The PsychENCODE consortium will quantify both coding and noncoding RNA by RNA-seq and long-read sequencing (Iso-seq)

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders.

So far, neither such a comprehensive data set nor any systematic characterization of the functional genomic elements and noncoding RNAs linked to psychiatric disorders is available. The PsychENCODE project was founded to begin to rectify this deficiency and to facilitate research on psychiatric diseases; a list of participating institutions and groups is available at


The genomic data will be generated from tissues, sorted nuclei and cell culture systems. For each data type, regional, cell-type, developmental, sex-specific and disease-related differences will be identified. Different data modalities will be integrated to identify global mechanisms relevant to disease. Bi-directional flow between genetic information and functional data define eQTLs, epiQTLs and pQTLs, which in turn will assist in prioritizing and refining disease. The specific diseases of interest are shown in outer circle; cross-disorder analysis will also be performed for all data types.

Akbarian S et al. (2015) The PsychENCODE project. Nat Neurosci 18(12):1707-12. [abstract]

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