A Resource for the Genetic Dissection of Complex Traits

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PROJECT SUMMARY A large, diverse set of common human diseases, and most of the biomedically-relevant traits that model organism biologists routinely target, are complex and polygenic. Population variation in these traits has a sizeable genetic component, and dissecting this variation can yield improved diagnostics and therapeutics, and enable detailed descriptions of the molecular and cellular processes underlying disease and trait variation. Genomewide association studies (GWAS) are largely responsible for dramatic progress in the analysis of human complex traits in recent years. GWAS have linked many genes to variation in human health, and imply a significant fraction of trait variation is controlled by thousands of tiny-effect, primarily regulatory sites spread along the genome. Despite this critical insight, there remain many gaps in our understanding of the nature of causative loci. One notable caveat of the GWAS approach is its inherent bias towards intermediate- frequency alleles; GWAS are ill-suited to uncovering rare alleles of large effect and genes harboring several individually-rare mutations, events that mutation-selection balance models predict contribute to trait variation. The dissection of complex traits in model organisms offers great experimental flexibility, and the opportunity to deploy methods synergistic with the dominant GWAS paradigm, yielding a more complete picture of the genetic basis of trait variation. With this in mind we established the DSPR (Drosophila Synthetic Population Resource) as a shareable toolkit for complex trait analysis in flies. The set of 1600 DSPR strains were derived from 15 highly-characterized founder genotypes, and represent the most extensive multiparental population (MPP) available in animals. The DSPR is used by many research groups, has enabled the identification of thousands of QTL, and has associated rare alleles with trait variation. The DSPR complements GWAS approaches for uncovering the full spectrum of allelic variation contributing to complex traits. In Aim 1 we will validate and refine the genotypes of all DSPR strains, strengthening the living resource we will continue to share with the Drosophila community, and enhance the usability of the collection by integrating analytical routines into the powerful R/qtl2 software platform. In Aim 2 we will extend the DSPR, and enable extreme QTL (or X-QTL) mapping. For many traits, an efficient and user-friendly strategy to identify QTL is to compare allele frequencies in phenotypically-extreme recombinant populations to those in control cohorts. We will derive such mixed DSPR populations, experimentally refine our approach, and distribute populations and software to facilitate novel, investigator-driven research. In Aim 3 we will broaden the utility of the DSPR to explore the nature of expression regulation. Using a host-pathogen model, we will exploit the rapid regulatory change that occurs during the immune response to develop dynamic eQTL mapping methods, finding loci that contribute to variation in the trajectory of the regulatory reaction. These general resources will allow researchers employing any MPP to move beyond static pictures of gene expression in populations.