Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.

Journal Article (Journal Article)

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).

Full Text

Duke Authors

Cited Authors

  • Sieberts, SK; Perumal, TM; Carrasquillo, MM; Allen, M; Reddy, JS; Hoffman, GE; Dang, KK; Calley, J; Ebert, PJ; Eddy, J; Wang, X; Greenwood, AK; Mostafavi, S; CommonMind Consortium (CMC), ; The AMP-AD Consortium, ; Omberg, L; Peters, MA; Logsdon, BA; De Jager, PL; Ertekin-Taner, N; Mangravite, LM

Published Date

  • October 12, 2020

Published In

Volume / Issue

  • 7 / 1

Start / End Page

  • 340 -

PubMed ID

  • 33046718

Pubmed Central ID

  • PMC7550587

Electronic International Standard Serial Number (EISSN)

  • 2052-4463

Digital Object Identifier (DOI)

  • 10.1038/s41597-020-00642-8

Language

  • eng

Conference Location

  • England