Dow AgroSciences, 9330 Zionsville Rd, Indianapolis, IN 46268-1054, USA.
Theor Appl Genet. 2010 Aug;121(3):577-88. doi: 10.1007/s00122-010-1331-8. Epub 2010 Apr 18.
The duplicated and the highly repetitive nature of the maize genome has historically impeded the development of true single nucleotide polymorphism (SNP) markers in this crop. Recent advances in genome complexity reduction methods coupled with sequencing-by-synthesis technologies permit the implementation of efficient genome-wide SNP discovery in maize. In this study, we have applied Complexity Reduction of Polymorphic Sequences technology (Keygene N.V., Wageningen, The Netherlands) for the identification of informative SNPs between two genetically distinct maize inbred lines of North and South American origins. This approach resulted in the discovery of 1,123 putative SNPs representing low and single copy loci. In silico and experimental (Illumina GoldenGate (GG) assay) validation of putative SNPs resulted in mapping of 604 markers, out of which 188 SNPs represented 43 haplotype blocks distributed across all ten chromosomes. We have determined and clearly stated a specific combination of stringent criteria (>0.3 minor allele frequency, >0.8 GenTrainScore and >0.5 Chi_test100 score) necessary for the identification of highly polymorphic and genetically stable SNP markers. Due to these criteria, we identified a subset of 120 high-quality SNP markers to leverage in GG assay-based marker-assisted selection projects. A total of 32 high-quality SNPs represented 21 haplotypes out of 43 identified in this study. The information on the selection criteria of highly polymorphic SNPs in a complex genome such as maize and the public availability of these SNP assays will be of great value for the maize molecular genetics and breeding community.
玉米基因组的重复和高度重复性质在历史上阻碍了真正的单核苷酸多态性（SNP）标记在该作物中的发展。最近基因组复杂性降低方法的进步以及测序合成技术的结合，使得在玉米中实现高效的全基因组 SNP 发现成为可能。在这项研究中，我们应用了复杂序列减少技术（Keygene N.V.，瓦赫宁根，荷兰）来鉴定来自北美和南美两个遗传上不同的玉米自交系之间的信息性 SNP。这种方法导致发现了 1123 个代表低拷贝和单拷贝基因座的假定 SNP。对假定 SNP 的计算机模拟和实验（Illumina GoldenGate (GG) 分析）验证导致了 604 个标记的映射，其中 188 个 SNP 代表了分布在所有十个染色体上的 43 个单倍型块。我们已经确定并明确说明了一组严格的标准（>0.3 的次要等位基因频率、>0.8 的 GenTrainScore 和>0.5 的 Chi_test100 得分），这些标准对于鉴定高度多态和遗传稳定的 SNP 标记是必要的。由于这些标准，我们确定了一个子集的 120 个高质量 SNP 标记，以利用基于 GG 分析的标记辅助选择项目。在本研究中鉴定的 43 个单倍型中，共有 32 个高质量 SNP 代表了 21 个单倍型。关于在复杂基因组（如玉米）中选择高度多态性 SNP 的标准的信息以及这些 SNP 分析的公开可用性，对于玉米分子遗传学和育种社区将具有巨大的价值。
