Norton Nadine, Williams Nigel M, Williams Hywel J, Spurlock Gillian, Kirov George, Morris Derek W, Hoogendoorn Bastiaan, Owen Michael J, O'Donovan Michael C
Department of Psychological Medicine, University of Wales College of Medicine, Heath Park, Cardiff CF14 4XN, UK.
Hum Genet. 2002 May;110(5):471-8. doi: 10.1007/s00439-002-0706-6. Epub 2002 Mar 23.
Detecting alleles that confer small increments in susceptibility to disease will require large-scale allelic association studies of single-nucleotide polymorphisms (SNPs) in candidate, or positional candidate, genes. However, current genotyping technologies are one to two orders of magnitude too expensive to permit the analysis of thousands of SNPs in large samples. We have developed and thoroughly validated a highly accurate protocol for SNP allele frequency estimation in DNA pools based upon the SNaPshot (Applied Biosystems) chemistry adaptation of primer extension. Using this assay, we were able to estimate the difference in allele frequencies between pooled cases and controls (Delta) with a mean error of 0.01. Moreover, when we genotyped seven different SNPs in a single multiplex reaction, the results were similar, with a mean error for Delta of 0.008. The assay performed well for alleles of low frequency alleles (f approximately 0.05) and was accurate even with relatively poor quality DNA template extracted from mouthwashes. Our assay conditions are generalisable, universal, robust and, therefore, for the first time, permit high-throughput association analysis at a realistic cost.
检测那些使疾病易感性有小幅度增加的等位基因,将需要对候选基因或定位候选基因中的单核苷酸多态性(SNP)进行大规模的等位基因关联研究。然而,目前的基因分型技术昂贵了一到两个数量级,以至于无法在大样本中对数千个SNP进行分析。我们基于引物延伸的SNaPshot(应用生物系统公司)化学方法,开发并全面验证了一种用于DNA池中等位基因频率估计的高度准确的方案。使用该检测方法,我们能够估计病例组和对照组混合样本之间的等位基因频率差异(Δ),平均误差为0.01。此外,当我们在单个多重反应中对7个不同的SNP进行基因分型时,结果相似,Δ的平均误差为0.008。该检测方法对于低频等位基因(f约为0.05)表现良好,即使从漱口液中提取的DNA模板质量相对较差时也很准确。我们的检测条件具有通用性、普遍性和稳健性,因此首次能够以实际可行的成本进行高通量关联分析。