1Department of Molecular Biology and Genetics,Center for Quantitative Genetics and Genomics,Aarhus University,DK-8830 Tjele,Denmark.
2Seges,DK-8200 Aarhus,Denmark.
Animal. 2016 Jun;10(6):1067-75. doi: 10.1017/S1751731115001792. Epub 2015 Sep 2.
Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such like Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing size of reference population in Danish Jersey. The first approach was to include North American Jersey bulls in Danish Jersey reference population. The second was to genotype cows and use them as reference animals. The validation of genomic prediction was carried out on bulls and cows, respectively. In validation on bulls, about 300 Danish bulls (depending on traits) born in 2005 and later were used as validation data, and the reference populations were: (1) about 1050 Danish bulls, (2) about 1050 Danish bulls and about 1150 US bulls. In validation on cows, about 3000 Danish cows from 87 young half-sib families were used as validation data, and the reference populations were: (1) about 1250 Danish bulls, (2) about 1250 Danish bulls and about 1150 US bulls, (3) about 1250 Danish bulls and about 4800 cows, (4) about 1250 Danish bulls, 1150 US bulls and 4800 Danish cows. Genomic best linear unbiased prediction model was used to predict breeding values. De-regressed proofs were used as response variables. In the validation on bulls for eight traits, the joint DK-US bull reference population led to higher reliability of genomic prediction than the DK bull reference population for six traits, but not for fertility and longevity. Averaged over the eight traits, the gain was 3 percentage points. In the validation on cows for six traits (fertility and longevity were not available), the gain from inclusion of US bull in reference population was 6.6 percentage points in average over the six traits, and the gain from inclusion of cows was 8.2 percentage points. However, the gains from cows and US bulls were not accumulative. The total gain of including both US bulls and Danish cows was 10.5 percentage points. The results indicate that sharing reference data and including cows in reference population are efficient approaches to increase reliability of genomic prediction. Therefore, genomic selection is promising for numerically small population.
小规模参考群体限制了数量较少的品种(如丹麦泽西牛)的基因组预测准确性。本研究的目的是探讨两种方法,通过增加丹麦泽西牛参考群体的规模来提高基因组预测的准确性。第一种方法是将北美泽西公牛纳入丹麦泽西牛参考群体。第二种方法是对奶牛进行基因分型并将其用作参考动物。分别对公牛和奶牛进行基因组预测验证。在对公牛的验证中,使用了大约 300 头(取决于性状)2005 年及以后出生的丹麦公牛作为验证数据,参考群体为:(1)约 1050 头丹麦公牛,(2)约 1050 头丹麦公牛和约 1150 头美国公牛。在对奶牛的验证中,使用了 87 个年轻半同胞家系的约 3000 头丹麦奶牛作为验证数据,参考群体为:(1)约 1250 头丹麦公牛,(2)约 1250 头丹麦公牛和约 1150 头美国公牛,(3)约 1250 头丹麦公牛和约 4800 头奶牛,(4)约 1250 头丹麦公牛、1150 头美国公牛和约 4800 头丹麦奶牛。使用基因组最佳线性无偏预测模型预测育种值。去回归证据用作响应变量。在对 8 个性状的公牛验证中,丹麦-美国联合公牛参考群体比丹麦公牛参考群体在 6 个性状上具有更高的基因组预测可靠性,但在繁殖力和寿命上并非如此。在 8 个性状的平均水平上,增益为 3 个百分点。在对 6 个性状(繁殖力和寿命不可用)的奶牛验证中,引入美国公牛参考群体的平均增益为 6.6 个百分点,引入奶牛的增益为 8.2 个百分点。然而,奶牛和美国公牛的增益并非累加的。同时纳入美国公牛和丹麦奶牛的总增益为 10.5 个百分点。结果表明,共享参考数据和将奶牛纳入参考群体是提高基因组预测可靠性的有效方法。因此,基因组选择对于数量较少的群体是有前途的。