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• W1966235930 abstract "Abstract Background Transcriptional dysregulation is an early, key pathogenic mechanism in Huntington's disease (HD). Therefore, gene expression analyses have biomarker potential for measuring therapeutic efficacy in pre-clinical trials, particularly those aimed at correcting gene expression abnormalities. Housekeeping genes are commonly used as endogenous references in gene expression studies. However, a systematic study comparing the suitability of candidate reference genes for use in HD mouse models has not been performed. To remedy this situation, 12 housekeeping genes were examined to identify suitable reference genes for use in expression assays. Results We found that commonly used reference genes are dysregulated at later time points in the R6/2 mouse model of HD. Therefore, in order to reliably measure gene expression changes for use as pre-clinical trial biomarkers, we set out to identify suitable reference genes for use in R6/2 mice. The expression of potential reference genes was examined in striatum, cortex and cerebellum from 15 week old R6/2 and matched wild-type littermates. Expression levels of candidate reference genes varied according to genotype and brain region. GeNorm software was used to identify the three most stably expressed genes for each brain region. Relative quantification methods using the geometric mean of three reference genes for normalisation enables accurate determination of gene expression levels in wild-type and R6/2 mouse brain regions. Conclusion Our study has identified a reproducible, reliable method by which we able to accurately determine the relative expression level of target genes in specific brain regions, thus increasing the potential of gene expression analysis as a biomarker in HD pre-clinical trials." @default.
• W1966235930 created "2016-06-24" @default.
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• W1966235930 date "2008-10-27" @default.
• W1966235930 modified "2023-09-28" @default.
• W1966235930 title "Optimisation of region-specific reference gene selection and relative gene expression analysis methods for pre-clinical trials of Huntington's disease" @default.
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• W1966235930 doi "https://doi.org/10.1186/1750-1326-3-17" @default.
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