Biomathematics and Statistics Scotland, Invergowrie, Dundee, UK,
Theor Appl Genet. 2014 Sep;127(9):1885-904. doi: 10.1007/s00122-014-2347-2. Epub 2014 Jul 1.
Dense linkage maps derived by analysing SNP dosage in autotetraploids provide detailed information about the location of, and genetic model at, quantitative trait loci. Recent developments in sequencing and genotyping technologies enable researchers to generate high-density single nucleotide polymorphism (SNP) genotype data for mapping studies. For polyploid species, the SNP genotypes are informative about allele dosage, and Hackett et al. (PLoS ONE 8:e63939, 2013) presented theory about how dosage information can be used in linkage map construction and quantitative trait locus (QTL) mapping for an F1 population in an autotetraploid species. Here, QTL mapping using dosage information is explored for simulated phenotypic traits of moderate heritability and possibly non-additive effects. Different mapping strategies are compared, looking at additive and more complicated models, and model fitting as a single step or by iteratively re-weighted modelling. We recommend fitting an additive model without iterative re-weighting, and then exploring non-additive models for the genotype means estimated at the most likely position. We apply this strategy to re-analyse traits of high heritability from a potato population of 190 F1 individuals: flower colour, maturity, height and resistance to late blight (Phytophthora infestans (Mont.) de Bary) and potato cyst nematode (Globodera pallida), using a map of 3839 SNPs. The approximate confidence intervals for QTL locations have been improved by the detailed linkage map, and more information about the genetic model at each QTL has been revealed. For several of the reported QTLs, candidate SNPs can be identified, and used to propose candidate trait genes. We conclude that the high marker density is informative about the genetic model at loci of large effects, but that larger populations are needed to detect smaller QTLs.
通过分析同源四倍体 SNP 剂量得出的高密度连锁图谱为数量性状基因座的位置和遗传模型提供了详细信息。测序和基因分型技术的最新进展使研究人员能够为图谱研究生成高密度单核苷酸多态性 (SNP) 基因型数据。对于多倍体物种，SNP 基因型提供了关于等位基因剂量的信息，Hackett 等人（PLoS ONE 8:e63939, 2013）提出了关于如何在同源四倍体物种的 F1 群体中使用剂量信息构建连锁图谱和进行数量性状基因座 (QTL) 作图的理论。在这里，探索了剂量信息在中度遗传力和可能非加性效应的模拟表型性状中的 QTL 作图。比较了不同的作图策略，研究了加性和更复杂的模型，以及作为单个步骤或通过迭代重新加权建模进行的模型拟合。我们建议拟合没有迭代重新加权的加性模型，然后探索最有可能位置估计的基因型均值的非加性模型。我们应用这种策略重新分析了来自 190 个 F1 个体的马铃薯群体的高遗传力性状：花色、成熟度、高度和对晚疫病（Phytophthora infestans (Mont.) de Bary）和马铃薯胞囊线虫（Globodera pallida）的抗性，使用了一个包含 3839 个 SNP 的图谱。详细的连锁图谱改善了 QTL 位置的近似置信区间，并揭示了每个 QTL 遗传模型的更多信息。对于报告的几个 QTL，可以鉴定候选 SNP，并用于提出候选性状基因。我们的结论是，高密度标记提供了关于大效应基因座遗传模型的信息，但需要更大的群体来检测较小的 QTL。
