title: PeakSeeker: a program for interpreting genotypes of mononucleotide repeats.
abstract: BACKGROUND
  Mononucleotide repeat microsatellites are abundant, highly polymorphic DNA sequences, having the potential to serve as valuable genetic markers. Use of mononucleotide microsatellites has been limited by their tendency to produce "stutter", confounding signals from insertions and deletions within the mononucleotide tract that occur during PCR, which complicates interpretation of genotypes by masking the true position of alleles. Consequently, microsatellites with larger repeating subunits (dinucleotide and trinucleotide motifs) are used, which produce less stutter but are less genetically heterogeneous and less informative. A method to interpret the genotypes of mononucleotide repeats would permit the widespread use of those highly informative microsatellites in genetic research.
  
  
  RESULTS
  We have developed an approach to interpret genotypes of mononucleotide repeats using a software program, named PeakSeeker. PeakSeeker interprets experimental electropherograms as the most likely product of signals from individual alleles. Because mononucleotide tracts demonstrate locus-specific patterns of stutter peaks, this approach requires that the genotype pattern from a single allele is defined for each marker, which can be approximated by genotyping single DNA molecules or homozygotes. We have evaluated the program's ability to discriminate various types of homozygous and heterozygous mononucleotide loci using simulated and experimental data.
  
  
  CONCLUSIONS
  Mononucleotide tracts offer significant advantages over di- and tri-nucleotide microsatellite markers traditionally employed in genetic research. The PeakSeeker algorithm provides a high-throughput means to type mononucleotide tracts using conventional and widely implemented fragment length polymorphism genotyping. Furthermore, the PeakSeeker algorithm could potentially be adapted to improve, and perhaps to standardize, the analysis of conventional microsatellite genotypes.
authors.affiliation: Department of Genome Sciences, University of Washington School of Medicine, Seattle, USA. tex@u.washington.edu
authors.forename: James M
authors.initials: JM
authors.lastname: Thompson
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Salipante