• confidence intervals;
  • genetic maps;
  • map distances;
  • recombination fractions;
  • SNP markers;
  • microsatellite markers


Genetic maps play an important role in gene mapping. Inaccurate genetic maps can hinder gene mapping by biasing lod scores and reducing the power to map a trait to a particular region. Although sequence-based physical maps can provide a unique order for markers, they do not provide information on genetic map distances. By simulation studies, I investigated how many meioses are necessary to accurately estimate genetic map distances for maps constructed from microsatellite and single-nucleotide polymorphism (SNP) markers for various intermarker distances and marker heterozygosity. To evaluate the accuracy of the generated genetic maps, the length of the 95% confidence interval for intermarker genetic distances was examined. In addition, the power to separate two adjacent markers by a nonzero map distance was investigated. The number of meioses necessary to accurately estimate map distances depends greatly not only on intermarker distances but also on marker heterozygosity. For example, for a genetic map with intermarker distances of 0.5 cM generated with 1,000 meioses, when marker heterozygosity was high (0.90), for 96% of the markers there was a nonzero map distance between adjacent markers. However, when marker heterozygosity was low (0.32), only 48% of the markers mapped to a unique position. For identical numbers of meioses and intermarker distances, genetic maps constructed from microsatellite markers will be more precise than maps assembled from SNP markers, due to the higher levels of heterozygosity for microsatellite markers. Genet Epidemiol 24:243–252, 2003. © 2003 Wiley-Liss, Inc.