Human Genetics

, Volume 125, Issue 3, pp 305–318 | Cite as

Identification of susceptibility genes for complex diseases using pooling-based genome-wide association scans

  • Yohan Bossé
  • François Bacot
  • Alexandre Montpetit
  • Johan Rung
  • Hui-Qi Qu
  • James C. Engert
  • Constantin Polychronakos
  • Thomas J. Hudson
  • Philippe Froguel
  • Robert Sladek
  • Martin Desrosiers
Original Investigation

Abstract

The success of genome-wide association studies (GWAS) to identify risk loci of complex diseases is now well-established. One persistent major hurdle is the cost of those studies, which make them beyond the reach of most research groups. Performing GWAS on pools of DNA samples may be an effective strategy to reduce the costs of these studies. In this study, we performed pooling-based GWAS with more than 550,000 SNPs in two case-control cohorts consisting of patients with Type II diabetes (T2DM) and with chronic rhinosinusitis (CRS). In the T2DM study, the results of the pooling experiment were compared to individual genotypes obtained from a previously published GWAS. TCF7L2 and HHEX SNPs associated with T2DM by the traditional GWAS were among the top ranked SNPs in the pooling experiment. This dataset was also used to refine the best strategy to correctly identify SNPs that will remain significant based on individual genotyping. In the CRS study, the top hits from the pooling-based GWAS located within ten kilobases of known genes were validated by individual genotyping of 1,536 SNPs. Forty-one percent (598 out of the 1,457 SNPs that passed quality control) were associated with CRS at a nominal P value of 0.05, confirming the potential of pooling-based GWAS to identify SNPs that differ in allele frequencies between two groups of subjects. Overall, our results demonstrate that a pooling experiment on high-density genotyping arrays can accurately determine the minor allelic frequency as compared to individual genotyping and produce a list of top ranked SNPs that captures genuine allelic differences between a group of cases and controls. The low cost associated with a pooling-based GWAS clearly justifies its use in screening for genetic determinants of complex diseases.

Supplementary material

439_2009_626_MOESM1_ESM.pdf (472 kb)
Supplementary material 1 (PDF 472 kb)

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Yohan Bossé
    • 1
    • 2
  • François Bacot
    • 3
  • Alexandre Montpetit
    • 3
  • Johan Rung
    • 3
  • Hui-Qi Qu
    • 4
  • James C. Engert
    • 5
    • 6
  • Constantin Polychronakos
    • 4
    • 5
    • 7
  • Thomas J. Hudson
    • 8
  • Philippe Froguel
    • 9
  • Robert Sladek
    • 3
    • 5
    • 6
  • Martin Desrosiers
    • 10
    • 11
  1. 1.Laval Hospital Research CenterLaval UniversityQuebecCanada
  2. 2.Laval University Hospital Research Center (CRCHUL)QuebecCanada
  3. 3.McGill University and Genome Quebec Innovation CenterMontrealCanada
  4. 4.Endocrine Genetics Lab, The McGill University Health CenterMontreal Children’s HospitalMontrealCanada
  5. 5.Department of Human Genetics, Faculty of MedicineMcGill UniversityMontrealCanada
  6. 6.Department of Medicine, Faculty of MedicineMcGill UniversityMontrealCanada
  7. 7.Department of Pediatrics, Faculty of MedicineMcGill UniversityMontrealCanada
  8. 8.The Ontario Institute for Cancer ResearchTorontoCanada
  9. 9.CNRS 8090-Institute of BiologyPasteur InstituteLilleFrance
  10. 10.Department of Otolaryngology-Head and Neck SurgeryMcGill UniversityMontrealCanada
  11. 11.Department of Otolaryngology-Head and Neck SurgeryMontreal UniversityMontrealCanada

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