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 , Buxbaum Joseph D. , Charney Alexander , Chess Andrew , Couto Lizette , Crawford Greg , Devillers Olivia , Devlin Bernie , Dobbyn Amanda , Domenici Enrico , Filosi Michele , Flatow Elie , Francoeur Nancy , Fullard John , Gil Sergio Espeso , Girdhar Kiran , Gulyás-Kovács Attila , Gur Raquel , Hahn Chang-Gyu , Haroutunian Vahram , Hauberg Mads Engel , Huckins Laura , Jacobov Rivky , Jiang Yan , Johnson Jessica S. , Kassim Bibi , Kim Yungil , Klei Lambertus , Kramer Robin , Lauria Mario , Lehner Thomas , Lewis David A. , Lipska Barbara K. , Montgomery Kelsey , Park Royce , Rosenbluh Chaggai , Roussos Panagiotis , Ruderfer Douglas M. , Senthil Geetha , Shah Hardik R. , Sloofman Laura , Song Lingyun , Stahl Eli , Sullivan Patrick , Visintainer Roberto , Wang Jiebiao , Wang Ying-Chih , Wiseman Jennifer , Xia Eva , Zhang Wen , Zharovsky Elizabeth ,   The AMP-AD Consortium, Addis Laura , Addo Sadiya N. , Airey David Charles , Arnold Matthias , Bennett David A. , Bi Yingtao , Biber Knut , Blach Colette , Bradhsaw Elizabeth , Brennan Paul , Canet-Aviles Rosa , Cao Sherry , Cavalla Anna , Chae Yooree , Chen William W. , Cheng Jie , Collier David Andrew , Dage Jeffrey L. , Dammer Eric B. , Davis Justin Wade , Davis John , Drake Derek , Duong Duc , Eastwood Brian J. , Ehrlich Michelle , Ellingson Benjamin , Engelmann Brett W. , Esmaeelinieh Sahar , Felsky Daniel , Funk Cory , Gaiteri Chris , Gandy Samuel , Gao Fan , Gileadi Opher , Golde Todd , Grosskurth Shaun E. , Gupta Rishi R. , Gutteridge Alex X. , Haroutunian Vahram , Hooli Basavaraj , Humphryes-Kirilov Neil , Iijima Koichi , James Corey , Jung Paul M. , Kaddurah-Daouk Rima , Kastenmuller Gabi , Klein Hans-Ulrich , Kummer Markus , Lacor Pascale N. , Lah James , Laing Emma , Levey Allan , Li Yupeng , Lipsky Samantha , Liu Yushi , Liu Jimmy , Liu Zhandong , Louie Gregory , Lu Tao , Ma Yiyi , Matsuoka Yasuji Y. , Menon Vilas , Miller Bradley , Misko Thomas P. , Mollon Jennifer E. , Montgomery Kelsey , Mukherjee Sumit , Noggle Scott , Pao Ping-Chieh , Pearce Tracy Young , Pearson Neil , Penny Michelle , Petyuk Vladislav A. , Price Nathan , Quarless Danjuma X. , Ravikumar Brinda , Ried Janina S. , Ruble Cara Lee Ann , Runz Heiko , Saykin Andrew J. , Schadt Eric , Scherschel James E. , Seyfried Nicholas , Shulman Joshua M. , Snyder Phil , Soares Holly , Srivastava Gyan P. , Stockmann Henning , Taga Mariko , Tasaki Shinya , Tenenbaum Jessie , Tsai Li-Huei , Vasanthakumar Aparna , Wachter Astrid , Wang Yaming , Wang Hong , Wang Minghui , Whelan Christopher D. , White Charles , Woo Kara H. , Wren Paul , Wu Jessica W. , Xi Hualin S. , Yankner Bruce A. , Younkin Steven G. , Yu Lei , Zavodszky Maria , Zhang Wenling , Zhang Guoqiang , Zhang Bin , Zhu Jun , Omberg Larsson , Peters Mette A. , Logsdon Benjamin A. , De Jager Philip L. , Ertekin-Taner Nilüfer , Mangravite Lara M. 
Published: October 2020

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).