High-throughput identification of causal variants underlying neuropsychiatric disease-related GWAS hits

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Project Summary Neuropsychiatric diseases affect millions of people world-wide. Genome-wide association studies (GWAS) have identified a growing number of sequence variants associated with neuropsychiatric diseases and related traits, but the majority of these GWAS hits fall within non-coding regions and their functional effects are difficult to decipher. We hypothesize that the majority of functional non-coding variants related to neuropsychiatric disease fall within brain cis-regulatory elements (CREs; i.e., enhancers/promoters), and exert their effects by disrupting transcription factor (TF) binding sites and thereby altering the expression level of genes encoding proteins expressed in the brain, particularly the cerebral cortex. To identify causal variants underlying neuropsychiatric disease-related GWAS hits and to map neuropsychiatric disease-related CREs, we propose to implement a technique called CRE-seq (Cis-Regulatory Element analysis by sequencing). In CRE-seq, individual CREs are fused to reporter genes, each containing a unique DNA barcode. The resultant CRE-reporter library, consisting of thousands of constructs, is introduced into living tissue, and reporter gene expression is quantified by counting barcoded transcripts with RNA-seq. CRE-seq promises to greatly accelerate our ability to measure the effects of cis-regulatory variants in neuropsychiatric disease. To achieve this goal, we propose two Specific Aims. In Aim 1, we will use CRE-seq to identify causal cis-regulatory variants at all known GWAS loci associated with neuropsychiatric diseases and related traits. We will measure the cis-regulatory activity of thousands of wild-type and variant CREs in mouse cerebral cortex in vivo and in human iPSC-derived forebrain organoids via adeno-associated virus (AAV)-mediated CRE-seq library delivery. We will then evaluate the functional effects of selected variants on TF binding using protein-microarrays containing all known human TFs. Lastly, we will correlate the results of our CRE-seq analyses with brain eQTL data. In Aim 2, we will establish a template for interpreting rare neuropsychiatric disease-related variants by systematically mapping the location of human brain CREs. We will utilize a 'capture and clone' strategy for CRE-seq library construction, which permits analysis of long (i.e., ~500 bp) tiled reporters at each locus. In this way, we will pinpoint essential TF binding sites (TFBSs) which are the likely targets of rare functional variants. Next, we will use CRE-seq to analyze the effects of introducing all possible single-nucleotide substitutions into identified TFBSs. As in Aim 1, we will perform CRE- seq in both mouse brain and human iPSC-derived cerebral organoids. Taken together, these two Aims will enable functional interpretation of both common and rare variants in individual human genomes and thereby facilitate assessment of neuropsychiatric disease risk in patients.