Functional mapping of noncoding regulatory variants in human neuronal subtypes3.

Complex neuropsychiatric disorders, including schizophrenia and autism spectrum disorder (ASD) among others, impose an enormous socioeconomic burden on families and on society. The pathobiological mechanisms are largely unknown, and treatment options are limited and often incompletely effective. During the past decade, advances in human genetics and next-generation sequencing, coupled with expanding cohort sizes, have permitted the identification of thousands of genetic variants that influence risk for neuropsychiatric diseases. Each disease-associated variants identified by genome-wide association studies (GWAS) could provide insights into a biological mechanism that underlies the risk of disease in humans. However, the availability of data is not synonymous with the presence of meaning. The challenge researchers are facing now is the derivation of biological meaning post-GWAS. Particularly, more than 90% of the risk variants are found in the non-coding regions of the human genome. Although the potential contribution of non-coding variants to complex human diseases has long been speculated, it has been a major challenge to develop testable hypotheses to decipher their role in disease etiology. Here, we propose to develop innovative multidisciplinary approaches to bridge the gap between human genetics and experimental biology. The major hypothesis underlying the approach is that epigenetic changes caused by non-coding variation in the cis-regulatory elements, particularly enhancers that are platforms for sequence-specific transcription factor binding and can influence gene transcription over long distance, may confer disease liability by disrupting gene expression. We aim to (i) annotate functionally distinct enhancers in disease-relevant human neuronal subtypes generated by reprogramming of pluripotent stem cells, (ii) apply the cutting-edge HiChIP technology to profile the promoter-enhancer interactions in neurons in resting and active states, and identify the target genes of enhancers, finally, (iii) we will determine how disease- associated variants affect enhancer activity in human neurons. Such effort will provide the foundation to map and prioritize non-coding risk variants for future mechanistic studies. Especially, the enhancer-interactome analysis performed in this study will provide a physical-interaction-based approach for the identification of enhancer target genes in neurons. The information will lay the groundwork for developing testable hypotheses to elucidate the molecular impact of risk variants in non-coding regions. Last but not least, determining how non- coding risk variants disrupt activity-regulated gene expression in neuronal subtypes may uncover novel disease- relevant biology not observed using the incomplete existing methodologies and resources (activity-responsive enhancers are not possible to identify from post-mortem tissue). Once accomplished, the proposed work will have broad impact on translating genetic discoveries into actionable biological hypotheses that can potentially power a new round of development of novel therapeutics strategies for complex neuropsychiatric disorders.