difficult to distinguish causal mutations from neutral variants. Fine mapping of variants can be attempted by functional profiling of candidates within each quantitative trait locus. However, without cellular and molecular studies it remains extremely difficult to determine which variants are responsible for phenotypic variability. The identification of causal variants in model organisms requires extensive outbreeding or introduction of individual mutations, both of which are lengthy and costly approaches. She and Jarosz tackled this problem using computational modelling to define the requirements for a mating scheme in yeast that enables single-nucleotide resolution mapping of natural genetic variation. The model takes into account the number of generations of inbreeding, the number of individuals that need to be genotyped and the mean distance between polymorphisms. This approach yielded a statistically optimal crossing scheme for precision mapping. By creating a dense recombination map, the authors were able to statistically differentiate individual causal variants from multiple, highly linked passenger mutations in close proximity.