Animal models, primarily mice, have been important tools in elucidating the genetic architecture of polygenic traits such as obesity, and the mouse 'obesity map' is now well populated with genes influencing body weight, fatness and components of energy balance [10
]. However, robust identification of these quantitative trait loci (QTL) at the gene or nucleotide level has proved frustratingly elusive. Given the recent rise of GWA studies and their success, it might seem that the role of mouse models for complex trait analysis requires re-evaluation [10
]. In fact, the success of GWA studies is likely to increase the importance of relevant animal models for several reasons. First, mouse models will now be important in pursuing the mechanisms of genes discovered in association studies [12
]. Second, many important obesity-related phenotypes (for example, those requiring measures of energy intake and energy expenditure) are challenging for GWA studies because of the high cost of obtaining accurate measurements, and require informative animal models for initial evaluation of genetic predisposition (see, for example, [13
Useful animal models extend beyond the mouse, as illustrated by De Luca and colleagues in their paper in BMC Genetics
]. They identified LanA5
as a candidate gene for triacylglycerol storage in Drosophila melanogaster
, which led to their subsequent finding of an association of SNPs in the closely related human gene LAMA5
with body composition. Mechanisms for regulating energy balance are a relatively common thermodynamic inheritance of all organisms, and thus studies using Drosophila
, Caenorhabditis elegans
and zebrafish are showing that genetically tractable lower organisms can contribute to our understanding of obesity [14
]. These non-mammalian animal models have several advantages over mice, including shorter generation times, ease of breeding very large populations, powerful tools for genetic mapping, and high-throughput methods for creation and screening of mutants and phenocopies and conducting quantitative complementation testing. The findings of De Luca et al
. confirm that D. melanogaster
is a good model to identify genes that have evolutionarily conserved effects on body composition and that may represent obesity-predisposition genes in humans. Nevertheless, the discovery of association in a relatively small study in a limited human population will require replication in other human cohorts.
The third, and perhaps the most important, reason for using animal models is the difficulty in implementing robustly powerful designs for human association studies that could test anything beyond relatively simple models of obesity. Appropriately designed animal models can uncover networks of functionally important relationships within and among diverse sets of biological and physiological phenotypes that can be altered by relevant external factors (for example, diet and exercise), and thus incorporate multiple genetic, environmental and developmental variables into comprehensive models describing susceptibility to obesity and its progression. Such a model is represented by a new paradigm for complex-trait analysis, the 'collaborative cross' (CC) [15
The CC is a large panel of recombinant inbred mouse lines derived from a genetically diverse set of eight founder strains (Figure ). It has a distribution of allele frequencies resembling that seen in human populations, in which many variants are found at low frequencies and only a minority of variants are common [16
]. The eight parental inbred lines contributing to the CC are estimated to capture more than 90% of the known variation present in all mouse strains. Existing data on the founder strains and on many of the early generations in development of the CC demonstrate broad variability in many obesity phenotypes (F Pardo-Manuel de Villena, DW Threadgill, D Pomp, unpublished data), indicating that the CC will represent an excellent resource for identifying genes controlling predisposition to many traits relevant to obesity, and for understanding the pathways, networks and systems that control obesity.
Figure 1 The Collaborative Cross for complex trait analysis. Starting with eight inbred mouse strains capturing 90% of all genetic variation in mice, a funnel breeding scheme is used to randomize variation. A single breeding funnel results in one immortal CC recombinant (more ...)
Not only are new models of obesity being developed, but the approaches used to evaluate such models are rapidly evolving. For example, the blending of technologies to study genes, genomes, transcriptomes, proteomes and metabolomes in order to identify the molecular basis for common diseases such as obesity is on the increase [17
]. This 'systems biology' approach incorporates the synergistic connections between 'omic' and environmental influences into a comprehensive framework.