Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University/JiangSu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095, China.
Int J Mol Sci. 2019 Jan 16;20(2):359. doi: 10.3390/ijms20020359.
Pasmo () is a fungal disease causing major losses in seed yield and quality and stem fibre quality in flax. Pasmo resistance (PR) is quantitative and has low heritability. To improve PR breeding efficiency, the accuracy of genomic prediction (GP) was evaluated using a diverse worldwide core collection of 370 accessions. Four marker sets, including three defined by 500, 134 and 67 previously identified quantitative trait loci (QTL) and one of 52,347 PR-correlated genome-wide single nucleotide polymorphisms, were used to build ridge regression best linear unbiased prediction (RR-BLUP) models using pasmo severity (PS) data collected from field experiments performed during five consecutive years. With five-fold random cross-validation, GP accuracy as high as 0.92 was obtained from the models using the 500 QTL when the average PS was used as the training dataset. GP accuracy increased with training population size, reaching values >0.9 with training population size greater than 185. Linear regression of the observed PS with the number of positive-effect QTL in accessions provided an alternative GP approach with an accuracy of 0.86. The results demonstrate the GP models based on marker information from all identified QTL and the 5-year PS average is highly effective for PR prediction.
黄麻斑点病是一种真菌病，可导致种子产量和质量以及亚麻茎纤维质量的重大损失。黄麻斑点病抗性（PR）是数量性状，遗传力低。为了提高 PR 育种效率，使用来自全球 370 个品系的多样化核心群体评估了基因组预测（GP）的准确性。使用了四个标记集，包括由先前鉴定的 500、134 和 67 个数量性状位点（QTL）和 52,347 个与黄麻斑点病相关的全基因组单核苷酸多态性中的一个定义的三个标记集，用于构建脊回归最佳线性无偏预测（RR-BLUP）模型使用在五年内进行的五次田间试验中收集的黄麻斑点病严重度（PS）数据。使用五倍随机交叉验证，当使用平均 PS 作为训练数据集时，使用 500 个 QTL 的模型获得高达 0.92 的 GP 准确性。GP 准确性随训练群体大小的增加而增加，当训练群体大小大于 185 时，准确性值大于 0.9。用品系中阳性效应 QTL 的数量对观察到的 PS 进行线性回归，提供了一种替代 GP 方法，准确性为 0.86。结果表明，基于所有鉴定的 QTL 的标记信息和 5 年 PS 平均值的 GP 模型对 PR 预测非常有效。
