gene expression dysregulation of euploid genes
Statistical analysis revealed a group of dysregulated genes with ratios ranging from 0.1 to 0.8 and from 1.2 to 70.7 (short list in Table 4). The analysis was validated by qPCR on a group of seven genes, and the differential expression of six were confirmed. Comparative analysis of microarray data [our study on Ts1Cje and study of Saran et al. (6Go) on the cerebellum of adult Ts65Dn mice] revealed euploid genes that are severely differentially expressed (up or down) with large statistical values (Fig. 5A and C). In the transcriptome study on whole brain from Ts1Cje at P0, most differentially expressed genes were from the triplicated genomic segment, with ratios below 2 (7Go) (Fig. 5B). Because whole brain is a mixture of many different cell types, including cerebellar cells, cell-specific regulation is diluted and below the level of detection. Reducing cellular complexity by the use of cerebellum increases the chance of seeing genes that are differentially expressed in a particular cell type. Using even smaller brain structures may reveal differentially expressed genes that are specific for one region of the brain. The higher number of dysregulated genes found in our study (5.1, 4.1 and 3.1% at P0, P15 and P30, respectively, Table 5) and in the study of Saran et al. (6Go) in adult Ts65Dn cerebellum (5.35%) as compared to 0.95% in the study of Amano et al. (7Go) on whole brain of Ts1Cje at P0 could relate to the complexity of the tissue used. In a similar way, pooling the same tissue (cerebellum) at different time points (P0, P15 and P30) decreased the number of differentially expressed genes to 0.61% (Fig. 5A). From VARAN analysis, two euploid genes were selected as differentially expressed both from our study (Ts1Cje at P30) and from the data of Saran et al. (6Go) (Ts65Dn at 3–4 months). One, corresponding to hemoglobin ß1 chain, was repressed, and the other, corresponding to erythroid differentiation regulator, was overexpressed. Supplementary Material, Table S4 shows that several hemoglobin {alpha}- and ß-subunits were highly repressed at P30 and P15, thus suggesting a decrease in the amount of meninges that surround the cerebellum. Additional experiments done on animals bred on the same genetic background and at the same time points will be necessary to draw a final conclusion on particular genes.

Pathways modified during postnatal development of the cerebellum in Ts1Cje mice: cell differentiation and development
We used gene ontology to categorize the differentially expressed genes from our microarray experiments and found that at P0 there was an enrichment of genes involved in cell differentiation and development. This suggests that cell differentiation and migration of cells might be more affected by trisomy than cell proliferation. At P0, of the 17 genes known to be involved in development, six are homeobox genes, all of which were repressed. In addition, at P15 and P30, respectively, 12 and one homeobox genes were found to be differentially expressed. Homeoproteins are involved in the early patterning of the nervous system and possibly at later stages of neuronal differentiation (23Go). Among them, Homeo box A5 was found to be severely down-regulated (to 0.12) at P0 in our study, as well as in two pools of cerebellum from adult Ts65Dn mice (0.47 and 0.54) (6Go). In the study of Amano et al. (7Go) on whole brain of Ts1Cje mice, Homeo box A5 was not detected. Homeo box A5 is mostly expressed during the neonatal period, but there are studies relating to its expression in the adult, particularly in Purkinje cells, where it activates the transcription of Purkinje cell protein 2 (24Go).

