Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures
Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures
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DOI：
10.1186/1297-9686-44-3
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发表时间：
2012-01-24
影响因子：
4.1
通讯作者：
Bovenhuis, Henk
中科院分区：
文献类型：
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作者：
Bastiaansen, John W. M.;Coster, Albart;Bovenhuis, Henk
背景：基因组选择已成为动植物遗传改良的重要工具。本研究的目的是调查育种值估计方法，参考群体结构和性状遗传结构的影响，对长期反应的基因组选择没有更新标记effects.Methods：三种方法被用来估计基因组育种值：具有从全基因组标记估计的关系的BLUP方法（GBLUP）、贝叶斯方法和偏最小二乘回归方法（PLSR）。每种方法都使用浅参考群体（来自一代的个体）或深参考群体（来自五代的个体）。在4种不同的遗传结构下比较了不同选择方法的选择效果。选择是基于三个基因组育种值之一，系谱BLUP育种值，或随机进行。结果：长期选择反应差异较小。对于一个遗传结构与一个非常小的数量3至4个数量性状基因座（QTL），贝叶斯方法实现了响应，是0.05至0.1遗传标准差高于其他方法在第10代。对于具有大约30至300个QTL的遗传结构，PLSR（浅参考）或GBLUP（深参考）在第10代中具有比贝叶斯方法平均0.2遗传标准差的优势。GBLUP导致0.6%和0.9%的近交比PLSR和BM和平均三分之一的遗传方差减少。在早期世代的反应是更大的浅参考种群，而长期的反应是不受参考种群结构。结论：估计方法的排名与没有选择。在选择下，应用GBLUP导致较低的近交和较小的遗传方差的减少，同时实现了类似的选择反应。参考人群结构对长期准确性和反应的影响有限。使用浅参考群体，最密切相关的选择候选人，早期的好处，而在后代，当标记效应没有更新，估计标记效应的基础上更深的参考群体没有回报。
Background: Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects.Methods: Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations.Results: Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure.Conclusions: The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was achieved. The reference population structure had a limited effect on long-term accuracy and response. Use of a shallow reference population, most closely related to the selection candidates, gave early benefits while in later generations, when marker effects were not updated, the estimation of marker effects based on a deeper reference population did not pay off.