A particular advantage of model systems such as yeast, C. elegans and Drosophila is the potential to examine arrays of genetic combinations to identify factors produced by the host or pathogen that act redundantly (host) or that genetically interact (host or pathogen). These types of studies are inherently number intensive (known as 'the n problem'), because many combinations must be analyzed in a comprehensive fashion. However, there are excellent examples in which combinatorial genetic analysis has been used to investigate cellular processes involved in other types of human disease. For example, the interacting components of the DNA mismatch repair machinery were first identified in yeast, and the same components were found to interact in humans in a dominant manner and to contribute to cancer (Kolodner, 1995) . Drosophila cells and intact fly mis-expression systems (e.g. combined RNAi expression) are also well suited for such analyses, which would be prohibitively expensive and labor intensive in vertebrate models. It is of course important to validate results obtained in single cells or invertebrate model systems in vertebrates, a process previously referred to as 'closing-the-loop' (Bier, 2005) . It is possible to envision a tiered system of analysis in which initial discoveries that are made using powerful model genetic systems, including yeast, worms and flies (in cells and in whole organisms), are then validated in vertebrate models, including zebrafish, mice and human cells, and finally are linked via human genetics to specific disease processes. For example, in a recent study of genes on human chromosome 21 causing congenital heart defects when overexpressed in individuals with Down syndrome, a combined genetic analysis in flies, mice and humans pointed to two interacting genes, DSCAM and COL6A2, as contributing to formation of atrial septal defects (Grossman et al., 2011) .