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- Title
Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.
- Authors
Sieberts, Solveig K.; Perumal, Thanneer M.; Carrasquillo, Minerva M.; Allen, Mariet; Reddy, Joseph S.; Hoffman, Gabriel E.; Dang, Kristen K.; Calley, John; Ebert, Philip J.; Eddy, James; Wang, Xue; Greenwood, Anna K.; Mostafavi, Sara; The CommonMind Consortium (CMC); Akbarian, Schahram; Bendl, Jaroslav; Breen, Michael S.; Brennand, Kristen; Brown, Leanne; Browne, Andrew
- Abstract
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's 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).
- Subjects
NUCLEOTIDE sequence; GENOTYPES; AUTOPSY; ALZHEIMER'S disease; META-analysis; CEREBRAL cortex; CEREBELLUM
- Publication
Scientific Data, 2020, Vol 7, Issue 1, pN.PAG
- ISSN
2052-4463
- Publication type
Article
- DOI
10.1038/s41597-020-00642-8