Project description:Comparative analysis of cerebellar gene expression changes occurring in Sca1154Q/2Q and Sca7266Q/5Q knock-in mice; Polyglutamine diseases are inherited neurodegenerative disorders caused by expansion of CAG repeats encoding a glutamine tract in the disease-causing proteins. There are nine disorders each having distinct features but also clinical and pathological similarities. In particular, spinocerebellar ataxia type 1 and type 7 (SCA1 and SCA7) patients manifest cerebellar ataxia with degeneration of Purkinje cells. To determine whether the disorders share molecular pathogenic events, we studied two mouse models of SCA1 and SCA7 that express the glutamine-expanded protein from the respective endogenous loci. We found common transcriptional changes, with down-regulation of Insulin-like growth factor binding protein 5 (Igfbp5) representing one of the most robust changes. Igfbp5 down-regulation occurred in granule neurons through a non-cell autonomous mechanism and was concomitant with activation of of the Insulin-like growth factor (IGF) pathway and the type I IGF receptor on Purkinje cells. These data define one common pathogenic response in SCA1 and SCA7 and reveal the importance of intercellular mechanisms in their pathogenesis. Given that SCA1 and SCA7 share a cerebellar degenerative phenotype, we proposed that some shared molecular changes might occur in both diseases, and that common molecular alterations could pinpoint pathways that could be targeted to modulate or monitor the pathogenesis of more than one disease. We focused on transcriptional changes because both ATXN1 and ATXN7 play roles in transcriptional regulation and transcriptional defects can be detected in early-symptomatic stages of both SCA1 and SCA7 mouse models. To test our hypothesis, we examined cerebellar gene expression patterns in SCA1 and SCA7 knock-in (KI) models--Sca1154Q/2Q and Sca7266Q/5Q mice. Experiment Overall Design: Total cerebellar RNA samples were collected from Sca1154Q/2Q knock-in and wild type mice at the early symptomatic disease stage (4 weeks, n=3 knock-in and 3 wild type; 9-12 weeks, n=3 knock-in and 3 wild type). In parallel experiments, total cerebellar RNA samples were collected from Sca7266Q/5Q knock-in and wild type mice also at the early symptomatic disease stage (5 weeks, n=5 knock-in and 5 wild type).

Project description:Transcriptional profiling of mouse cerebellar extract comparing SCA7 KI mice with wild type mice. Female mice were killed by decapitation on post natal days 10 and 22 and 11 weeks. Goal was to determine gene expression profiles differing between SCA7 KI mice and wild-type mice during post-natal developement of the cerebellum. Gene expression profiling was performed using RNA extracted from the cerebellum of KI and WT mice at P10 (5 WT and 5 KI), P22 (5 WT and 4 KI) and 11 wks (5WT and 6 KI). After labeling, RNAs were hybridized on dual-label G4122F AgilentM-BM-. chips; a mix of all P10 samples was used as common reference (green channel). Quality control included visual control of the reconstructed image of the chip, M/A plot, corner intensities, outliers, positive and negative intensities, normalization factors. Normalization and statistical analyses were carried out by using BRB-array Tools developed by Dr. Richard Simon and the BRB-ArrayTools development team (Biometrics Research Branch, http://linus.nci.nih.gov/BRB-ArrayTools.html). Genes with less than 50% present calls or with low variability along the arrays (less than 20% of values with at least 2-fold change in either direction from the geneM-bM-^@M-^Ys median value) were excluded from further analysis. For the 1905 remaining probes an interaction between time and genotype was analyzed by regression analysis of the time course of expression. In brief, probes for which variation over time differed for the genotype class were fitted to the following model: log expression ~ time + time**2 + genotype + genotype*time + genotype*time**2. A univiariate p-value < 0.001 (random variance model) was set for significant probes (genotype*time + genotype*time**2) and a False Discovery Rate (FDR) was calculated for each probe (Benjamini & Hochberg, 1995). Differences in profiles were identified with a Self Organisation Tree Algorithm (MultiplExperiment Viewer (MeV), (Saeed et al, 2006). Expression values were averaged by group and then clustered according to their profile as a function of time.

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Mus musculus

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