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Validation of genomic predictions for body weight in broilers using crossbred information and considering breed-of-origin of alleles
Genetics Selection Evolution ( IF 4.1 ) Pub Date : 2019-07-08 , DOI: 10.1186/s12711-019-0481-7
Pascal Duenk , Mario P. L. Calus , Yvonne C. J. Wientjes , Vivian P. Breen , John M. Henshall , Rachel Hawken , Piter Bijma

Pig and poultry breeding programs aim at improving crossbred (CB) performance. Selection response may be suboptimal if only purebred (PB) performance is used to compute genomic estimated breeding values (GEBV) because the genetic correlation between PB and CB performance ($$r_{pc}$$) is often lower than 1. Thus, it may be beneficial to use information on both PB and CB performance. In addition, the accuracy of GEBV of PB animals for CB performance may improve when the breed-of-origin of alleles (BOA) is considered in the genomic relationship matrix (GRM). Thus, our aim was to compare scenarios where GEBV are computed and validated by using (1) either CB offspring averages or individual CB records for validation, (2) either a PB or CB reference population, and (3) a GRM that either accounts for or ignores BOA in the CB individuals. For this purpose, we used data on body weight measured at around 7 (BW7) or 35 (BW35) days in PB and CB broiler chickens and evaluated the accuracy of GEBV based on the correlation GEBV with phenotypes in the validation population (validation correlation). With validation on CB offspring averages, the validation correlation of GEBV of PB animals for CB performance was lower with a CB reference population than with a PB reference population for BW35 ($$r_{pc}$$ = 0.96), and about equal for BW7 ($$r_{pc}$$ = 0.80) when BOA was ignored. However, with validation on individual CB records, the validation correlation was higher with a CB reference population for both traits. The use of a GRM that took BOA into account increased the validation correlation for BW7 but reduced it for BW35. We argue that the benefit of using a CB reference population for genomic prediction of PB animals for CB performance should be assessed either by validation on CB offspring averages, or by validation on individual CB records while using a GRM that accounts for BOA in the CB individuals. With this recommendation in mind, our results show that the accuracy of GEBV of PB animals for CB performance was equal to or higher with a CB reference population than with a PB reference population for a trait with an $$r_{pc}$$ of 0.8, but lower for a trait with an $$r_{pc}$$ of 0.96. In addition, taking BOA into account was beneficial for a trait with an $$r_{pc}$$ of 0.8 but not for a trait with an $$r_{pc}$$ of 0.96.

中文翻译:

利用杂交信息并考虑等位基因的起源,验证肉鸡体重的基因组预测

猪和家禽育种计划旨在提高杂交(CB)性能。如果仅使用纯种(PB)性能来计算基因组估计育种值(GEBV),则选择响应可能不是最佳选择,因为PB和CB性能之间的遗传相关性($$ r_ {pc} $$)通常低于1。因此,同时使用PB和CB性能信息可能会有所帮助。此外,当在基因组关系矩阵(GRM)中考虑等位基因的起源品种(BOA)时,PB动物的GEBV对CB性能的准确性可能会提高。因此,我们的目的是比较通过以下方法计算和验证GEBV的方案:(1)使用CB后代平均值或单个CB记录进行验证;(2)PB或CB参考人群;以及(3)可以使用以下方法计算的GRM:支持或忽略CB个人中的BOA。以此目的,我们使用了PB和CB肉鸡在第7(BW7)或35(BW35)天时测得的体重数据,并根据验证人群中GEBV与表型之间的相关性(验证相关性)评估了GEBV的准确性。通过对CB后代平均值的验证,对于CB参考种群,PB动物对CB性能的GEBV验证相关性低于BW35的PB参考种群($$ r_ {pc} $$ = 0.96),对于忽略BOA时的BW7($$ r_ {pc} $$ = 0.80)。但是,通过对单个CB记录的验证,两种性状的CB参考人群的验证相关性都更高。考虑到BOA的GRM的使用增加了BW7的验证相关性,但减少了BW35的验证相关性。我们认为,使用CB参考种群对PB动物进行CB表现进行基因组预测的益处应该通过对CB后代平均值进行验证,或者通过对单个CB记录进行验证来评估,同时使用在CB个人中占BOA的GRM进行评估。考虑到这一建议,我们的结果表明,对于CB参考种群,PB动物对CB性能的GEBV准确度等于或高于对具有$ r_ {pc} $$的性状的PB参考种群0.8,但对于$$ r_ {pc} $$为0.96的特征而言较低。此外,考虑到BOA对于$ r_ {pc} $$为0.8的特征是有利的,但对于$ r_ {pc} $$为0.96的特征是不利的。或通过在使用CRM个人帐户中的BOA的GRM时通过对单个CB记录进行验证来进行验证。考虑到这一建议,我们的结果表明,对于CB参考种群,PB动物对CB性能的GEBV准确度等于或高于对具有$ r_ {pc} $$的性状的PB参考种群0.8,但对于$$ r_ {pc} $$为0.96的特征而言较低。此外,考虑到BOA对于$ r_ {pc} $$为0.8的特征是有利的,但对于$ r_ {pc} $$为0.96的特征是不利的。或通过在使用CRM个人帐户中的BOA的GRM时通过对单个CB记录进行验证来进行验证。考虑到这一建议,我们的结果表明,对于CB参考种群,PB动物对CB性能的GEBV准确度等于或高于对$ r_ {pc} $$的性状进行PB参考种群0.8,但对于$$ r_ {pc} $$为0.96的特征而言较低。另外,考虑到BOA对于$ r_ {pc} $$为0.8的特征是有益的,但对于$ r_ {pc} $$为0.96的特征是不利的。但对于$ r_ {pc} $$为0.96的特征,则较低。此外,考虑到BOA对于$ r_ {pc} $$为0.8的特征是有利的,但对于$ r_ {pc} $$为0.96的特征是不利的。但对于$ r_ {pc} $$为0.96的特征,则较低。此外,考虑到BOA对于$ r_ {pc} $$为0.8的特征是有利的,但对于$ r_ {pc} $$为0.96的特征是不利的。
更新日期:2019-07-08
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