Optimal selection strategies for QTL mapping using pooled DNA samples.

摘要: The cost of large-scale association studies may be reduced substantially by analysis pooled DNA from multiple individuals. Here we examine the optimal symmetric and asymmetric designs for pooling experiments quantitative traits under a range assumptions about underlying genetic model sources experimental errors in allele frequency estimation. results indicate that, absence common alleles with additive effects, scheme comparing top 27% bottom trait distribution is optimal, extracting 80% total information available. A design not rare or recessive alleles, which require (or other) strategies. Allele measurement reduce fraction as well overall efficiency design. In contrast, random variation amount contributed individuals to pool reduces only Our emphasize importance minimising suggest around 20%.