Matukumalli Lakshmi K, Lawley Cynthia T, Schnabel Robert D, Taylor Jeremy F, Allan Mark F, Heaton Michael P, O'Connell Jeff, Moore Stephen S, Smith Timothy P L, Sonstegard Tad S, Van Tassell Curtis P
Department of Bioinformatics and Computational Biology, George Mason University, Manassas, Virginia, United States of America.
PLoS One. 2009;4(4):e5350. doi: 10.1371/journal.pone.0005350. Epub 2009 Apr 24.
The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb. The assay was tested on a panel of 576 animals from 21 cattle breeds and six outgroup species and revealed that from 39,765 to 46,492 SNP are polymorphic within individual breeds (average minor allele frequency (MAF) ranging from 0.24 to 0.27). The assay also identified 79 putative copy number variants in cattle. Utility for GWA was demonstrated by localizing known variation for coat color and the presence/absence of horns to their correct genomic locations. The combination of SNP selection and the novel spacing algorithm allows an efficient approach for the development of high-density genotyping platforms in species having full or even moderate quality draft sequence. Aspects of the approach can be exploited in species which lack an available genome sequence. The BovineSNP50 assay described here is commercially available from Illumina and provides a robust platform for mapping disease genes and QTL in cattle.
全基因组关联(GWA)研究在检测影响人类复杂性状的序列变异方面取得的成功,激发了人们对使用大规模高密度单核苷酸多态性(SNP)基因分型来鉴定数量性状位点(QTL)以及在模式生物和农业物种中进行标记辅助选择的兴趣。本文描述了一种经济高效的方法,用于开发一种定制基因分型检测方法,该方法可检测54,001个SNP位点,以支持牛的GWA应用。一种用于实现压缩标记间间隔分布的新算法被证明非常成功,其间隔中位数为37 kb,最大预测间隔<350 kb。该检测方法在来自21个牛品种和6个外群物种的576只动物组成的群体上进行了测试,结果显示每个品种内有39,765至46,492个SNP具有多态性(平均次要等位基因频率(MAF)在0.24至0.27之间)。该检测方法还在牛中鉴定出79个推定的拷贝数变异。通过将已知的毛色变异和有无角的变异定位到其正确的基因组位置,证明了该检测方法在GWA中的实用性。SNP选择和新的间隔算法相结合,为在具有完整甚至中等质量草图序列的物种中开发高密度基因分型平台提供了一种有效的方法。该方法的某些方面可用于缺乏可用基因组序列的物种。本文所述的牛SNP50检测方法可从Illumina公司商业获得,并为牛的疾病基因和QTL定位提供了一个强大的平台。