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A 3.9-centimorgan-resolution human single-nucleotide polymorphism linkage map and screening set.

Tara C Matise1, Ravi Sachidanandam, Andrew G Clark

  • 1Department of Genetics, Rutgers University, Piscataway, NJ, 08840, USA. matise@biology.rutgers.edu

American Journal of Human Genetics
|July 5, 2003
PubMed
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This summary is machine-generated.

This study introduces a novel single-nucleotide polymorphism (SNP) screening set and linkage map, crucial for efficient genomewide association studies. This resource aids in rapidly scanning genomes for disease genes, offering improved informativeness over existing methods.

Area of Science:

  • Genetics
  • Genomics
  • Bioinformatics

Background:

  • High-throughput single-nucleotide polymorphism (SNP) genotyping technologies have advanced, making them suitable for genomewide linkage analysis.
  • A comprehensive SNP screening set and linkage map were previously lacking for efficient disease gene discovery.

Purpose of the Study:

  • To develop and characterize a robust SNP screening set and linkage map for genomewide association studies.
  • To provide a valuable resource for accelerating the identification of disease-associated genes.

Main Methods:

  • Evaluation of 6,297 SNPs for assay robustness, allele frequencies, and cluster informativeness in diverse populations.
  • Genotyping of 2,988 SNPs in 56 Centre d'Etude du Polymorphisme Humain pedigrees for linkage map construction.

Related Experiment Videos

  • Extensive genotyping error analysis and comparison with existing physical and linkage maps.

    • Main Results:

    • Development of an SNP linkage map with an average resolution of 3.9 cM, featuring single or tightly linked SNPs.
    • The generated map demonstrates favorable marker order compared to other established maps.
    • The SNP screening set proved more informative than the commonly used Marshfield Clinic microsatellite set.

    Conclusions:

    • The developed SNP screening set and linkage map represent a significant advancement for genomewide linkage analysis.
    • This resource facilitates faster and more efficient genome scanning for identifying disease genes.
    • The map provides insights into recombination rates across human chromosomes.