The American Journal of Human GeneticsGeneticsPeer-reviewed journal article
Parkinson-associated SNCA enhancer variants revealed by open chromatin in mouse dopamine neurons
Sarah A. McClymontiD, Paul W. HookiD, Alexandra I. Soto, Xylena ReediD, William Law, Samuel J. Kerans, Eric L. WaiteiD, Nicole BricenoiD, Joseph F. TholeiD, Michael G. HeckmaniD, Nancy N. DiehliD, Zbigniew K. WszołekiD, Cedric D. MooreiD, Heng ZhuiD, Jennifer A. AkiyamaiD, Diane E. DickeliD, Axel ViseliD, Len A. PennacchioiD, Owen A. RossiD, M BeeriD, Andrew S. McCallioniD
Abstract
The progressive loss of midbrain (MB) dopaminergic (DA) neurons defines the motor features of Parkinson disease (PD) and modulation of risk by common variation in PD has been well established through GWAS. Anticipating that a fraction of PD-associated genetic variation mediates their effects within this neuronal population, we acquired open chromatin signatures of purified embryonic mouse MB DA neurons. Correlation with >2,300 putative enhancers assayed in mice reveals enrichment for MB cis-regulatory elements (CRE), data reinforced by transgenic analyses of six additional sequences in zebrafish and mice. One CRE, within intron 4 of the familial PD gene SNCA, directs reporter expression in catecholaminergic neurons of transgenic mice and zebrafish. Sequencing of this CRE in 986 PD patients and 992 controls reveals two common variants associated with elevated PD risk. To assess potential mechanisms of action, we screened >20,000 DNA interacting proteins and identify a subset whose binding is impacted by these enhancer variants. Additional genotyping across the SNCA locus identifies a single PD-associated haplotype, containing the minor alleles of both of the aforementioned PD-risk variants. Our work posits a model for how common variation at SNCA may modulate PD risk and highlights the value of cell context-dependent guided searches for functional non-coding variation.
- organism: mouse
- organism: zebrafish
- assay: ChIP-seq
- assay: DNA methylation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 51
- FWCI
- 3.39
- Field percentile
- top 7%
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