Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS.
Amanda Dobbyn,Laura M. Huckins,James Boocock,Laura G. Sloofman,Benjamin S. Glicksberg,Claudia Giambartolomei,Gabriel E. Hoffman,Thanneer M. Perumal,Kiran Girdhar,Yan Jiang,Towfique Raj,Douglas M. Ruderfer,Robin Kramer,Dalila Pinto,Schahram Akbarian,Panos Roussos,Enrico Domenici,Bernie Devlin,Pamela Sklar,Eli A. Stahl,Solveig K. Sieberts +20 more
TLDR
It is shown that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations and supports previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.Abstract:
Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.read more
Citations
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Integrative analysis of 111 reference human epigenomes
Anshul Kundaje,Wouter Meuleman,Jason Ernst,Angela Yen,Pouya Kheradpour,Zhizhuo Zhang,Jianrong Wang,Lucas D. Ward,Abhishek Sarkar,Gerald Quon,Matthew L. Eaton,Yi-Chieh Wu,Andreas R. Pfenning,Xinchen Wang,Melina Claussnitzer,Yaping Liu,Mukul S. Bansal,Soheil Feizi-Khankandi,Ah Ram Kim,Richard C Sallari,Nicholas A Sinnott-Armstrong,Laurie A. Boyer,Elizabeta Gjoneska,Li-Huei Tsai,Manolis Kellis +24 more
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
ChromHMM: automating chromatin-state discovery and characterization
TL;DR: ChromHMM is developed, an automated computational system for learning chromatin states, characterizing their biological functions and correlations with large-scale functional datasets, and visualizing the resulting genome-wide maps of chromatin state annotations.
Journal ArticleDOI
Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.
Solveig K. Sieberts,Thanneer M. Perumal,Minerva M. Carrasquillo,Mariet Allen,Joseph S. Reddy,Gabriel E. Hoffman,Kristen K. Dang,John N. Calley,Phillip J. Ebert,James A. Eddy,Xue Wang,Anna K. Greenwood,Sara Mostafavi,Sara Mostafavi,S Akbarian,J Bendl,M S Breen,K Brennand,L Brown,A Browne,J D Buxbaum,A Charney,Andrew Chess,Couto L,Gregory E. Crawford,Devillers O,Bernie Devlin,Amanda Dobbyn,E Domenici,M Filosi,E Flatow,Nancy Francoeur,John F. Fullard,S E Gil,Kiran Girdhar,A Gulyás-Kovács,R.E. Gur,C G Hahn,Vahram Haroutunian,Mads E. Hauberg,Laura M. Huckins,Rivka Jacobov,Y Jiang,Jessica S. Johnson,Bibi Kassim,Y Kim,Lambertus Klei,Robin Kramer,Mario Lauria,Thomas Lehner,David A. Lewis,Barbara K. Lipska,Kelsey S. Montgomery,R Park,C Rosenbluh,Panagiotis Roussos,Douglas M. Ruderfer,G Senthil,Hardik Shah,Laura G. Sloofman,L Song,E Stahl,P.F. Sullivan,R Visintainer,J Wang,Y C Wang,Jennifer Wiseman,E Xia,W Zhang,Elizabeth Zharovsky,L Addis,S N Addo,David C. Airey,Matthias Arnold,David A. Bennett,Y Bi,K Biber,Colette Blach,E Bradhsaw,Paul Brennan,R Canet-Aviles,S Cao,A Cavalla,Yooree Chae,W W Chen,J Cheng,David A. Collier,J L Dage,Eric B. Dammer,J W Davis,John B. Davis,Derek Drake,D Duong,Brian J. Eastwood,Michelle E. Ehrlich,B Ellingson,B W Engelmann,S Esmaeelinieh,Daniel Felsky,Cory C. Funk,Chris Gaiteri +100 more
TL;DR: A colocalization analysis is applied to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalized with lncRNA RP11-677M14.
Journal ArticleDOI
Synergistic effects of common schizophrenia risk variants.
Nadine Schrode,Seok-Man Ho,Kazuhiko Yamamuro,Amanda Dobbyn,Laura M. Huckins,Marliette R. Matos,Esther Cheng,P J Michael Deans,Erin Flaherty,Natalie Barretto,Aaron Topol,Khaled Alganem,Sonya Abadali,James Gardner Gregory,Emily Hoelzli,Hemali Phatnani,Vineeta Singh,Deeptha Girish,Bruce J. Aronow,Robert E. McCullumsmith,Gabriel E. Hoffman,Eli A. Stahl,Hirofumi Morishita,Pamela Sklar,Kristen J. Brennand +24 more
TL;DR: It is proposed that the links between rare and common variants implicated in psychiatric disease risk constitute a potentially generalizable phenomenon occurring more widely in complex genetic disorders.
Journal ArticleDOI
Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk.
Prashanth Rajarajan,Tyler M. Borrman,Will Liao,Nadine Schrode,Erin Flaherty,Charlize Casiño,Samuel K. Powell,Chittampalli Yashaswini,Elizabeth A. LaMarca,Bibi Kassim,Behnam Javidfar,Sergio Espeso-Gil,Aiqun Li,Hyejung Won,Daniel H. Geschwind,Seok-Man Ho,Matthew L. MacDonald,Gabriel E. Hoffman,Panos Roussos,Bin Zhang,Chang-Gyu Hahn,Zhiping Weng,Kristen J. Brennand,Schahram Akbarian +23 more
TL;DR: This study shows that neural differentiation is associated with highly cell type–specific 3DG remodeling, which is paralleled by an expansion of3DG space associated with SZ risk, and tests whether the neural cell–specific SZ-related “chromosomal connectome” showed evidence of coordinated transcriptional regulation and proteomic interaction of the participating genes.
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