Dissemin is shutting down on January 1st, 2025

Published in

Nature Research, Scientific Data, 1(7), 2020

DOI: 10.1038/s41597-020-00642-8

Links

Tools

Export citation

Search in Google Scholar

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

Journal article published in 2020 by Solveig K. Sieberts, Thanneer M. Perumal ORCID, Minerva M. Carrasquillo, Mariet Allen, Xue Wang, Joseph S. Reddy, Schahram Akbarian, Gabriel E. Hoffman, Jaroslav Bendl, Michael S. Breen, Kristen K. Dang, Kristen Brennand, Leanne Brown, Andrew Browne, Joseph D. Buxbaum and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Red circle
Postprint: archiving forbidden
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

AbstractThe 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).