Because of their abundance, and because many effectively dichotomize human populations, single nucleotide polymorphisms (SNPs) are attractive tools for studying gene-phenotype interactions, for instance in commonly occurring diseases. Although our understanding of linkage disequilibrium is still incomplete (Abecasis et al., 2001), it is generally assumed that a SNP can serve as a marker for the surrounding DNA region in outbred populations. However, the size of the regions may well vary considerably between SNPs and populations and discontinuities may occur. To explore and utilize SNPs in such studies it is necessary to develop quick, reliable, high-throughput typing methods. One approach is the development of solid-state arrays (Fan et al., 2000), which can be used to type thousands of SNPs in a person's DNA. The approach allows for the coverage of the complete genome with an average distance between SNPs of a few 100 kb. However, the statistical problems are large, and the issue of mass significance will be difficult to deal with. We have taken a different approach. On the assumption that the same genes influence rarely occurring familial diseases and the commonly occurring "sporadic" diseases we have chosen areas around already defined genes and studied those with LightCycler technology in relation to disease occurrence in outbred populations (Dybdahl et al., 1999; Vogel et al., 2001). The technique typically allows for the typing of one SNP in each assay, but has a fast turn-around time. We have chosen a SNP, designed primers and probes for it, had them synthesized, optimized PCR and temperature profiling for the reaction, typed around 200 persons for the SNP, and analyzed the results in a matter of 3 weeks. The time can be further reduced, if fast access to synthesis of primers and probes is available. Thus, with this technique the choice of markers can be a dynamic process. In this paper we illustrate the use of LightCycler technology by presenting a single-step assay for a polymorphism in human ERCC1 exon 4.