Macgregor Stuart, Zhao Zhen Zhen, Henders Anjali, Nicholas Martin G, Montgomery Grant W, Visscher Peter M
Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia.
Nucleic Acids Res. 2008 Apr;36(6):e35. doi: 10.1093/nar/gkm1060. Epub 2008 Feb 14.
Genome-wide association (GWA) studies to map genes for complex traits are powerful yet costly. DNA-pooling strategies have the potential to dramatically reduce the cost of GWA studies. Pooling using Affymetrix arrays has been proposed and used but the efficiency of these arrays has not been quantified. We compared and contrasted Affymetrix Genechip HindIII and Illumina HumanHap300 arrays on the same DNA pools and showed that the HumanHap300 arrays are substantially more efficient. In terms of effective sample size, HumanHap300-based pooling extracts >80% of the information available with individual genotyping (IG). In contrast, Genechip HindIII-based pooling only extracts approximately 30% of the available information. With HumanHap300 arrays concordance with IG data is excellent. Guidance is given on best study design and it is shown that even after taking into account pooling error, one stage scans can be performed for >100-fold reduced cost compared with IG. With appropriately designed two stage studies, IG can provide confirmation of pooling results whilst still providing approximately 20-fold reduction in total cost compared with IG-based alternatives. The large cost savings with Illumina HumanHap300-based pooling imply that future studies need only be limited by the availability of samples and not cost.
全基因组关联(GWA)研究用于绘制复杂性状的基因图谱,虽功能强大但成本高昂。DNA池策略有潜力大幅降低GWA研究的成本。有人提出并使用了基于Affymetrix芯片的池化方法,但这些芯片的效率尚未得到量化。我们在相同的DNA池上对Affymetrix Genechip HindIII芯片和Illumina HumanHap300芯片进行了比较,结果表明HumanHap300芯片的效率要高得多。就有效样本量而言,基于HumanHap300芯片的池化提取了个体基因分型(IG)可获得信息的80%以上。相比之下,基于Genechip HindIII芯片的池化仅提取了约30%的可用信息。使用HumanHap300芯片时,与IG数据的一致性非常好。文中给出了最佳研究设计的指导意见,结果表明,即使考虑到池化误差,与IG相比,单阶段扫描的成本可降低100倍以上。通过适当设计的两阶段研究,IG可以对池化结果进行确认,同时与基于IG的替代方案相比,总成本仍可降低约20倍。基于Illumina HumanHap300芯片的池化能大幅节省成本,这意味着未来的研究仅受样本可用性的限制,而不受成本的限制。