Lee Yun-Mi, Dang Chang-Gwon, Alam Mohammad Z, Kim You-Sam, Cho Kwang-Hyeon, Park Kyung-Do, Kim Jong-Joo
Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Korea.
Division of Animal Breeding and Genetics, National Institute of Animal Science, RDA, Cheonan 31000, Korea.
Asian-Australas J Anim Sci. 2020 Mar;33(3):382-389. doi: 10.5713/ajas.19.0546. Epub 2019 Dec 24.
This study was conducted to test the efficiency of genomic selection for milk production traits in a Korean Holstein cattle population.
A total of 506,481 milk production records from 293,855 animals (2,090 heads with single nucleotide polymorphism information) were used to estimate breeding value by single step best linear unbiased prediction.
The heritability estimates for milk, fat, and protein yields in the first parity were 0.28, 0.26, and 0.23, respectively. As the parity increased, the heritability decreased for all milk production traits. The estimated generation intervals of sire for the production of bulls (LSB) and that for the production of cows (LSC) were 7.9 and 8.1 years, respectively, and the estimated generation intervals of dams for the production of bulls (LDB) and cows (LDC) were 4.9 and 4.2 years, respectively. In the overall data set, the reliability of genomic estimated breeding value (GEBV) increased by 9% on average over that of estimated breeding value (EBV), and increased by 7% in cows with test records, about 4% in bulls with progeny records, and 13% in heifers without test records. The difference in the reliability between GEBV and EBV was especially significant for the data from young bulls, i.e. 17% on average for milk (39% vs 22%), fat (39% vs 22%), and protein (37% vs 22%) yields, respectively. When selected for the milk yield using GEBV, the genetic gain increased about 7.1% over the gain with the EBV in the cows with test records, and by 2.9% in bulls with progeny records, while the genetic gain increased by about 24.2% in heifers without test records and by 35% in young bulls without progeny records.
More genetic gains can be expected through the use of GEBV than EBV, and genomic selection was more effective in the selection of young bulls and heifers without test records.
本研究旨在测试韩国荷斯坦奶牛群体中基因组选择对产奶性状的效率。
使用来自293,855头动物(2,090头具有单核苷酸多态性信息)的总共506,481条产奶记录,通过单步最佳线性无偏预测来估计育种值。
头胎产奶量、乳脂产量和乳蛋白产量的遗传力估计值分别为0.28、0.26和0.23。随着胎次增加,所有产奶性状的遗传力均下降。公牛生产公牛犊(LSB)和母牛犊(LSC)的估计世代间隔分别为7.9年和8.1年,母牛生产公牛犊(LDB)和母牛犊(LDC)的估计世代间隔分别为4.9年和4.2年。在整个数据集中,基因组估计育种值(GEBV)的可靠性平均比估计育种值(EBV)提高了9%,在有检测记录的母牛中提高了7%,在有后代记录的公牛中提高了约4%,在无检测记录的小母牛中提高了13%。GEBV和EBV之间可靠性的差异在年轻公牛的数据中尤为显著,即产奶量(分别为39%对22%)、乳脂产量(39%对22%)和乳蛋白产量(37%对22%)平均分别提高了17%。当使用GEBV选择产奶量时,有检测记录的母牛的遗传进展比使用EBV时增加了约7.1%;有后代记录公牛的遗传进展增加了2.9%;而无检测记录的小母牛的遗传进展增加了约24.2%,无后代记录的年轻公牛的遗传进展增加了35%。
与EBV相比,使用GEBV有望获得更多的遗传进展,并且基因组选择在选择无检测记录年轻公牛和小母牛方面更有效。