A pooled-sample approach to the construction of high-resolution genetic maps is described. The strategy depends on the existence of an easily selectable target locus and the ability to produce large segregating populations. If these requirements are met, the pooled-sample mapping approach allows tightly linked markers (e.g., restriction fragment length polymorphisms) to be mapped relative to the target with a great economy of effort. The recombination fractions among loci can be estimated by the maximum likelihood method and a simple approximate estimator is derived. The order of loci is deduced using a Bayesian statistical framework to yield posterior probabilities for all possible orderings of a marker set. Optimal pooling strategies and the effects of misclassification of selected individuals are discussed and studied by computer simulation. The feasibility of this method is demonstrated by the high-resolution mapping of a region on chromosome 5 of tomato that contains a gene regulating fruit ripening.