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

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-an...

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Autores principales: 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, Omberg, Larsson, Peters, Mette A., Logsdon, Benjamin A., De Jager, Philip L., Ertekin-Taner, Nilüfer, Mangravite, Lara M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550587/
https://www.ncbi.nlm.nih.gov/pubmed/33046718
http://dx.doi.org/10.1038/s41597-020-00642-8
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author 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
Omberg, Larsson
Peters, Mette A.
Logsdon, Benjamin A.
De Jager, Philip L.
Ertekin-Taner, Nilüfer
Mangravite, Lara M.
author_facet 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
Omberg, Larsson
Peters, Mette A.
Logsdon, Benjamin A.
De Jager, Philip L.
Ertekin-Taner, Nilüfer
Mangravite, Lara M.
author_sort Sieberts, Solveig K.
collection PubMed
description 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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spelling pubmed-75505872020-10-19 Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions 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 Omberg, Larsson Peters, Mette A. Logsdon, Benjamin A. De Jager, Philip L. Ertekin-Taner, Nilüfer Mangravite, Lara M. Sci Data Analysis 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). Nature Publishing Group UK 2020-10-12 /pmc/articles/PMC7550587/ /pubmed/33046718 http://dx.doi.org/10.1038/s41597-020-00642-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Analysis
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
Omberg, Larsson
Peters, Mette A.
Logsdon, Benjamin A.
De Jager, Philip L.
Ertekin-Taner, Nilüfer
Mangravite, Lara M.
Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
title Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
title_full Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
title_fullStr Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
title_full_unstemmed Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
title_short Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
title_sort large eqtl meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550587/
https://www.ncbi.nlm.nih.gov/pubmed/33046718
http://dx.doi.org/10.1038/s41597-020-00642-8
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