Over the last 20 years many thousands of genetic loci have been identified that contribute to complex traits in rodents, including models of common diseases. The findings are expected to advance our understanding of biological mechanisms underlying disease and other traits of biomedical interest, yet relative to the number of successful mapping experiments the yield of novel insights is very small. This is because the mapping experiments have rarely led to the identification of genes. This proposal will radically change this situation by deploying an innovative approach to identifying genes at genetic loci that contribute to variation in complex traits in mice. By using resources and techniques that the PI has developed, including the use of outbred rodents for high-resolution genetic mapping, catalogs of genetic variants in mouse strains from genome sequencing, and methods for gene identification, an efficient and simple protocol will be developed that will allow researchers to rapidly progress from locus to gene identification. Since gene identification is particularly important (and challenging) in models of psychiatric disease where etiologic understanding is still limited and access to the relevant tissues or cell type difficult, the efficacy of the approach is tested on animal models of anxiety. Our approach consists of three steps: first, ensure that association evidence supporting each locus is robust; second, identify at each locus all candidate genes; third, make knockouts of those genes on an inbred strain and test their candidacy using a quantitative trait locus gene-knockout interaction test. Using a discovery set of 62 loci that contribute to variation in anxiety in mice, we aim to identify 24 loci with two or fewer candidate genes, and to confirm the identity of genes involved in anxiety at these loci. Until recently the key experiment that makes gene identification possible, the interaction test, could not easily be implemented because of the difficulty of obtaining a knockout and wildtype on the same genetic background. The advent of the new genomic engineering technology, CRISPR/Cas9, has overcome that obstacle. We will take advantage of this advance to make gene identification at complex trait loci a routine task. Our findings will transform complex trait genetics in rodents, and, by identifying up to 24 genes involved in anxiety, will make a major inroad into understanding the biological basis of a common disease, with consequent implications for developing new therapies.
Many thousands of genetic loci contributing to variation in bio-medically important phenotypes, including disease models, have been identified in rodents. Turning these discoveries into mechanistic insights, a necessary first step for understanding the pathophysiology of the disease models, and ultimately leading to the development of new therapies, requires finding the genes involved at complex trait loci. This application will develop a method that makes gene identification at complex trait loci in rodents simple and fast, and will do so by taking the example of mouse models of anxiety, a common and debilitating psychiatric illness whose origins are poorly understood and for which we have relatively ineffective treatment.