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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Tag SNP selection for candidate gene association studies using HapMap and gene resequencing data.

Zongli Xu1, Norman L Kaplan, Jack A Taylor

  • 1Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.

European Journal of Human Genetics : EJHG
|June 15, 2007
PubMed
Summary

HapMap data offers limited coverage for selecting tag SNPs in candidate genes across diverse populations. Supplementing with resequencing data and using ethnic-specific information improves SNP selection efficiency for genetic studies.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Population Genetics

Background:

  • The HapMap project provides extensive single nucleotide polymorphism (SNP) data for linkage disequilibrium (LD) analysis.
  • The Environmental Genome Project (EGP) has resequenced over 500 genes, offering a valuable resource for SNP ascertainment.
  • Evaluating HapMap's utility for tag SNP selection in candidate genes requires comparison with comprehensive gene resequencing data.

Purpose of the Study:

  • To assess the effectiveness of HapMap data for tag SNP selection in candidate genes across different ethnic groups.
  • To quantify the proportion of common SNPs (MAF>or=0.05) adequately tagged (rho2>or=0.8) by HapMap SNPs within EGP genes.
  • To explore strategies for improving tag SNP selection, including incorporating resequencing data and utilizing ethnic-specific information.

Main Methods:

  • Utilized HapMap data to select tag SNPs for 127 EGP Panel 2 genes with available ethnic information.
  • Calculated gene-tagging proportions for African, Asian, and European populations.
  • Estimated the LD of nonsynonymous SNPs (nsSNPs) with HapMap SNPs.
  • Developed and implemented a generalized greedy algorithm (mPopTag) for multi-population tag SNP selection.

Main Results:

  • Median gene-tagging proportions for HapMap SNPs were 50% (African), 80% (Asian), and 74% (European).
  • Only approximately 30% of EGP nonsynonymous SNPs were in high LD with any HapMap SNP.
  • Tagging proportions improved significantly by adding tag SNPs selected from resequencing data.
  • Ethnic-specific data provided more efficient gene-tagging than ethnic-mixed data.

Conclusions:

  • HapMap data alone may provide insufficient coverage for tag SNP selection in candidate gene studies, particularly in African populations.
  • Integrating resequencing data and employing ethnic-specific strategies are crucial for optimizing tag SNP selection.
  • The mPopTag software offers a valuable tool for multi-population tag SNP selection, enhancing the efficiency of genetic association studies.