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. 2020 Oct 12;7(1):340.
doi: 10.1038/s41597-020-00642-8.

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

Solveig K Sieberts  1 , Thanneer M Perumal  2 , Minerva M Carrasquillo  3 , Mariet Allen  3 , Joseph S Reddy  3 , Gabriel E Hoffman  4   5 , Kristen K Dang  2 , John Calley  6 , Philip J Ebert  6 , James Eddy  2 , Xue Wang  3 , Anna K Greenwood  2 , Sara Mostafavi  7   8   9 ; CommonMind Consortium (CMC); The AMP-AD Consortium; Larsson Omberg  2 , Mette A Peters  2 , Benjamin A Logsdon  2 , Philip L De Jager  10 , Nilüfer Ertekin-Taner  3   11 , Lara M Mangravite  12
Collaborators, Affiliations

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

Solveig K Sieberts et al. Sci Data. .

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).

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
eQTL meta-analysis discovers more eQTL than individual cohorts. (a) Quantile-quantile plot of eQTL from individual cohorts as well as the meta-analysis of the true (black) and permuted (light blue) data. Number of significant eQTL (SNP-gene pairs) (b) or genes with significant eQTL (c) as a function of cohort size.
See this image and copyright information in PMC

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