In the past decade, the ability to generate whole-genome sequences has provided geneticists with a view of the astonishing breadth of genetic variation. This, in theory, means we should be able to identify the specific differences in DNA sequence that lead to an inherited phenotype, including disease states. But this wealth of new information has revealed perhaps the most fundamental challenge for geneticists since Mendel.While we understand that phenotypes are influenced by genetic variation, we do not yet know how to interpret individual genome sequences, and, therefore, we cannot predict which genetic variants are linked to which phenotypes. Indeed, the term “missing heritability” was coined to highlight the fact that in natural populations the genes or genetic elements associated with complex traits explain only a small proportion of the phenotypic variation in these traits. In starkcontrast, controlled crossesofmodelorganismshave generated a wealth of information about the genetic basis of phenotypes. From broad associations of genomic regions with traits, to individual polymorphisms that act by well understood mechanisms, geneticists have been remarkably successful in revealing the impact of genetic variation on phenotype. Applications as diverse as targeted drug therapy and dramatic improvements in agricultural output have been enabled by our understanding of genetics. But it remains a significant challenge to transfer this understanding to natural populations. To bridge the gap between natural populations and experimental systems, experimental systems need to incorporatemore of the complexity of natural populations. This has given rise to aburstofcreativity inthedesignofgeneticreferencepopulations. The basic idea is simple: combine the strength of the experimental system,where thegenetic compositioncanbereplicated,with thegeneticdiversityof the targetpopulation.Rather thanchoose two inbred lines or two phenotypically divergent individuals as founders of a genetic reference panel (recombinant inbreds), choose eight, or 25.Usingmultiple lines as founders of a set of inbred lineswhose haplotypes can be replicated has been referred to as Interconnected populationsmulti-parent, advanced-generation inter-cross design, Complex Cross, and multi-parental RIL. We are choosing to refer to this broad set of genetic reference panels as multi-parent populations (MPP). Fifteen years ago, themouse genetics community embraced the challenge of creating strains that would represent the diversityofnatural variation inmice, thereby improving theutility of the organism for exploring complex human disease. Eight foundermouse strainswere selected, andoffspringpopulations with all eight haplotypes were developed in a funnel mating scheme (Figure 1, Collaborative Cross Consortium 2012). The first set of papers describing these strains was published in GENETICS and G3 in 2012 (http://www.g3journal.org/ content/mpp_mouse#cc). Systematic monitoring of progress with the mouse collaborative cross has provided a window into the impact of drift on the genomes (Srivastava et al. 2017), a startling insight into the genetic basis of male sterility (Odet et al. 2015; Shorter et al. 2017), the impact of structural variation (Morgan et al. 2017), and a new method for estimating haplotypes and preserving uncertainty (Oreper et al. 2017). The resources developed for mouse enable detection of many types of loci, from those associatedwith SARS (Gralinski et al. 2017) andWest Nile (Green et al. 2017) virus infections to those associated with fertility (Shorter et al. 2017) allergens Kelada (2016).Morgan et al. (2016) andDumont et al. (2017) also provide insights into genome structure. This large effort in mouse is matched by ambitious projects on a plethora of organisms. MPPs have been created in plants [Arabidopsis (Kover et al. 2009), Maize (Yu et al. 2008), wheat (Mackay et al. 2014), sunflower (Bowers et al. 2012), and other crops (Brenton et al. 2016; Nice et al. 2016)], in animals [Drosophila (Mackay et al. 2012; King et al. 2012)], and in yeast (Cubillos et al. 2013). In 2014, we highlighted the diversity of MPPs in GENETICS and G3 Copyright © 2017 de Koning and McIntyre doi: https://doi.org/10.1534/genetics.117.203265 This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.