Going from Genetic Associations to Identification of Causative Genes

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ABSTRACT Many studies, including analyses in this overall Program of research, have conducted genome-wide association studies (GWAS) to identify genes and loci associated with complex disease. While a number of genetic association signals have been uncovered, the challenge of identifying causative genes at these genetic loci remains. As such, the goal of this Project is to move from GWAS association to identification of causal effector genes relevant to obstructive sleep apnea (OSA) and excessive sleepiness, two key traits studied in this Program. To fill this critical gap in evidence this Project combines state-of-the-art approaches in cell-based and animal models. Analyses will begin by interrogating genetic loci from recent GWAS on OSA and sleepiness, and be extended to evaluate loci from ongoing analyses, including those in Projects 01 and 03. In Aim 1, we will conduct in silico physical `variant to gene mapping' based on our established Assay for Transposase Accessible Chromatin sequencing (ATAC-seq) plus genome-wide promotor-focused Capture C data on relevant cell types - osteoblasts and adipocytes (for anatomy; relevant to Project 01) and neurons and primary astrocytes (for sleepiness; relevant to Project 03). These 3D Genomics analyses will identify the most likely causal genes and variants by determining which candidates at implicated loci directly interact with regions of open chromatin. After identifying likely causal genes and variants, follow-up analyses in animal models will be performed to understand if candidate effector genes act by affecting OSA-related anatomy in mice (Aim 2) and sleep behavior reflective of sleepiness and disturbed sleep in Drosophila and zebrafish (Aim 3). Specifically, Aim 2 will utilize the novel multivariate genotype-phenotype mapping pipeline we developed to identify causal genes affecting OSA risk through effects on craniofacial shape and/or tongue fat. In applying this method, this Aim leverages both existing and newly generated data in a large sample of Diversity Outbred mice with genetic data and anatomical traits quantified via imaging. This cutting-edge approach facilitates determination of the effects of multiple genes on multivariate phenotypes using high-dimensional data to compare directions, not just magnitudes, of associations. For sleepiness, Aim 3 will utilize Drosophila RNAi lines to study the impact of knocking-down candidate genes on sleep-related phenotypes (including sleep amounts, sleep fragmentation, and sleep drive). Then, genes shown to affect sleep in Drosophila will be validated in a vertebrate model by utilizing CRISPR-Cas9 methods to knock-out these same genes in zebrafish and studying the effects on similar sleep phenotypes. Taken together, results in this Project and the other projects in this Program will provide essential knowledge about effector genes for OSA and for sleepiness in OSA in humans. This knowledge is crucial for understanding the biological and clinical impact of GWAS associations, and will facilitate more efficient clinical translation and incorporation of genetic evidence into precision medicine approaches to OSA, as well as provide an important resource for the broader scientific community and proof of principle for the field of applied genomics in OSA.