Parkinson-associated risk variant in distal enhancer of alpha-synuclein modulates target gene expression | |
Article | |
关键词: GENOME-WIDE ASSOCIATION; ADULT HUMAN BRAIN; STEM-CELLS; INTEGRATIVE ANALYSIS; GENOTYPE IMPUTATION; REGULATORY DNA; HUMAN-DISEASE; METAANALYSIS; LOCUS; IDENTIFICATION; | |
DOI : 10.1038/nature17939 | |
来源: SCIE |
【 摘 要 】
Genome-wide association studies (GWAS) have identified numerous genetic variants associated with complex diseases, but mechanistic insights are impeded by a lack of understanding of how specific risk variants functionally contribute to the underlying pathogenesis(1). It has been proposed that cis-acting effects of non-coding risk variants on gene expression are a major factor for phenotypic variation of complex traits and disease susceptibility. Recent genome-scale epigenetic studies have highlighted the enrichment of GWAS-identified variants in regulatory DNA elements of disease-relevant cell types(2-6). Furthermore, single nucleotide polymorphism (SNP)specific changes in transcription factor binding are correlated with heritable alterations in chromatin state and considered a major mediator of sequence-dependent regulation of gene expression(7-10). Here we describe a novel strategy to functionally dissect the cis-acting effect of genetic risk variants in regulatory elements on gene expression by combining genome-wide epigenetic information with clustered regularly-interspaced short palindromic repeats (CRISPR)/Cas9 genome editing in human pluripotent stem cells. By generating a genetically precisely controlled experimental system, we identify a common Parkinson's disease associated risk variant in a non-coding distal enhancer element that regulates the expression of a-synuclein (SNCA), a key gene implicated in the pathogenesis of Parkinson's disease. Our data suggest that the transcriptional deregulation of SNCA is associated with sequence-dependent binding of the brain-specific transcription factors EMX2 and NKX6-1. This work establishes an experimental paradigm to functionally connect genetic variation with disease-relevant phenotypes.
【 授权许可】
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