At P15, Dlx1 was found to be overexpressed in Ts1Cje mice when compared with euploid mice (Table 6: 80-fold and 70.8-fold by microarray and qPCR, respectively). This very high ratio probably indicates that Dlx1 is expressed only in trisomic cerebellum. Dlx1 is not known to be involved in postnatal development of the cerebellum. However, its role in the lineage of a particular type of GABAergic interneurons in human neocortex has been demonstrated recently (25Go). In addition, an increase of Dlx1 and Dlx2 negatively regulates the Notch signalling to specify a later subset of neuronal progenitors and promote their terminal differentiation (26Go). Dlx2 was also found to be increased at P15 (7-fold; Supplementary Material, Table S4). It is therefore likely that increase of Dlx1 and Dlx2 may be associated with cell differentiation. We cannot exclude significant changes in the expression of transcription factors important for development of the cerebellum, such as Math1, Mash1 and Shh, that have been described in microarray studies (14Go), as they were not present on the Affymetrix U74Av2 microarray. More data on these particular genes will be useful for understanding cerebellum development, as Math1 has recently been shown to be involved in the control of cerebellar granule cell differentiation by regulating multiple components of the Notch signalling pathway (27Go). Study of gene expression of Notch receptors and ligands and transcription factor targets will confirm whether the Notch pathway is altered in Down syndrome.

Gene profiling from the study of Diaz et al. (14Go) on cerebellum mutants (weaver and lurcher) were compared to gene profiling in Ts1Cje mice using the same statistical analysis (ANOVA with the parameterization described in Materials and Methods). In weaver mice, granule cells are severely reduced in the internal layer of the adult cerebellum, whereas in lurcher mice, Purkinje cells are reduced (28Go,29Go). Comparison of Ts1Cje, weaver and lurcher revealed more similarity between Ts1cje and weaver mutants than between Ts1Cje and lurcher mutants (unpublished data). This is consistent with morphological data (13Go) suggesting that granule cells, rather than Purkinje cells, are altered in Ts1Cje mice.

The list of genes differentially expressed also includes transthyretin, a transporter of thyroid hormone and vitamin A, which has been shown to be a carrier of amyloid beta peptide in the cerebrospinal fluid. Transthyretin prevents formation of amyloid fibrils and Apo-E-induced accumulation of amyloid beta (30Go,31Go). In Ts1Cje mice, transthyretin was repressed on microarrays and by qPCR at P0 (Table 6). Repression of transthyretin, if present in Down syndrome, might contribute to the amyloid beta deposition process in brain in addition to APP overexpression.

Another gene expression study in Down syndrome has shown that REST (neuron-specific silencer factor) and its targets (SCG10, L1, synapsin) are down-regulated in neuronal precursor cells from Down syndrome fetal cortex (32Go). From our study, expression of SCG10, synapsin and L1, but not of REST, was detected during postnatal development of the cerebellum. Only L1 was found to be differentially expressed, with a ratio of 0.52 between Ts1Cje and euploid at P0, although with low statistical value (Fisher=4.6 under the 1% threshold). Our data do not, therefore, provide evidence for or against the hypothesis of down-regulation of REST pathway in neuronal precursor cells proposed by Bahn et al. (32Go).

In conclusion, in the Ts1Cje mouse model of Down syndrome, the presence of three copies of ~85 genes having orthologues on human chromosome 21 induces a consistent change in expression of these triplicated genes throughout postnatal development. In addition to this general gene-dosage effect, where the expected 1.5 overexpression ratio is largely but not totally respected, a number of euploid genes are differentially expressed in a time-dependant manner, with an over-representation of transcripts involved in cell differentiation and development. Finally, gene profiling reveals that development has more impact on the transcriptome than the trisomic/eusomic status, and that there is no detectable delay in the postnatal development of the cerebellum of the segmental trisomy Ts1Cje mice.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
SUPPLEMENTARY MATERIAL
 REFERENCES
 
Mice
Ts1Cje mice carry a segmental duplication of the MMU16 region from Sod1 to Znf295. Ts1Cje mice were bred on a C57BL/6 background (11 backcrosses). For gene expression analysis, three pairs of euploid (C57BL/6) and trisomic Ts1Cje male sibs from two litters were used for each developmental stage P0, P15 and P30.

Genotyping
Because the trisomic segment of MMU16 has a truncated Sod1 allele with the neomycin resistance cassette, the mice were first typed on genomic DNA from the tail by PCR using Neo primers (10Go).

