Genomic Predictability of Interconnected Biparental Maize Populations
Genomic Predictability of Interconnected Biparental Maize Populations
复制标题
DOI：
10.1534/genetics.113.150227
复制
发表时间：
2013-06-01
期刊：
影响因子：
3.3
通讯作者：
Melchinger, Albrecht E.
中科院分区：
文献类型：
--
作者：
Riedelsheimer, Christian;Endelman, Jeffrey B.;Melchinger, Albrecht E.
植物育种群体的高度结构化对基因组选择中训练集的设计提出了挑战。一个重要的开放问题是如何从多个相关或不相关的小双亲本家庭中构建TS来预测个体杂交的后代。本研究以来自4个亲本的5个相互关联的双单倍体（DH）玉米（Zea mays L.）群体为研究对象，系统地研究了TS的组成对单交系预测精度的影响。在赤霉素穗腐病严重程度和籽粒产量组成性状等5个性状上，对635个DH系进行了基因分型，共检测到16741个多态性SNPs。种群表现出基因组相似性模式，这反映了全兄妹、半兄妹和无亲缘关系群体明显分离的杂交方案。在DH系全同胞家族内的预测精度与理论预期密切相关，考虑到样本量和性状遗传力的影响。如果用半同胞DH系代替全同胞DH系，预测精度下降42%，但如果从验证群体的双亲而不是只有一个亲本获得半同胞DH系，则可以获得统计学上显著更好的结果。一旦验证群体的双亲在TS中都有代表，包括更多具有恒定TS大小的杂交并不会增加准确性。如果单独使用或与相关家族组合使用，则与验证群体显示相反连锁阶段的不相关杂交分别导致负面或降低预测准确性。此外，观察到的种群和性状之间的变异表明，在优化遗传资源配置的模型中，必须考虑这些不确定性。
Intense structuring of plant breeding populations challenges the design of the training set (TS) in genomic selection (GS). An important open question is how the TS should be constructed from multiple related or unrelated small biparental families to predict progeny from individual crosses. Here, we used a set of five interconnected maize (Zea mays L.) populations of doubled-haploid (DH) lines derived from four parents to systematically investigate how the composition of the TS affects the prediction accuracy for lines from individual crosses. A total of 635 DH lines genotyped with 16,741 polymorphic SNPs were evaluated for five traits including Gibberella ear rot severity and three kernel yield component traits. The populations showed a genomic similarity pattern, which reflects the crossing scheme with a clear separation of full sibs, half sibs, and unrelated groups. Prediction accuracies within full-sib families of DH lines followed closely theoretical expectations, accounting for the influence of sample size and heritability of the trait. Prediction accuracies declined by 42% if full-sib DH lines were replaced by half-sib DH lines, but statistically significantly better results could be achieved if half-sib DH lines were available from both instead of only one parent of the validation population. Once both parents of the validation population were represented in the TS, including more crosses with a constant TS size did not increase accuracies. Unrelated crosses showing opposite linkage phases with the validation population resulted in negative or reduced prediction accuracies, if used alone or in combination with related families, respectively. We suggest identifying and excluding such crosses from the TS. Moreover, the observed variability among populations and traits suggests that these uncertainties must be taken into account in models optimizing the allocation of resources in GS.