Sverrisdóttir Elsa, Byrne Stephen, Sundmark Ea Høegh Riis, Johnsen Heidi Øllegaard, Kirk Hanne Grethe, Asp Torben, Janss Luc, Nielsen Kåre L
Department of Chemistry and Bioscience, Aalborg University, Fredrik Bajers Vej 7H, 9220, Aalborg, Denmark.
Department of Molecular Biology and Genetics, Aarhus University, Forsøgsvej 1, 4200, Slagelse, Denmark.
Theor Appl Genet. 2017 Oct;130(10):2091-2108. doi: 10.1007/s00122-017-2944-y. Epub 2017 Jul 13.
Genomic prediction models for starch content and chipping quality show promising results, suggesting that genomic selection is a feasible breeding strategy in tetraploid potato. Genomic selection uses genome-wide molecular markers to predict performance of individuals and allows selections in the absence of direct phenotyping. It is regarded as a useful tool to accelerate genetic gain in breeding programs, and is becoming increasingly viable for crops as genotyping costs continue to fall. In this study, we have generated genomic prediction models for starch content and chipping quality in tetraploid potato to facilitate varietal development. Chipping quality was evaluated as the colour of a potato chip after frying following cold induced sweetening. We used genotyping-by-sequencing to genotype 762 offspring, derived from a population generated from biparental crosses of 18 tetraploid parents. Additionally, 74 breeding clones were genotyped, representing a test panel for model validation. We generated genomic prediction models from 171,859 single-nucleotide polymorphisms to calculate genomic estimated breeding values. Cross-validated prediction correlations of 0.56 and 0.73 were obtained within the training population for starch content and chipping quality, respectively, while correlations were lower when predicting performance in the test panel, at 0.30-0.31 and 0.42-0.43, respectively. Predictions in the test panel were slightly improved when including representatives from the test panel in the training population but worsened when preceded by marker selection. Our results suggest that genomic prediction is feasible, however, the extremely high allelic diversity of tetraploid potato necessitates large training populations to efficiently capture the genetic diversity of elite potato germplasm and enable accurate prediction across the entire spectrum of elite potatoes. Nonetheless, our results demonstrate that GS is a promising breeding strategy for tetraploid potato.
淀粉含量和薯片加工品质的基因组预测模型显示出了良好的结果，这表明基因组选择是四倍体马铃薯可行的育种策略。基因组选择利用全基因组分子标记来预测个体的表现，并允许在没有直接表型分析的情况下进行选择。它被认为是加速育种计划中遗传增益的有用工具，并且随着基因分型成本的持续下降，对于作物来说变得越来越可行。在本研究中，我们生成了四倍体马铃薯淀粉含量和薯片加工品质的基因组预测模型，以促进品种开发。薯片加工品质通过冷诱导糖化后油炸的薯片颜色来评估。我们使用简化基因组测序对762个后代进行基因分型，这些后代来自18个四倍体亲本双亲杂交产生的群体。此外，对74个育种克隆进行了基因分型，作为模型验证的测试群体。我们从171,859个单核苷酸多态性生成了基因组预测模型，以计算基因组估计育种值。在训练群体中，淀粉含量和薯片加工品质的交叉验证预测相关性分别为0.56和0.73，而在测试群体中预测表现时相关性较低，分别为0.30 - 0.31和0.42 - 0.43。当在训练群体中纳入测试群体的代表时，测试群体中的预测略有改善，但在进行标记选择后预测变差。我们的结果表明基因组预测是可行的，然而，四倍体马铃薯极高的等位基因多样性需要大量的训练群体才能有效地捕获优良马铃薯种质的遗传多样性，并实现对整个优良马铃薯谱的准确预测。尽管如此，我们的结果表明基因组选择是四倍体马铃薯有前景的育种策略。
