TY - JOUR
T1 - Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
AU - The CommonMind Consortium (CMC)
AU - The AMP-AD Consortium
AU - Sieberts, Solveig K.
AU - Perumal, Thanneer M.
AU - Carrasquillo, Minerva M.
AU - Allen, Mariet
AU - Reddy, Joseph S.
AU - Hoffman, Gabriel E.
AU - Dang, Kristen K.
AU - Calley, John
AU - Ebert, Philip J.
AU - Eddy, James
AU - Wang, Xue
AU - Greenwood, Anna K.
AU - Mostafavi, Sara
AU - Akbarian, Schahram
AU - Bendl, Jaroslav
AU - Breen, Michael S.
AU - Brennand, Kristen
AU - Brown, Leanne
AU - Browne, Andrew
AU - Buxbaum, Joseph D.
AU - Charney, Alexander
AU - Chess, Andrew
AU - Couto, Lizette
AU - Crawford, Greg
AU - Devillers, Olivia
AU - Devlin, Bernie
AU - Dobbyn, Amanda
AU - Domenici, Enrico
AU - Filosi, Michele
AU - Flatow, Elie
AU - Francoeur, Nancy
AU - Fullard, John
AU - Gil, Sergio Espeso
AU - Girdhar, Kiran
AU - Gulyás-Kovács, Attila
AU - Gur, Raquel
AU - Hahn, Chang Gyu
AU - Haroutunian, Vahram
AU - Hauberg, Mads Engel
AU - Huckins, Laura
AU - Jacobov, Rivky
AU - Johnson, Jessica S.
AU - Rosenbluh, Chaggai
AU - Roussos, Panagiotis
AU - Ruderfer, Douglas M.
AU - Xia, Eva
AU - Ehrlich, Michelle
AU - Gandy, Samuel
AU - Haroutunian, Vahram
AU - Wang, Minghui
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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).
AB - 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).
UR - http://www.scopus.com/inward/record.url?scp=85092511647&partnerID=8YFLogxK
U2 - 10.1038/s41597-020-00642-8
DO - 10.1038/s41597-020-00642-8
M3 - Article
C2 - 33046718
AN - SCOPUS:85092511647
SN - 2052-4463
VL - 7
JO - Scientific data
JF - Scientific data
IS - 1
M1 - 340
ER -