Using three-dimensional regulatory chromatin interactions from adult and fetal cortex to interpret genetic results for psychiatric disorders and cognitive traits
Cheynna A Crowley,
Joshua S. Martin,
S. Colby Allred,
Nicholas J. Bray,
Cynthia M. Bulik,
James J. Crowley,
Philip R Jansen,
George J Jurjus,
Patrick F Sullivan,
Michael C O'Donovan,
James C Overholser,
Michael J Owen,
Antonio F. Pardiñas,
Jeanne E Savage,
Craig A. Stockmeier,
James TR Walters,
Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Eating Disorders Working Group of the Psychiatric Genomics Consortium,
Gregory E. Crawford,
Posted 31 Aug 2018
bioRxiv DOI: 10.1101/406330
Posted 31 Aug 2018
Genome-wide association studies have identified hundreds of genetic associations for complex psychiatric disorders and cognitive traits. However, interpretation of most of these findings is complicated by the presence of many significant and highly correlated genetic variants located in non-coding regions. Here, we address this issue by creating a high-resolution map of the three-dimensional (3D) genome organization by applying Hi-C to adult and fetal brain cortex with concomitant RNA-seq, open chromatin (ATAC-seq), and ChIP-seq data (H3K27ac, H3K4me3, and CTCF). Extensive analyses established the quality, information content, and salience of these new Hi-C data. We used these data to connect 938 significant genetic loci for schizophrenia, intelligence, ADHD, alcohol dependence, Alzheimer's disease, anorexia nervosa, autism spectrum disorder, bipolar disorder, major depression, and educational attainment to 8,595 genes (with 42.1% of these genes implicated more than once). We show that assigning genes to traits based on proximity provides a limited view of the complexity of GWAS findings and that gene set analyses based on functional genomic data provide an expanded view of the biological processes involved in the etiology of schizophrenia and other complex brain traits.
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