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The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

文献类型： 外文期刊

作者： Wei, Chen 1 ; Luo, Hanpeng 3 ; Zhao, Bingru 3 ; Tian, Kechuan 2 ; Huang, Xixia 1 ; Wang, Yachun 3 ; Fu, Xuefeng 2 ; Tian, 1 ;

作者机构： 1.Xinjiang Agr Univ, Coll Anim Sci, Urumqi 830052, Peoples R China

2.Xinjiang Acad Anim Sci, Inst Anim Sci, Key Lab Genet Breeding & Reprod Xinjiang Cashmere, Urumqi 830011, Peoples R China

3.China Agr Univ, Coll Anim Sci & Technol, Lab Anim Genet Breeding & Reprod, Minist Agr China,Natl Engn Lab Anim Breeding, Beijing 100193, Peoples R China

4.Xinjiang Gonaisi Fine Wool Sheep Breeding Farm, Xinjiang 835800, Ili Kazak Auton, Peoples R China

关键词： Chinese Merino sheep; wool traits; Bayesian inference; single-step GBLUP

期刊名称：ANIMALS （ 影响因子：2.752； 五年影响因子：2.942 ）

ISSN： 2076-2615

年卷期： 2020 年 10 卷 4 期

页码：

收录情况： SCI

摘要： Simple Summary Genetic improvement of wool production and quality traits in fine-wool sheep is an appealing option for enhancing the market value of wool products. We estimated genetic parameters and the accuracies of estimated breeding values for various wool production and quality traits in fine-wool sheep using pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) strategies. ssGBLUP performed slightly better than PBLUP for the studied traits. Therefore, the single-step genetic evaluation method could be successfully implemented in genomic evaluations of fine-wool sheep and the prediction of future breeding values in young Merino sheep as part of an early preselection strategy in the near future. Abstract Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992-2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h(2) values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

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