DNA POOLING METHODS FOR QUANTITATIVE TRAITS USING UNRELATED POPULATIONS OR SIB PAIRS

摘要

Identifying the genetic determinants for disease and disease prediposition remains one of the outstanding goals of the human genome project. When large patient populations are available, genetic approaches using single nucleotide polymorphism markers have the potential to identify relevant genes directly. While indivieual genotyping is the most powerful method for establishing association, determining allele frequencies in DNA pooled on the basis of phenotypic value can also reveal association at much-reduced cost. Here we analyze pooling methods to establish association between a genetic polymorphism and a quantitative phenotype. Exact results are provided for the statistical power for a number of pooling designs where the phenotype is described by a variance components model and the fraction of the population pooled is optimized to minimize the population requirements. For low to moderate sibling phenotypic correlation, unrelated population requirements. For low to moderate sibling phenotypic correlation, unrelated populations are more powerful than sib pair populations with an equal number of individuals, for sibling phenotypic correlations above 75 %, however, designs selecting the sib pairs with the greatest phenotype difference become more powerful. For sibling phenotype correlations below 75 %, pooling extreme unrelated individuals is the most powerful design for sib pair populations. The optimal pooling fractions for each design are constant over a wide range of parameters. These results for quantitative phenotypes differ from those reported for qualitative phenotypes, for which unrelated populations are more powerful than sib pairs and concordant designs are more powerful than discordant, and have immediate relevance to ongoing association studies and anticipated whole-genome scans.