Londoño-Gil Marisol, Cardona-Cifuentes Daniel, Espigolan Rafael, Peripolli Elisa, Lôbo Raysildo B, Pereira Angélica S C, Aguilar Ignacio, Baldi Fernando
Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Via de Acesso Prof. Paulo Donato Castellane s/n, CEP, Jaboticabal, SP, 14884-900, Brazil.
Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, Av. Duque de Caxias Norte, 225m Campus Fernando Costa - USP, CEP, Pirassununga, SP, 13635-900, Brazil.
Trop Anim Health Prod. 2023 Feb 21;55(2):95. doi: 10.1007/s11250-023-03508-4.
The aim of this work was to evaluate the impact of applying genomic information in pedigree uncertainty situations on genetic evaluations for growth- and cow productivity-related traits in Nelore commercial herds. Records for accumulated cow productivity (ACP) and adjusted weight at 450 days of age (W450) were used, as well as genotypes of registered and commercial herd animals, genotyped with the Clarifide Nelore 3.1 panel (~29,000 SNPs). The genetic values for commercial and registered populations were estimated using different approaches that included (ssGBLUP) or did not include genomic information (BLUP), with different pedigree structures. Different scenarios were tested, varying the proportion of young animals with unknown sires (0, 25, 50, 75, and 100%), and unknown maternal grandsires (0, 25, 50, 75, and 100%). The prediction accuracies and abilities were calculated. The estimated breeding value accuracies decreased as the proportion of unknown sires and maternal grandsires increased. The genomic estimated breeding value accuracy using the ssGBLUP was higher in scenarios with a lower proportion of known pedigree when compared to the BLUP methodology. The results obtained with the ssGBLUP showed that it is possible to obtain reliable direct and indirect predictions for young animals from commercial herds without pedigree structure.
本研究的目的是评估在系谱不确定情况下应用基因组信息对内洛尔商业牛群生长和奶牛生产性能相关性状遗传评估的影响。使用了累计奶牛生产力（ACP）和450日龄校正体重（W450）的记录，以及使用Clarifide Nelore 3.1芯片（约29,000个单核苷酸多态性）进行基因分型的注册牛群和商业牛群动物的基因型。使用包括（ssGBLUP）或不包括基因组信息（BLUP）的不同方法，以及不同的系谱结构，对内洛尔商业牛群和注册牛群的遗传值进行了估计。测试了不同的场景，改变未知父系（0、25、50、75和100%）和未知母系祖父（0、25、50、75和100%）的幼畜比例。计算了预测准确性和能力。随着未知父系和母系祖父比例的增加，估计育种值准确性降低。与BLUP方法相比，在已知系谱比例较低的情况下，使用ssGBLUP的基因组估计育种值准确性更高。使用ssGBLUP获得的结果表明，对于没有系谱结构的商业牛群中的幼畜，可以获得可靠的直接和间接预测。
