Figure 1. Advancing genetic findings with functional epigenomic information and integration. Genetic analyses identify common variation associated with schizophrenia (SZ) risk using genome-wide association studies (GWAS), as indicated by the Manhattan plot (left). Most variants do not alter protein structure and may have diverse regulatory functions (eg, enhancer, repressor, regulator of splicing, etc). Quantitative mapping approaches (middle) can measure transcript abundance and 
splicing (RNA-seq); chromatin state through histone modifications (ChIP-seq), DNA methylation, identification of active/
open chromatin (ATAC-seq, DNase-seq); and higher-order chromatin conformations (Hi-C, HiChIP, Capture-C). Integration 
of these functional datasets with the genetic architecture from GWAS can identify putative causal variants that impact any one (or more) of the epigenetic features listed above, providing a mechanism for potential gene dysregulation converging 
on important neural and developmental pathways.