Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection
Moving Beyond Managing Realized Genomic Relationship in Long-Term Genomic Selection
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DOI：
10.1534/genetics.116.194449
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发表时间：
2017-06-01
期刊：
影响因子：
3.3
通讯作者：
De Meyer, Geert
中科院分区：
文献类型：
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作者：
De Beukelaer, Herman;Badke, Yvonne;De Meyer, Geert
长期基因组选择（GS）需要平衡遗传增益和种群多样性的策略，以维持选择下的性状进展，并保持未来育种的多样性。在循环选择方案的模拟模型中，我们首次对两种现有策略进行了头对头比较：基因组最佳贡献选择（GOCS），它限制了选择候选者之间已实现的基因组关系，以及加权基因组选择（WGS），它扩大了 GS 中罕见的等位基因效应。与 GS 相比，这两种方法都提供了相同的更高的长期遗传增益和类似的更低的近交率，尽管存在一些固有的局限性。 GOCS 不控制与性状选择相关的近交率部分，因此无法在遗传增益和近交之间达到最佳平衡。这使得它在整个育种计划中效率较低，尤其是在开始时，遗传增益和多样性可能不存在竞争。对于全基因组测序，截断选择被证明对于管理选择候选者中的稀有等位基因频率而言不是最佳选择。为了克服这些限制，我们引入了两种新的集合选择方法，这些方法可以最大化平衡遗传增益与控制预期杂合性（IND-HE）或维持稀有等位基因（IND-RA）的加权指数，并表明这些方法以几乎相同的方式优于 GOCS 和 WGS。虽然需要进一步测试，但我们相信 IND-HE 和 IND-RA 方法的固有优势将从我们的模拟框架转移到许多实际育种环境中，因此是朝着高效的长期基因组选择迈出的重要一步。
Long-term genomic selection (GS) requires strategies that balance genetic gain with population diversity, to sustain progress for traits under selection, and to keep diversity for future breeding. In a simulation model for a recurrent selection scheme, we provide the first head-to-head comparison of two such existing strategies: genomic optimal contributions selection (GOCS), which limits realized genomic relationship among selection candidates, and weighted genomic selection (WGS), which upscales rare allele effects in GS. Compared to GS, both methods provide the same higher long-term genetic gain and a similar lower inbreeding rate, despite some inherent limitations. GOCS does not control the inbreeding rate component linked to trait selection, and, therefore, does not strike the optimal balance between genetic gain and inbreeding. This makes it less effective throughout the breeding scheme, and particularly so at the beginning, where genetic gain and diversity may not be competing. For WGS, truncation selection proved suboptimal to manage rare allele frequencies among the selection candidates. To overcome these limitations, we introduce two new set selection methods that maximize a weighted index balancing genetic gain with controlling expected heterozygosity (IND-HE) or maintaining rare alleles (IND-RA), and show that these outperform GOCS and WGS in a nearly identical way. While requiring further testing, we believe that the inherent benefits of the IND-HE and IND-RA methods will transfer from our simulation framework to many practical breeding settings, and are therefore a major step forward toward efficient long-term genomic selection.