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High-throughput screening for evidence of association by using mass spectrometry genotyping on DNA pools
Author(s) -
Karen L. Mohlke,
Michael R. Erdos,
Laura J. Scott,
Tasha E. Fingerlin,
Anne Jackson,
Kaisa Silander,
Pablo E. Hollstein,
Michael Boehnke,
Francis S. Collins
Publication year - 2002
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.262661399
Subject(s) - minor allele frequency , single nucleotide polymorphism , genotyping , allele frequency , genetics , biology , allele , quantitative trait locus , population , genotype , medicine , gene , environmental health
To facilitate positional cloning of complex trait susceptibility loci, we are investigating methods to reduce the effort required to identify trait-associated alleles. We examined primer extension analysis by matrix-assisted laser desorptionionization time-of-flight mass spectrometry to screen single-nucleotide polymorphisms (SNPs) for association by using DNA pools. We tested whether this method can accurately estimate allele frequency differences between pools while maintaining the high-throughput nature of assay design, sample handling, and scoring. We follow up interesting allele frequency differences in pools by genotyping individuals. We tested DNA pools of 182, 228, and 499 individuals using 16 SNPs with minor allele frequencies 0.026-0.486 and allele frequency differences 0.001-0.108 that we had genotyped previously on individuals and 381 SNPs that we had not. Precision, as measured by the average standard deviation among 16 semidependent replicates, was 0.021 +/- 0.011 for the 16 SNPs and 0.018 +/- 0.008 for the 291381 SNPs used in further analysis. For the 16 SNPs, the average absolute error in predicting allele frequency differences between pools was 0.009; the largest errors were 0.031, 0.028, and 0.027. We determined that compensating for unequal peak heights in heterozygotes improved precision of allele frequency estimates but had only a very minor effect on accuracy of allele frequency differences between pools. Based on these data and assuming pools of 500 individuals, we conclude that at significance level 0.05 we would have 95% (82%) power to detect population allele frequency differences of 0.07 for control allele frequencies of 0.10 (0.50).

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