In addition, after individual RNA extraction (discussed subsequently), all animals were tested for the presence of both Sod1 wild-type and truncated alleles by PCR on cDNAs using Sod1 primers: up—CAATGTGACTGCTGGAAAGG and low—ATCCCAATCACTCCACAGGC. For each mouse, 500 ng of total RNA from cerebellum were reverse-transcribed overnight at 37°C in the presence of 200 U of Superscript II (InVitrogen), 1x first-strand buffer, 100 µM DTT, 5 µM random hexamers oligonucleotides (Pasteur Institute) and 500 µM dNTPs. PCRs were performed using 2.5 U of HotstartTaq® DNA polymerase (Qiagen) with 1x PCR buffer containing 1.5 mM MgCl2, 0.3 µM of each primer and 200 µM dNTPs for 40 cycles of 94°C for 30 s, 58°C for 30 s, 72°C for 40 s. Because one of the P30 euploid mice showed a pattern with an unexpected number of bands, we decided not to use it, and the euploid P30 pool was therefore composed of only two animals instead of three.

RNA extraction and microarray hybridizations
Total RNA was extracted from frozen individual cerebellum and treated with DNase using RNeasy Midi kit (Qiagen). The quality of each RNA sample was then checked using the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Palo Alto, CA, USA).

For the three postnatal stages, euploid and trisomic samples were prepared by pooling an equal amount of each individual RNA. An aliquot 20 µg of total RNA from each pool was converted to cDNA and then to biotinylated cRNA, and were hybridized to Affymetrix Murine Genome U74A version 2 microarrays (Affymetrix, Inc., Santa Clara, CA, USA) on the Curie Institute Affymetrix microarray platform (Paris, France), according to the Affymetrix procedures. Each pool was hybridized in duplicate on independent U74Av2 microarrays.

Data analysis: filtering, normalization, VARAN and ANOVA and ontology
After hybridization, signal intensities were calculated using the Affymetrix GeneChip® software MAS 5.0. The software generates a ‘detection P-value’ and a ‘detection call’ to decide whether a gene is expressed, and then attributes to each gene a status: present, absent or marginal. For further analysis, we used only the 8287 genes that were defined as ‘Present’ or ‘Marginal’ in Ts1Cje or euploid mice at least at one time point. Genes called ‘Absent’ in all conditions were not used for further analysis.

We have deposited all the raw data (accession number GSE1611) in the NCBI public database Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/).

Filtered data (8287 genes) were submitted to VARAN (http://www.bionet.espci.fr,) for normalization and differential expression analysis (16Go). The microarray measurements were grouped into six pairs of replicates: euploids at P0, P15, and P30, and Ts1Cje mice at P0, P15, and P30. The expression levels were corrected in order to constrain the mean ratio of each pair to be equal to one using a Lowess fit on the M–A plot of the log-expression levels (16Go). In the numerical analysis, the logarithm of the expression levels was used. For each experiment replicates on euploid mice (i.e. at P0, P15 and P30), a reference M–A plot was established. Assuming that the variance of the gene expression level was a function of their mean, and that the expression levels were Gaussian, the 1% threshold values for the difference as a function of the mean were estimated.

For each stage, the M–A plots of the four possible combinations of euploid and Ts1Cje mice were established, thus providing four analysis at each time point, and the genes whose difference of expression between euploid and trisomic exceeded the 1% threshold values were selected. For the ANOVA, we applied a regression model for gene expression levels. Table 1 indicates the parameters {{alpha}i}, which model the effects of development in euploid mice, and {ßi}, which model the effects of trisomy at each development stage. The number n of parameters equals six, and the number N of microarray measurements equals 12.

