Great progress has been made in mapping functional units of the genome as well as the epigenome through the efforts of the ENCODE project, such work has mainly been carried out in cell lines and peripheral tissues. The goal of our PsychENCODE project is to construct detailed maps for multiple important chromatin modifications in a tissue of specific relevance to schizophrenia (SCZ), human neurons and glia, and subsequently assess the relationship of several of these marks to known genetic risk factors for SCZ. We will first broadly survey a series of important chromatin marks in two brain regions, the pre-frontal cortex and anterior cingulate cortex, in limited number of samples to provide brain and neuronal specific maps of the chromatin marks. We will then focus deeply on a single region, the pre-frontal cortex, and on an important promoter and enhancer mark, in a large sample of post-mortem human brain samples. Specifically, we will first, map cell-type specific transcriptome and epigenome components in cortical tissue homogenates and in neuronal and non-neuronal chromatin in nuclei from normal human adult brain (n=20) using fluorescence- activated cell sorting followed by ChIP-Seq. Second, we will map promoter (H3K4me3) and enhancer (H3K27ac) marks in neuronal chromatin of the prefrontal cortex of 328 cases with SCZ, and 315 controls. We will integrate genome-wide SNP, CNV and brain mRNA expression with the neuronal ChIP-seq promoter and enhancer marks to identify novel SCZ genes using a variety of analytic strategies including constructing weighted interaction and causal probabilistic SCZ networks to identify key drivers and subnetworks underlying SCZ. Finally, we will map distal enhancer elements using chromosome conformation capture and investigate the role of medication confounds on mapping results. Our PsychENCODE project will apply innovative techniques and analytic strategies including cell-type specific epigenome mapping, chromosome conformation capture, deconvolution mapping and construction of causal probabilistic network analyses. All data will be made available to the research community through the Sage Bionetworks Synapse Platform. There is a deep need to understand the epigenetic landscape in the human brain, and in particular in neurons and glia and to integrate this information with human SCZ genetics. We have assembled the critical key personnel, sample resources, technological know-how, and analytic strategies to be able to provide both useful maps for the field, as well as begin to unravel SCZ biology.
In the United States, over a million people have schizophrenia. The costs are staggering in human and financial terms. We propose to develop methods for integrating a broad range of genomic and epi- (Greek for 'over', 'above') genetic data collected from hundreds of postmortem brain samples from controls and from subjects who were diagnosed with schizophrenia. These data will provide a much needed resource to explore the genetic risk architecture and neurobiology of the disorder.
|Roussos, Panos; Mitchell, Amanda C; Voloudakis, Georgios et al. (2014) A role for noncoding variation in schizophrenia. Cell Rep 9:1417-29|