Steyn Yvette, Lourenco Daniela A, Chen Ching-Yi, Valente Bruno D, Holl Justin, Herring William O, Misztal Ignacy
Department of Animal and Dairy Science, University of Georgia, Athens, GA.
Genus PIC, Hendersonville, TN.
J Anim Sci. 2021 Jan 1;99(1). doi: 10.1093/jas/skaa396.
In the pig industry, purebred animals are raised in nucleus herds and selected to produce crossbred progeny to perform in commercial environments. Crossbred and purebred performances are different, correlated traits. All purebreds in a pen have their performance assessed together at the end of a performance test. However, only selected crossbreds are removed (based on visual inspection) and measured at different times creating many small contemporary groups (CGs). This may reduce estimated breeding value (EBV) prediction accuracies. Considering this sequential recording of crossbreds, the objective was to investigate the impact of different CG definitions on genetic parameters and EBV prediction accuracy for crossbred traits. Growth rate (GP) and ultrasound backfat (BFP) records were available for purebreds. Lifetime growth (GX) and backfat (BFX) were recorded on crossbreds. Different CGs were tested: CG_all included farm, sex, birth year, and birth week; CG_week added slaughter week; and CG_day used slaughter day instead of week. Data of 124,709 crossbreds were used. The purebred phenotypes (62,274 animals) included three generations of purebred ancestors of these crossbreds and their CG mates. Variance components for four-trait models with different CG definitions were estimated with average information restricted maximum likelihood. Purebred traits' variance components remained stable across CG definitions and varied slightly for BFX. Additive genetic variances (and heritabilities) for GX fluctuated more: 812 ± 36 (0.28 ± 0.01), 257 ± 15 (0.17 ± 0.01), and 204 ± 13 (0.15 ± 0.01) for CG_all, CG_week, and CG_day, respectively. Age at slaughter (AAS) and hot carcass weight (HCW) adjusted for age were investigated as alternatives for GX. Both have potential for selection but lower heritabilities compared with GX: 0.21 ± 0.01 (0.18 ± 0.01), 0.16 ± 0.02 (0.16 + 0.01), and 0.10 ± 0.01 (0.14 ± 0.01) for AAS (HCW) using CG_all, CG_week, and CG_day, respectively. The predictive ability, linear regression (LR) accuracy, bias, and dispersion of crossbred traits in crossbreds favored CG_day, but correlations with unadjusted phenotypes favored CG_all. In purebreds, CG_all showed the best LR accuracy, while showing small relative differences in bias and dispersion. Different CG scenarios showed no relevant impact on BFX EBV. This study shows that different CG definitions may affect evaluation stability and animal ranking. Results suggest that ignoring slaughter dates in CG is more appropriate for estimating crossbred trait EBV for purebred animals.
在养猪业中,纯种动物饲养于核心种畜群中,并经过选育以生产杂交后代,使其能在商业环境中表现良好。杂交种和纯种的性能是不同的相关性状。一栏中的所有纯种动物在性能测试结束时一起评估其性能。然而,只有经过挑选的杂交种(基于目视检查)会被剔除,并在不同时间进行测量,从而形成许多小的同期组(CGs)。这可能会降低估计育种值(EBV)的预测准确性。考虑到杂交种的这种顺序记录方式,本研究的目的是调查不同的同期组定义对杂交性状的遗传参数和EBV预测准确性的影响。纯种动物有生长率(GP)和超声背膘厚(BFP)记录。杂交种记录了终生生长(GX)和背膘厚(BFX)。测试了不同的同期组:CG_all包括农场、性别、出生年份和出生周;CG_week增加了屠宰周;CG_day使用屠宰日而非周。使用了124,709头杂交种的数据。纯种表型(62,274只动物)包括这些杂交种及其同期组同伴的三代纯种祖先。使用平均信息约束最大似然法估计了具有不同同期组定义的四性状模型的方差分量。纯种性状的方差分量在不同的同期组定义下保持稳定,BFX略有变化。GX的加性遗传方差(和遗传力)波动更大:CG_all、CG_week和CG_day分别为812±36(0.28±0.01)、257±15(0.
17±0.01)和204±13(0.15±0.01)。研究了屠宰年龄(AAS)和经年龄调整的热胴体重(HCW)作为GX的替代指标。两者都有选择潜力,但与GX相比遗传力较低:使用CG_all、CG_week和CG_day时,AAS(HCW)的遗传力分别为0.21±0.01(0.18±0.01)、0.16±0.02(0.16 + 0.01)和0.10±0.01(0.14±0.01)。杂交种中杂交性状的预测能力、线性回归(LR)准确性、偏差和离散度有利于CG_day,但与未调整表型的相关性有利于CG_all。在纯种动物中,CG_all显示出最佳的LR准确性,同时在偏差和离散度方面显示出较小的相对差异。不同的同期组方案对BFX EBV没有相关影响。本研究表明,不同的同期组定义可能会影响评估稳定性和动物排名。结果表明,在同期组中忽略屠宰日期更适合估计纯种动物杂交性状的EBV。