Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
Author(s)
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; 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; 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.; ... Show more Show less![Thumbnail](/bitstream/handle/1721.1/135294.2/s41597-020-00642-8.pdf.jpg?sequence=2&isAllowed=y)
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© 2020, The Author(s). 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).
Date issued
2020-10Department
Picower Institute for Learning and MemoryJournal
Scientific Data
Publisher
Springer Science and Business Media LLC
ISSN
2052-4463