Comprehensive functional genomic resource and integrative model for the human brain
Authors
Wang, DaifengMattei, Eugenio
Moore, Jill E.
Weng, Zhiping
Geschwind, Daniel H.
Knowles, James A.
Gerstein, Mark B.
UMass Chan Affiliations
Program in Bioinformatics and Integrative BiologyDocument Type
Journal ArticlePublication Date
2018-12-14Keywords
psychiatric disordersPsychENCODE Consortium
genes
genome
Bioinformatics
Computational Biology
Computational Neuroscience
Genetic Phenomena
Genomics
Integrative Biology
Mental Disorders
Metadata
Show full item recordAbstract
Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with > 88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.Source
Science. 2018 Dec 14;362(6420). pii: eaat8464. doi: 10.1126/science.aat8464. Link to article on publisher's site
DOI
10.1126/science.aat8464Permanent Link to this Item
http://hdl.handle.net/20.500.14038/25854PubMed ID
30545857Notes
Full author list omitted for brevity. For the full list of authors, see article.
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10.1126/science.aat8464