Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection.
Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection.
复制标题
DOI：
10.1007/s00122-018-3125-3
复制
发表时间：
2018-09
期刊：
影响因子：
--
通讯作者：
Hickey JM
中科院分区：
文献类型：
--
作者：
Gorjanc G;Gaynor RC;Hickey JM
关键信息最佳交叉选择增加了快速循环基因组选择的两部分计划的长期遗传增益。它通过减少遗传多样性的损失和通过快速循环减少基因组预测精度的下降来优化将遗传多样性转化为遗传收益的效率。这项研究评估了在两部分植物育种计划和快速轮回基因组选择中平衡选择和保持遗传多样性的最佳杂交选择。这项由两部分组成的计划将传统育种计划重组为群体改良部分和产品开发部分，前者通过循环基因组选择来提高种质的平均值，后者采用标准方法来开发新品系。快速循环的基因组选择有很大的潜力，但由于基因分型成本或遗传漂移而具有挑战性。在这里，我们模拟了一个为期20年的小麦育种计划，并比较了群体改良部分的最优杂交选择和截尾选择每年一到六个周期。对于截断选择，我们交叉了少量或大量的亲本。通过最优交叉选择，我们与AlphaMate程序联合优化了选择、遗传多样性的保持和交叉分配。结果表明，最优交叉选择的两部分方案获得了最大的遗传增益，且随着周期数的增加而增加。与亲本数目少(多)的截尾选择相比，每年4个周期的优化杂交选择的长期遗传增益高出78%(15%)。通过提高遗传多样性转化为遗传增益的效率，获得了更高的遗传增益；最优杂交选择在亲本数量较少(较多)的情况下，截尾选择的效率提高了四倍(两倍)。最优交叉选择也减少了由于训练群体和预测群体之间的漂移而导致的基因组选择精度的下降。总之，最佳杂交选择使群体改良种质的最佳管理和利用分两部分进行。本文的在线版本(10.1007/s00122-0183125-3)包含向授权用户提供的补充材料。
Key message Optimal cross selection increases long-term genetic gain of two-part programs with rapid recurrent genomic selection. It achieves this by optimising efficiency of converting genetic diversity into genetic gain through reducing the loss of genetic diversity and reducing the drop of genomic prediction accuracy with rapid cycling. This study evaluates optimal cross selection to balance selection and maintenance of genetic diversity in two-part plant breeding programs with rapid recurrent genomic selection. The two-part program reorganises a conventional breeding program into a population improvement component with recurrent genomic selection to increase the mean value of germplasm and a product development component with standard methods to develop new lines. Rapid recurrent genomic selection has a large potential, but is challenging due to genotyping costs or genetic drift. Here we simulate a wheat breeding program for 20 years and compare optimal cross selection against truncation selection in the population improvement component with one to six cycles per year. With truncation selection we crossed a small or a large number of parents. With optimal cross selection we jointly optimised selection, maintenance of genetic diversity, and cross allocation with AlphaMate program. The results show that the two-part program with optimal cross selection delivered the largest genetic gain that increased with the increasing number of cycles. With four cycles per year optimal cross selection had 78% (15%) higher long-term genetic gain than truncation selection with a small (large) number of parents. Higher genetic gain was achieved through higher efficiency of converting genetic diversity into genetic gain; optimal cross selection quadrupled (doubled) efficiency of truncation selection with a small (large) number of parents. Optimal cross selection also reduced the drop of genomic selection accuracy due to the drift between training and prediction populations. In conclusion optimal cross selection enables optimal management and exploitation of population improvement germplasm in two-part programs. The online version of this article (10.1007/s00122-018-3125-3) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子：
3.3
作者：
Habier, D.;Fernando, R. L.;Dekkers, J. C. M.
通讯作者：
Dekkers, J. C. M.
影响因子：
2.3
作者：
Bernardo, Rex
通讯作者：
Bernardo, Rex
影响因子：
3.3
作者：
De Beukelaer, Herman;Badke, Yvonne;De Meyer, Geert
通讯作者：
De Meyer, Geert
影响因子：
3.5
作者：
Pszczola, M.;Strabel, T.;Calus, M. P. L.
通讯作者：
Calus, M. P. L.
影响因子：
2.3
作者：
Hickey, John M.;Dreisigacker, Susanne;Gorjanc, Gregor
通讯作者：
Gorjanc, Gregor