A novel measure of genetic distance for highly polymorphic tandem repeat loci

Mark D. Shriver, Li Jin, Eric Boerwinkle, Ranjan Deka, Robert E. Ferrell, Ranajit Chakraborty

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261 Scopus citations


Genetic distance measures are indicators of relatedness among populations or species and are useful for reconstructing the historic and phylogenetic relationships among such groups. Classical measures of genetic distance were developed to analyze biochemical and serological polymorphisms, systems which generally show limited variability. However, these traditional measures of genetic distance are inadequate for the analysis of certain classes of variable number tandem repeat (VNTR) loci, which have a larger number of alleles and higher levels of heterozygosity than traditional genetic markers. At the higher levels of heterozygosity observed at these loci, the standard measures of genetic distance are nonlinear and do not account for the mutational mechanisms of hypervariable loci. We have developed a measure of genetic distance, D(SW), which is appropriate for the analysis of highly polymorphic DNA loci. Using computer simulations of diverging populations, we show that D(SW) conforms to linearity and that the variance is similar in magnitude to traditional measures of genetic distance. Comparisons of phylogenetic trees derived from the simulated divergence of human racial groups demonstrate that the branch lengths of trees prepared using D(SW) are more similar to the model tree than those generated using other measures. Finally, we demonstrate the applicability of D(SW) to evolutionary analysis by reconstructing the relationships among eight human populations using 14 microsatellite and STR loci. The phylogenetic trees generated using D(SW) are different from trees constructed with traditional measures and better reflect the well-documented ancient divergence of African and non-African populations.

Original languageEnglish (US)
Pages (from-to)914-920
Number of pages7
JournalMolecular biology and evolution
Issue number5
StatePublished - Sep 1995

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics


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