Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species. The Challenge of Complex Disease Complex diseases present compelling biomedical challenges that can be studied using human and nonhuman animal genetics. Although advances in human genetics have identified loci for many heritable complex diseases [1-8], there are several well-known limitations of genomewide association studies (GWASs). (i) For many human disease loci, the biological mechanism of action is unknown. (ii) When little is known about a locus, the path from genetic association to clinically actionable targets is unclear. (iii) Disease process or developmental trajectory is not always obvious from a causal genetic variant. (iv) GWAS results may not generalize across human subpopulations. (v) Medical records and participant phenotyping is often incomplete, imprecise, and retrospective, whereas model organism phenotyping can include in-depth, prospective, and standardized measures. (vi) Sample size requirements are formidable in human GWASs. (vii) Power is insufficient to study interacting genetic loci. (viii) Studies of genetic interaction with development, environment, and sex are largely intractable. Further, heterogeneous diseases like psychiatric disorders manifest with overlapping symptoms, intertwined disease trajectories [9], and complex genetic regulation [9,10]. In summary, the SNP-to-disease association model underlying GWASs cannot readily capture complex disease biology without further biological context. These challenges are often tractable with discovery genetics in model organisms.