Isobe Sachiko, Nakaya Akihiro, Tabata Satoshi
1 National Agricultural Research Center for Hokkaido Region, Histujigaoka 1, Toyohira, Sapporo 062-8555, Japan.
DNA Res. 2007 Oct 31;14(5):217-25. doi: 10.1093/dnares/dsm020. Epub 2007 Nov 13.
In order to reveal quantitative trait loci (QTL) interactions and the relationship between various interactions in complex traits, we have developed a new QTL mapping approach, named genotype matrix mapping (GMM), which searches for QTL interactions in genetic variation. The central approach in GMM is the following. (1) Each tested marker is given a virtual matrix, named a genotype matrix (GM), containing intersecting lines and rows equal to the total allele number for that marker in the population analyzed. (2) QTL interactions are then estimated and compared through virtual networks among the GMs. To evaluate the contribution of marker combinations to a quantitative phenotype, the GMM method divides the samples into two non-overlapping subclasses, S(0) and S(1); the former contains the samples that have a specific genotype pattern to be evaluated, and the latter contains samples that do not. Based on this division, the F-measure is calculated as an index of significance. With the GMM method, we extracted significant marker combinations consisting of one to three interacting markers. The results indicated there were multiple QTL interactions affecting the phenotype (flowering date). GMM will be a valuable approach to identify QTL interactions in genetic variation of a complex trait within a variety of organisms.
为了揭示复杂性状中的数量性状基因座(QTL)相互作用以及各种相互作用之间的关系,我们开发了一种新的QTL定位方法,称为基因型矩阵定位(GMM),该方法在遗传变异中搜索QTL相互作用。GMM的核心方法如下:(1)为每个测试标记赋予一个虚拟矩阵,称为基因型矩阵(GM),其包含的相交行和列等于所分析群体中该标记的等位基因总数。(2)然后通过GM之间的虚拟网络估计和比较QTL相互作用。为了评估标记组合对数量性状表型的贡献,GMM方法将样本分为两个不重叠的子类,S(0)和S(1);前者包含具有特定基因型模式以待评估的样本,后者包含不具有该特定基因型模式的样本。基于这种划分,计算F值作为显著性指标。使用GMM方法,我们提取了由一到三个相互作用标记组成的显著标记组合。结果表明存在多个影响表型(开花日期)的QTL相互作用。GMM将是一种在多种生物体复杂性状的遗传变异中鉴定QTL相互作用的有价值方法。