Assuming a Gaussian distribution of gene expression levels with common variance s2, the sum of squared residuals of the model was {chi}2 distributed: SSR/{sigma}2->{chi}2(N–n). If trisomy had no effect at a given stage, we assumed the nullity of the corresponding parameter (null hypothesis H0). If H0 is true, (SSR0–SSR)(N–n)/SSR->Fisher(1, N–n), where SSR0 corresponded to the sum of squared residuals of the associated submodel. Hence the test rejects H0 if the Fisher statistic (SSR0–SSR) (N–n)/SSR>f{alpha}(1, N–n), where {alpha} denoted the chosen significance level and f{alpha}(1, N–n) denoted the corresponding quantile of the Fisher distribution. The hypergeometric distribution was used to calculate the probability of observing individual GO terms as enriched in sets of differentially expressed genes relative to the reference set of expressed genes on the Affymetrix U74Av2 microarray.

Principal component analysis
PCA was first performed on the 8287 expressed genes and then on subsets of genes of increasing size, the genes being according to their discriminatory power for trisomy. The discriminatory power of gene i was measured by the absolute value of its Student statistic ti:

where NTs=NEu=6 was the number of measurements on trisomic and euploid mice, respectively, whatever their stage of development, and the mean expression of gene i for the trisomic and euploid mice, respectively, and si the intraclass variance estimate.

Real-time quantitative PCR
From each euploid and trisomic pool, 250 ng and 6 µg of total RNA were individually converted into cDNAs overnight at 37°C in the presence of 200 U of Superscript II (In vitrogen), 1x first-strand buffer, 100 µM DTT, 5 µM random hexamers oligonucleotides (Pasteur Institute) and 500 µM dNTPs.

The cDNAs were then diluted 1 : 5 and 1 : 14 for the 250 ng and 6 µg RNA samples, respectively, for qPCR according to the following protocols: qPCR on the 78 MMU16 genes and 18 control genes mapping to chromosomes other than 16 were performed as Taqman assays in an ABI 7900 Sequence Detection System (Applied Biosystems). Assay sequences are available in Lyle et al. (17Go). Each expression value corresponds to the mean of five replicates.

qPCR on the seven genes outside MMU16 that were found to be differentially expressed by microarray analysis (ALDR, Astrotactin, Dlx1, Glutamine synthase, Homeo box A5, transthyretin, Uncx4.1) were performed in a Lightcycler system (Roche Molecular Biochemicals), in the presence of 0.5 µM of each specific primer (designed by Oligo4 software) and 1x QuantitectTM SYBR® Green PCR master mix (Qiagen) containing 2.5 mM MgCl2, HotstartTaq® Polymerase, dNTP mix and the fluorescent dye SYBR Green I. Each reaction was performed in triplicate. The list of primers is given in Supplementary Material, Table S5. For each sample tested, three control genes (GAPD, tubulin and Ppox) that showed no difference between Ts1Cje and euploids were used to normalize raw data, and the mean relative ratios Ts/Eu were calculated according to geNorm (33Go) as described in Lyle et al. (17Go).


   ACKNOWLEDGEMENTS
 
We wish to thank David Gentien from Curie Institute Paris for assistance in microarray experiments on the Affymetrix platform, Michel Volovitch and Alain Aurias for helpful discussions, John Ngai and Jean Yee Hwa Yang from UCSF and Nidhi Saran and Roger Reeves from Johns Hopkins Medical School for providing raw data from their published work. This work was supported by EEC grant 00816 to M.C.P. and S.E.A., Fondation Jérôme Lejeune grants to M.C.P. and P.M.S. and to S.E.A., grant from the Ministère de la Recherche to M.C.P., NIH grant HD-31498 to C.J.E., the Swiss National Science Foundation, NCCR Frontiers in Genetics, the ChildCare Foundation to S.E.A. and the Université Paris 5. G.G. had a fellowship from the Fondation Jérôme Lejeune France and RXM a C.J. Martin fellowship from NHMRC Australia.


   SUPPLEMENTARY MATERIAL
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
REFERENCES
 
Supplementary Material is available on HMG Online.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 SUPPLEMENTARY MATERIAL
 REFERENCES
 

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