Genomic landscape and functional characterization of structural variations in schizophrenia and bipolar disorder

Multiple types of variations have been postulated to confer risk of schizophrenia and bipolar disorder, but majority of present GWAS solely focused on SNPs or small indels, and the impacts of structural variations (SVs) remain less understood. Nevertheless, accumulating evidence suggest that SVs may explain the association signals in certain GWAS hits. Here, we conducted pairwise linkage disequilibrium (LD) analyses of SNPs and SVs in populations from 1000 Genomes Project. Among the 299 psychiatric GWAS loci, 1213 SVs showed an LD of r2 > 0.1 with GWAS risk SNPs, and 66 of them were in moderate to strong LD (r2 > 0.6) with at least one GWAS risk SNP. Nine SVs were subject to further explorative analyses, including eQTL analysis in DLPFC, luciferase reporter gene assays, CRISPR/Cas9-mediated genome deletion and RT-qPCR. These assays highlighted several functional SVs showing regulatory effects on transcriptional activities, and some risk genes (e.g., BORCS7, GNL3) affected by the SVs were also annotated. Finally, mice overexpressing Borcs7 in the mPFC exhibited schizophrenia-like behaviors, such as abnormal prepulse inhibition and social dysfunction. These data suggest that SNPs association signals at GWAS loci might be driven by SVs, highlighting the necessities of considering such variants in future.