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  • 标题:Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
  • 本地全文:下载
  • 作者:Solveig K. Sieberts ; Thanneer M. Perumal ; Minerva M. Carrasquillo
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2020
  • 卷号:7
  • 期号:1
  • 页码:1-11
  • DOI:10.1038/s41597-020-00642-8
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer鈥檚 Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).
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