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Combined normalized raw datasets of Luciferase assays on SNCA conserved elements

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Résumé fourni par la source

Several single nucleotide polymorphisms (SNPs) and the Rep-1 microsatellite marker of the α-synuclein ( SNCA ) gene have consistently been shown to be associated with Parkinson’s disease, but the functional relevance is unclear. Based on these findings we hypothesized that conserved cis-regulatory elements in the SNCA genomic region regulate expression of SNCA , and that SNPs in these regions could be functionally modulating the expression of SNCA , thus contributing to neuronal demise and predisposing to Parkinson’s disease. In a pair-wise comparison of a 206kb genomic region encompassing the SNCA gene, we revealed 32 evolutionary conserved DNA sequences between human and mouse. All elements were cloned into reporter vectors and assessed for expression modulation in dual luciferase reporter assays. We found that 11 out of 32 elements exhibited either an enhancement or reduction of the expression of the reporter gene. Three elements upstream of the SNCA gene displayed an approximately 1.5 fold (p<0.009) increase in expression. Of the intronic regions, three showed a 1.5 fold increase and two others indicated a 2 and 2.5 fold increase in expression (p<0.002). Two elements downstream of the SNCA gene showed 1.5 fold and 2.5 fold increase (p<0.0009). One element downstream of SNCA had a reduced expression of the reporter gene of 0.35 fold (p<0.0009) of normal activity. Our results demonstrate that the SNCA gene contains cis-regulatory regions that might regulate the transcription and expression of SNCA . Further studies in disease-relevant tissue types will be important to understand the functional impact of regulatory regions and specific Parkinson’s disease-associated SNPs and its function in the disease process.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Combined normalized raw datasets of Luciferase assays on SNCA conserved elements
Date Crossref
24/11/2025
Éditeur
F1000 Research Ltd
Type
dataset

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